Tag Archives: artificial intelligence

Less is more—a superconducting synapse

It seems the US National Institute of Standards and Technology (NIST) is more deeply invested into developing artificial brains than I had realized (See: April 17, 2018 posting). A January 26, 2018 NIST news release on EurekAlert describes the organization’s latest foray into the field,

Researchers at the National Institute of Standards and Technology (NIST) have built a superconducting switch that “learns” like a biological system and could connect processors and store memories in future computers operating like the human brain.

The NIST switch, described in Science Advances, is called a synapse, like its biological counterpart, and it supplies a missing piece for so-called neuromorphic computers. Envisioned as a new type of artificial intelligence, such computers could boost perception and decision-making for applications such as self-driving cars and cancer diagnosis.

A synapse is a connection or switch between two brain cells. NIST’s artificial synapse–a squat metallic cylinder 10 micrometers in diameter–is like the real thing because it can process incoming electrical spikes to customize spiking output signals. This processing is based on a flexible internal design that can be tuned by experience or its environment. The more firing between cells or processors, the stronger the connection. Both the real and artificial synapses can thus maintain old circuits and create new ones. Even better than the real thing, the NIST synapse can fire much faster than the human brain–1 billion times per second, compared to a brain cell’s 50 times per second–using just a whiff of energy, about one ten-thousandth as much as a human synapse. In technical terms, the spiking energy is less than 1 attojoule, lower than the background energy at room temperature and on a par with the chemical energy bonding two atoms in a molecule.

“The NIST synapse has lower energy needs than the human synapse, and we don’t know of any other artificial synapse that uses less energy,” NIST physicist Mike Schneider said.

The new synapse would be used in neuromorphic computers made of superconducting components, which can transmit electricity without resistance, and therefore, would be more efficient than other designs based on semiconductors or software. Data would be transmitted, processed and stored in units of magnetic flux. Superconducting devices mimicking brain cells and transmission lines have been developed, but until now, efficient synapses–a crucial piece–have been missing.

The brain is especially powerful for tasks like context recognition because it processes data both in sequence and simultaneously and stores memories in synapses all over the system. A conventional computer processes data only in sequence and stores memory in a separate unit.

The NIST synapse is a Josephson junction, long used in NIST voltage standards. These junctions are a sandwich of superconducting materials with an insulator as a filling. When an electrical current through the junction exceeds a level called the critical current, voltage spikes are produced. The synapse uses standard niobium electrodes but has a unique filling made of nanoscale clusters of manganese in a silicon matrix.

The nanoclusters–about 20,000 per square micrometer–act like tiny bar magnets with “spins” that can be oriented either randomly or in a coordinated manner.

“These are customized Josephson junctions,” Schneider said. “We can control the number of nanoclusters pointing in the same direction, which affects the superconducting properties of the junction.”

The synapse rests in a superconducting state, except when it’s activated by incoming current and starts producing voltage spikes. Researchers apply current pulses in a magnetic field to boost the magnetic ordering, that is, the number of nanoclusters pointing in the same direction. This magnetic effect progressively reduces the critical current level, making it easier to create a normal conductor and produce voltage spikes.

The critical current is the lowest when all the nanoclusters are aligned. The process is also reversible: Pulses are applied without a magnetic field to reduce the magnetic ordering and raise the critical current. This design, in which different inputs alter the spin alignment and resulting output signals, is similar to how the brain operates.

Synapse behavior can also be tuned by changing how the device is made and its operating temperature. By making the nanoclusters smaller, researchers can reduce the pulse energy needed to raise or lower the magnetic order of the device. Raising the operating temperature slightly from minus 271.15 degrees C (minus 456.07 degrees F) to minus 269.15 degrees C (minus 452.47 degrees F), for example, results in more and higher voltage spikes.

Crucially, the synapses can be stacked in three dimensions (3-D) to make large systems that could be used for computing. NIST researchers created a circuit model to simulate how such a system would operate.

The NIST synapse’s combination of small size, superfast spiking signals, low energy needs and 3-D stacking capability could provide the means for a far more complex neuromorphic system than has been demonstrated with other technologies, according to the paper.

NIST has prepared an animation illustrating the research,

Caption: This is an animation of how NIST’s artificial synapse works. Credit: Sean Kelley/NIST

Here’s a link to and a citation for the paper,

Ultralow power artificial synapses using nanotextured magnetic Josephson junctions by Michael L. Schneider, Christine A. Donnelly, Stephen E. Russek, Burm Baek, Matthew R. Pufall, Peter F. Hopkins, Paul D. Dresselhaus, Samuel P. Benz, and William H. Rippard. Science Advances 26 Jan 2018: Vol. 4, no. 1, e1701329 DOI: 10.1126/sciadv.1701329

This paper is open access.

Samuel K. Moore in a January 26, 2018 posting on the Nanoclast blog (on the IEEE [Institute for Electrical and Electronics Engineers] website) describes the research and adds a few technical explanations such as this about the Josephson junction,

In a magnetic Josephson junction, that “weak link” is magnetic. The higher the magnetic field, the lower the critical current needed to produce voltage spikes. In the device Schneider and his colleagues designed, the magnetic field is caused by 20,000 or so nanometer-scale clusters of manganese embedded in silicon. …

Moore also provides some additional links including this one to his November 29, 2017 posting where he describes four new approaches to computing including quantum computing and neuromorphic (brain-like) computing.

New path to viable memristor/neuristor?

I first stumbled onto memristors and the possibility of brain-like computing sometime in 2008 (around the time that R. Stanley Williams and his team at HP Labs first published the results of their research linking Dr. Leon Chua’s memristor theory to their attempts to shrink computer chips). In the almost 10 years since, scientists have worked hard to utilize memristors in the field of neuromorphic (brain-like) engineering/computing.

A January 22, 2018 news item on phys.org describes the latest work,

When it comes to processing power, the human brain just can’t be beat.

Packed within the squishy, football-sized organ are somewhere around 100 billion neurons. At any given moment, a single neuron can relay instructions to thousands of other neurons via synapses—the spaces between neurons, across which neurotransmitters are exchanged. There are more than 100 trillion synapses that mediate neuron signaling in the brain, strengthening some connections while pruning others, in a process that enables the brain to recognize patterns, remember facts, and carry out other learning tasks, at lightning speeds.

Researchers in the emerging field of “neuromorphic computing” have attempted to design computer chips that work like the human brain. Instead of carrying out computations based on binary, on/off signaling, like digital chips do today, the elements of a “brain on a chip” would work in an analog fashion, exchanging a gradient of signals, or “weights,” much like neurons that activate in various ways depending on the type and number of ions that flow across a synapse.

In this way, small neuromorphic chips could, like the brain, efficiently process millions of streams of parallel computations that are currently only possible with large banks of supercomputers. But one significant hangup on the way to such portable artificial intelligence has been the neural synapse, which has been particularly tricky to reproduce in hardware.

Now engineers at MIT [Massachusetts Institute of Technology] have designed an artificial synapse in such a way that they can precisely control the strength of an electric current flowing across it, similar to the way ions flow between neurons. The team has built a small chip with artificial synapses, made from silicon germanium. In simulations, the researchers found that the chip and its synapses could be used to recognize samples of handwriting, with 95 percent accuracy.

A January 22, 2018 MIT news release by Jennifer Chua (also on EurekAlert), which originated the news item, provides more detail about the research,

The design, published today [January 22, 2018] in the journal Nature Materials, is a major step toward building portable, low-power neuromorphic chips for use in pattern recognition and other learning tasks.

The research was led by Jeehwan Kim, the Class of 1947 Career Development Assistant Professor in the departments of Mechanical Engineering and Materials Science and Engineering, and a principal investigator in MIT’s Research Laboratory of Electronics and Microsystems Technology Laboratories. His co-authors are Shinhyun Choi (first author), Scott Tan (co-first author), Zefan Li, Yunjo Kim, Chanyeol Choi, and Hanwool Yeon of MIT, along with Pai-Yu Chen and Shimeng Yu of Arizona State University.

Too many paths

Most neuromorphic chip designs attempt to emulate the synaptic connection between neurons using two conductive layers separated by a “switching medium,” or synapse-like space. When a voltage is applied, ions should move in the switching medium to create conductive filaments, similarly to how the “weight” of a synapse changes.

But it’s been difficult to control the flow of ions in existing designs. Kim says that’s because most switching mediums, made of amorphous materials, have unlimited possible paths through which ions can travel — a bit like Pachinko, a mechanical arcade game that funnels small steel balls down through a series of pins and levers, which act to either divert or direct the balls out of the machine.

Like Pachinko, existing switching mediums contain multiple paths that make it difficult to predict where ions will make it through. Kim says that can create unwanted nonuniformity in a synapse’s performance.

“Once you apply some voltage to represent some data with your artificial neuron, you have to erase and be able to write it again in the exact same way,” Kim says. “But in an amorphous solid, when you write again, the ions go in different directions because there are lots of defects. This stream is changing, and it’s hard to control. That’s the biggest problem — nonuniformity of the artificial synapse.”

A perfect mismatch

Instead of using amorphous materials as an artificial synapse, Kim and his colleagues looked to single-crystalline silicon, a defect-free conducting material made from atoms arranged in a continuously ordered alignment. The team sought to create a precise, one-dimensional line defect, or dislocation, through the silicon, through which ions could predictably flow.

To do so, the researchers started with a wafer of silicon, resembling, at microscopic resolution, a chicken-wire pattern. They then grew a similar pattern of silicon germanium — a material also used commonly in transistors — on top of the silicon wafer. Silicon germanium’s lattice is slightly larger than that of silicon, and Kim found that together, the two perfectly mismatched materials can form a funnel-like dislocation, creating a single path through which ions can flow.

The researchers fabricated a neuromorphic chip consisting of artificial synapses made from silicon germanium, each synapse measuring about 25 nanometers across. They applied voltage to each synapse and found that all synapses exhibited more or less the same current, or flow of ions, with about a 4 percent variation between synapses — a much more uniform performance compared with synapses made from amorphous material.

They also tested a single synapse over multiple trials, applying the same voltage over 700 cycles, and found the synapse exhibited the same current, with just 1 percent variation from cycle to cycle.

“This is the most uniform device we could achieve, which is the key to demonstrating artificial neural networks,” Kim says.

Writing, recognized

As a final test, Kim’s team explored how its device would perform if it were to carry out actual learning tasks — specifically, recognizing samples of handwriting, which researchers consider to be a first practical test for neuromorphic chips. Such chips would consist of “input/hidden/output neurons,” each connected to other “neurons” via filament-based artificial synapses.

Scientists believe such stacks of neural nets can be made to “learn.” For instance, when fed an input that is a handwritten ‘1,’ with an output that labels it as ‘1,’ certain output neurons will be activated by input neurons and weights from an artificial synapse. When more examples of handwritten ‘1s’ are fed into the same chip, the same output neurons may be activated when they sense similar features between different samples of the same letter, thus “learning” in a fashion similar to what the brain does.

Kim and his colleagues ran a computer simulation of an artificial neural network consisting of three sheets of neural layers connected via two layers of artificial synapses, the properties of which they based on measurements from their actual neuromorphic chip. They fed into their simulation tens of thousands of samples from a handwritten recognition dataset commonly used by neuromorphic designers, and found that their neural network hardware recognized handwritten samples 95 percent of the time, compared to the 97 percent accuracy of existing software algorithms.

The team is in the process of fabricating a working neuromorphic chip that can carry out handwriting-recognition tasks, not in simulation but in reality. Looking beyond handwriting, Kim says the team’s artificial synapse design will enable much smaller, portable neural network devices that can perform complex computations that currently are only possible with large supercomputers.

“Ultimately we want a chip as big as a fingernail to replace one big supercomputer,” Kim says. “This opens a stepping stone to produce real artificial hardware.”

This research was supported in part by the National Science Foundation.

Here’s a link to and a citation for the paper,

SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations by Shinhyun Choi, Scott H. Tan, Zefan Li, Yunjo Kim, Chanyeol Choi, Pai-Yu Chen, Hanwool Yeon, Shimeng Yu, & Jeehwan Kim. Nature Materials (2018) doi:10.1038/s41563-017-0001-5 Published online: 22 January 2018

This paper is behind a paywall.

For the curious I have included a number of links to recent ‘memristor’ postings here,

January 22, 2018: Memristors at Masdar

January 3, 2018: Mott memristor

August 24, 2017: Neuristors and brainlike computing

June 28, 2017: Dr. Wei Lu and bio-inspired ‘memristor’ chips

May 2, 2017: Predicting how a memristor functions

December 30, 2016: Changing synaptic connectivity with a memristor

December 5, 2016: The memristor as computing device

November 1, 2016: The memristor as the ‘missing link’ in bioelectronic medicine?

You can find more by using ‘memristor’ as the search term in the blog search function or on the search engine of your choice.

The Hedy Lamarr of international research: Canada’s Third assessment of The State of Science and Technology and Industrial Research and Development in Canada (2 of 2)

Taking up from where I left off with my comments on Competing in a Global Innovation Economy: The Current State of R and D in Canada or as I prefer to call it the Third assessment of Canadas S&T (science and technology) and R&D (research and development). (Part 1 for anyone who missed it).

Is it possible to get past Hedy?

Interestingly (to me anyway), one of our R&D strengths, the visual and performing arts, features sectors where a preponderance of people are dedicated to creating culture in Canada and don’t spend a lot of time trying to make money so they can retire before the age of 40 as so many of our start-up founders do. (Retiring before the age of 40 just reminded me of Hollywood actresses {Hedy] who found and still do find that work was/is hard to come by after that age. You may be able but I’m not sure I can get past Hedy.) Perhaps our business people (start-up founders) could take a leaf out of the visual and performing arts handbook? Or, not. There is another question.

Does it matter if we continue to be a ‘branch plant’ economy? Somebody once posed that question to me when I was grumbling that our start-ups never led to larger businesses and acted more like incubators (which could describe our R&D as well),. He noted that Canadians have a pretty good standard of living and we’ve been running things this way for over a century and it seems to work for us. Is it that bad? I didn’t have an  answer for him then and I don’t have one now but I think it’s a useful question to ask and no one on this (2018) expert panel or the previous expert panel (2013) seems to have asked.

I appreciate that the panel was constrained by the questions given by the government but given how they snuck in a few items that technically speaking were not part of their remit, I’m thinking they might have gone just a bit further. The problem with answering the questions as asked is that if you’ve got the wrong questions, your answers will be garbage (GIGO; garbage in, garbage out) or, as is said, where science is concerned, it’s the quality of your questions.

On that note, I would have liked to know more about the survey of top-cited researchers. I think looking at the questions could have been quite illuminating and I would have liked some information on from where (geographically and area of specialization) they got most of their answers. In keeping with past practice (2012 assessment published in 2013), there is no additional information offered about the survey questions or results. Still, there was this (from the report released April 10, 2018; Note: There may be some difference between the formatting seen here and that seen in the document),

3.1.2 International Perceptions of Canadian Research
As with the 2012 S&T report, the CCA commissioned a survey of top-cited researchers’ perceptions of Canada’s research strength in their field or subfield relative to that of other countries (Section 1.3.2). Researchers were asked to identify the top five countries in their field and subfield of expertise: 36% of respondents (compared with 37% in the 2012 survey) from across all fields of research rated Canada in the top five countries in their field (Figure B.1 and Table B.1 in the appendix). Canada ranks fourth out of all countries, behind the United States, United Kingdom, and Germany, and ahead of France. This represents a change of about 1 percentage point from the overall results of the 2012 S&T survey. There was a 4 percentage point decrease in how often France is ranked among the top five countries; the ordering of the top five countries, however, remains the same.

When asked to rate Canada’s research strength among other advanced countries in their field of expertise, 72% (4,005) of respondents rated Canadian research as “strong” (corresponding to a score of 5 or higher on a 7-point scale) compared with 68% in the 2012 S&T survey (Table 3.4). [pp. 40-41 Print; pp. 78-70 PDF]

Before I forget, there was mention of the international research scene,

Growth in research output, as estimated by number of publications, varies considerably for the 20 top countries. Brazil, China, India, Iran, and South Korea have had the most significant increases in publication output over the last 10 years. [emphases mine] In particular, the dramatic increase in China’s output means that it is closing the gap with the United States. In 2014, China’s output was 95% of that of the United States, compared with 26% in 2003. [emphasis mine]

Table 3.2 shows the Growth Index (GI), a measure of the rate at which the research output for a given country changed between 2003 and 2014, normalized by the world growth rate. If a country’s growth in research output is higher than the world average, the GI score is greater than 1.0. For example, between 2003 and 2014, China’s GI score was 1.50 (i.e., 50% greater than the world average) compared with 0.88 and 0.80 for Canada and the United States, respectively. Note that the dramatic increase in publication production of emerging economies such as China and India has had a negative impact on Canada’s rank and GI score (see CCA, 2016).

As long as I’ve been blogging (10 years), the international research community (in particular the US) has been looking over its shoulder at China.

Patents and intellectual property

As an inventor, Hedy got more than one patent. Much has been made of the fact that  despite an agreement, the US Navy did not pay her or her partner (George Antheil) for work that would lead to significant military use (apparently, it was instrumental in the Bay of Pigs incident, for those familiar with that bit of history), GPS, WiFi, Bluetooth, and more.

Some comments about patents. They are meant to encourage more innovation by ensuring that creators/inventors get paid for their efforts .This is true for a set time period and when it’s over, other people get access and can innovate further. It’s not intended to be a lifelong (or inheritable) source of income. The issue in Lamarr’s case is that the navy developed the technology during the patent’s term without telling either her or her partner so, of course, they didn’t need to compensate them despite the original agreement. They really should have paid her and Antheil.

The current patent situation, particularly in the US, is vastly different from the original vision. These days patents are often used as weapons designed to halt innovation. One item that should be noted is that the Canadian federal budget indirectly addressed their misuse (from my March 16, 2018 posting),

Surprisingly, no one else seems to have mentioned a new (?) intellectual property strategy introduced in the document (from Chapter 2: Progress; scroll down about 80% of the way, Note: The formatting has been changed),

Budget 2018 proposes measures in support of a new Intellectual Property Strategy to help Canadian entrepreneurs better understand and protect intellectual property, and get better access to shared intellectual property.

What Is a Patent Collective?
A Patent Collective is a way for firms to share, generate, and license or purchase intellectual property. The collective approach is intended to help Canadian firms ensure a global “freedom to operate”, mitigate the risk of infringing a patent, and aid in the defence of a patent infringement suit.

Budget 2018 proposes to invest $85.3 million over five years, starting in 2018–19, with $10 million per year ongoing, in support of the strategy. The Minister of Innovation, Science and Economic Development will bring forward the full details of the strategy in the coming months, including the following initiatives to increase the intellectual property literacy of Canadian entrepreneurs, and to reduce costs and create incentives for Canadian businesses to leverage their intellectual property:

  • To better enable firms to access and share intellectual property, the Government proposes to provide $30 million in 2019–20 to pilot a Patent Collective. This collective will work with Canada’s entrepreneurs to pool patents, so that small and medium-sized firms have better access to the critical intellectual property they need to grow their businesses.
  • To support the development of intellectual property expertise and legal advice for Canada’s innovation community, the Government proposes to provide $21.5 million over five years, starting in 2018–19, to Innovation, Science and Economic Development Canada. This funding will improve access for Canadian entrepreneurs to intellectual property legal clinics at universities. It will also enable the creation of a team in the federal government to work with Canadian entrepreneurs to help them develop tailored strategies for using their intellectual property and expanding into international markets.
  • To support strategic intellectual property tools that enable economic growth, Budget 2018 also proposes to provide $33.8 million over five years, starting in 2018–19, to Innovation, Science and Economic Development Canada, including $4.5 million for the creation of an intellectual property marketplace. This marketplace will be a one-stop, online listing of public sector-owned intellectual property available for licensing or sale to reduce transaction costs for businesses and researchers, and to improve Canadian entrepreneurs’ access to public sector-owned intellectual property.

The Government will also consider further measures, including through legislation, in support of the new intellectual property strategy.

Helping All Canadians Harness Intellectual Property
Intellectual property is one of our most valuable resources, and every Canadian business owner should understand how to protect and use it.

To better understand what groups of Canadians are benefiting the most from intellectual property, Budget 2018 proposes to provide Statistics Canada with $2 million over three years to conduct an intellectual property awareness and use survey. This survey will help identify how Canadians understand and use intellectual property, including groups that have traditionally been less likely to use intellectual property, such as women and Indigenous entrepreneurs. The results of the survey should help the Government better meet the needs of these groups through education and awareness initiatives.

The Canadian Intellectual Property Office will also increase the number of education and awareness initiatives that are delivered in partnership with business, intermediaries and academia to ensure Canadians better understand, integrate and take advantage of intellectual property when building their business strategies. This will include targeted initiatives to support underrepresented groups.

Finally, Budget 2018 also proposes to invest $1 million over five years to enable representatives of Canada’s Indigenous Peoples to participate in discussions at the World Intellectual Property Organization related to traditional knowledge and traditional cultural expressions, an important form of intellectual property.

It’s not wholly clear what they mean by ‘intellectual property’. The focus seems to be on  patents as they are the only intellectual property (as opposed to copyright and trademarks) singled out in the budget. As for how the ‘patent collective’ is going to meet all its objectives, this budget supplies no clarity on the matter. On the plus side, I’m glad to see that indigenous peoples’ knowledge is being acknowledged as “an important form of intellectual property” and I hope the discussions at the World Intellectual Property Organization are fruitful.

As for the patent situation in Canada (from the report released April 10, 2018),

Over the past decade, the Canadian patent flow in all technical sectors has consistently decreased. Patent flow provides a partial picture of how patents in Canada are exploited. A negative flow represents a deficit of patented inventions owned by Canadian assignees versus the number of patented inventions created by Canadian inventors. The patent flow for all Canadian patents decreased from about −0.04 in 2003 to −0.26 in 2014 (Figure 4.7). This means that there is an overall deficit of 26% of patent ownership in Canada. In other words, fewer patents were owned by Canadian institutions than were invented in Canada.

This is a significant change from 2003 when the deficit was only 4%. The drop is consistent across all technical sectors in the past 10 years, with Mechanical Engineering falling the least, and Electrical Engineering the most (Figure 4.7). At the technical field level, the patent flow dropped significantly in Digital Communication and Telecommunications. For example, the Digital Communication patent flow fell from 0.6 in 2003 to −0.2 in 2014. This fall could be partially linked to Nortel’s US$4.5 billion patent sale [emphasis mine] to the Rockstar consortium (which included Apple, BlackBerry, Ericsson, Microsoft, and Sony) (Brickley, 2011). Food Chemistry and Microstructural [?] and Nanotechnology both also showed a significant drop in patent flow. [p. 83 Print; p. 121 PDF]

Despite a fall in the number of parents for ‘Digital Communication’, we’re still doing well according to statistics elsewhere in this report. Is it possible that patents aren’t that big a deal? Of course, it’s also possible that we are enjoying the benefits of past work and will miss out on future work. (Note: A video of the April 10, 2018 report presentation by Max Blouw features him saying something like that.)

One last note, Nortel died many years ago. Disconcertingly, this report, despite more than one reference to Nortel, never mentions the company’s demise.

Boxed text

While the expert panel wasn’t tasked to answer certain types of questions, as I’ve noted earlier they managed to sneak in a few items.  One of the strategies they used was putting special inserts into text boxes including this (from the report released April 10, 2018),

Box 4.2
The FinTech Revolution

Financial services is a key industry in Canada. In 2015, the industry accounted for 4.4%

of Canadia jobs and about 7% of Canadian GDP (Burt, 2016). Toronto is the second largest financial services hub in North America and one of the most vibrant research hubs in FinTech. Since 2010, more than 100 start-up companies have been founded in Canada, attracting more than $1 billion in investment (Moffatt, 2016). In 2016 alone, venture-backed investment in Canadian financial technology companies grew by 35% to $137.7 million (Ho, 2017). The Toronto Financial Services Alliance estimates that there are approximately 40,000 ICT specialists working in financial services in Toronto alone.

AI, blockchain, [emphasis mine] and other results of ICT research provide the basis for several transformative FinTech innovations including, for example, decentralized transaction ledgers, cryptocurrencies (e.g., bitcoin), and AI-based risk assessment and fraud detection. These innovations offer opportunities to develop new markets for established financial services firms, but also provide entry points for technology firms to develop competing service offerings, increasing competition in the financial services industry. In response, many financial services companies are increasing their investments in FinTech companies (Breznitz et al., 2015). By their own account, the big five banks invest more than $1 billion annually in R&D of advanced software solutions, including AI-based innovations (J. Thompson, personal communication, 2016). The banks are also increasingly investing in university research and collaboration with start-up companies. For instance, together with several large insurance and financial management firms, all big five banks have invested in the Vector Institute for Artificial Intelligence (Kolm, 2017).

I’m glad to see the mention of blockchain while AI (artificial intelligence) is an area where we have innovated (from the report released April 10, 2018),

AI has attracted researchers and funding since the 1960s; however, there were periods of stagnation in the 1970s and 1980s, sometimes referred to as the “AI winter.” During this period, the Canadian Institute for Advanced Research (CIFAR), under the direction of Fraser Mustard, started supporting AI research with a decade-long program called Artificial Intelligence, Robotics and Society, [emphasis mine] which was active from 1983 to 1994. In 2004, a new program called Neural Computation and Adaptive Perception was initiated and renewed twice in 2008 and 2014 under the title, Learning in Machines and Brains. Through these programs, the government provided long-term, predictable support for high- risk research that propelled Canadian researchers to the forefront of global AI development. In the 1990s and early 2000s, Canadian research output and impact on AI were second only to that of the United States (CIFAR, 2016). NSERC has also been an early supporter of AI. According to its searchable grant database, NSERC has given funding to research projects on AI since at least 1991–1992 (the earliest searchable year) (NSERC, 2017a).

The University of Toronto, the University of Alberta, and the Université de Montréal have emerged as international centres for research in neural networks and deep learning, with leading experts such as Geoffrey Hinton and Yoshua Bengio. Recently, these locations have expanded into vibrant hubs for research in AI applications with a diverse mix of specialized research institutes, accelerators, and start-up companies, and growing investment by major international players in AI development, such as Microsoft, Google, and Facebook. Many highly influential AI researchers today are either from Canada or have at some point in their careers worked at a Canadian institution or with Canadian scholars.

As international opportunities in AI research and the ICT industry have grown, many of Canada’s AI pioneers have been drawn to research institutions and companies outside of Canada. According to the OECD, Canada’s share of patents in AI declined from 2.4% in 2000 to 2005 to 2% in 2010 to 2015. Although Canada is the sixth largest producer of top-cited scientific publications related to machine learning, firms headquartered in Canada accounted for only 0.9% of all AI-related inventions from 2012 to 2014 (OECD, 2017c). Canadian AI researchers, however, remain involved in the core nodes of an expanding international network of AI researchers, most of whom continue to maintain ties with their home institutions. Compared with their international peers, Canadian AI researchers are engaged in international collaborations far more often than would be expected by Canada’s level of research output, with Canada ranking fifth in collaboration. [p. 97-98 Print; p. 135-136 PDF]

The only mention of robotics seems to be here in this section and it’s only in passing. This is a bit surprising given its global importance. I wonder if robotics has been somehow hidden inside the term artificial intelligence, although sometimes it’s vice versa with robot being used to describe artificial intelligence. I’m noticing this trend of assuming the terms are synonymous or interchangeable not just in Canadian publications but elsewhere too.  ’nuff said.

Getting back to the matter at hand, t he report does note that patenting (technometric data) is problematic (from the report released April 10, 2018),

The limitations of technometric data stem largely from their restricted applicability across areas of R&D. Patenting, as a strategy for IP management, is similarly limited in not being equally relevant across industries. Trends in patenting can also reflect commercial pressures unrelated to R&D activities, such as defensive or strategic patenting practices. Finally, taxonomies for assessing patents are not aligned with bibliometric taxonomies, though links can be drawn to research publications through the analysis of patent citations. [p. 105 Print; p. 143 PDF]

It’s interesting to me that they make reference to many of the same issues that I mention but they seem to forget and don’t use that information in their conclusions.

There is one other piece of boxed text I want to highlight (from the report released April 10, 2018),

Box 6.3
Open Science: An Emerging Approach to Create New Linkages

Open Science is an umbrella term to describe collaborative and open approaches to
undertaking science, which can be powerful catalysts of innovation. This includes
the development of open collaborative networks among research performers, such
as the private sector, and the wider distribution of research that usually results when
restrictions on use are removed. Such an approach triggers faster translation of ideas
among research partners and moves the boundaries of pre-competitive research to
later, applied stages of research. With research results freely accessible, companies
can focus on developing new products and processes that can be commercialized.

Two Canadian organizations exemplify the development of such models. In June
2017, Genome Canada, the Ontario government, and pharmaceutical companies
invested $33 million in the Structural Genomics Consortium (SGC) (Genome Canada,
2017). Formed in 2004, the SGC is at the forefront of the Canadian open science
movement and has contributed to many key research advancements towards new
treatments (SGC, 2018). McGill University’s Montréal Neurological Institute and
Hospital has also embraced the principles of open science. Since 2016, it has been
sharing its research results with the scientific community without restriction, with
the objective of expanding “the impact of brain research and accelerat[ing] the
discovery of ground-breaking therapies to treat patients suffering from a wide range
of devastating neurological diseases” (neuro, n.d.).

This is exciting stuff and I’m happy the panel featured it. (I wrote about the Montréal Neurological Institute initiative in a Jan. 22, 2016 posting.)

More than once, the report notes the difficulties with using bibliometric and technometric data as measures of scientific achievement and progress and open science (along with its cousins, open data and open access) are contributing to the difficulties as James Somers notes in his April 5, 2018 article ‘The Scientific Paper is Obsolete’ for The Atlantic (Note: Links have been removed),

The scientific paper—the actual form of it—was one of the enabling inventions of modernity. Before it was developed in the 1600s, results were communicated privately in letters, ephemerally in lectures, or all at once in books. There was no public forum for incremental advances. By making room for reports of single experiments or minor technical advances, journals made the chaos of science accretive. Scientists from that point forward became like the social insects: They made their progress steadily, as a buzzing mass.

The earliest papers were in some ways more readable than papers are today. They were less specialized, more direct, shorter, and far less formal. Calculus had only just been invented. Entire data sets could fit in a table on a single page. What little “computation” contributed to the results was done by hand and could be verified in the same way.

The more sophisticated science becomes, the harder it is to communicate results. Papers today are longer than ever and full of jargon and symbols. They depend on chains of computer programs that generate data, and clean up data, and plot data, and run statistical models on data. These programs tend to be both so sloppily written and so central to the results that it’s [sic] contributed to a replication crisis, or put another way, a failure of the paper to perform its most basic task: to report what you’ve actually discovered, clearly enough that someone else can discover it for themselves.

Perhaps the paper itself is to blame. Scientific methods evolve now at the speed of software; the skill most in demand among physicists, biologists, chemists, geologists, even anthropologists and research psychologists, is facility with programming languages and “data science” packages. And yet the basic means of communicating scientific results hasn’t changed for 400 years. Papers may be posted online, but they’re still text and pictures on a page.

What would you get if you designed the scientific paper from scratch today? A little while ago I spoke to Bret Victor, a researcher who worked at Apple on early user-interface prototypes for the iPad and now runs his own lab in Oakland, California, that studies the future of computing. Victor has long been convinced that scientists haven’t yet taken full advantage of the computer. “It’s not that different than looking at the printing press, and the evolution of the book,” he said. After Gutenberg, the printing press was mostly used to mimic the calligraphy in bibles. It took nearly 100 years of technical and conceptual improvements to invent the modern book. “There was this entire period where they had the new technology of printing, but they were just using it to emulate the old media.”Victor gestured at what might be possible when he redesigned a journal article by Duncan Watts and Steven Strogatz, “Collective dynamics of ‘small-world’ networks.” He chose it both because it’s one of the most highly cited papers in all of science and because it’s a model of clear exposition. (Strogatz is best known for writing the beloved “Elements of Math” column for The New York Times.)

The Watts-Strogatz paper described its key findings the way most papers do, with text, pictures, and mathematical symbols. And like most papers, these findings were still hard to swallow, despite the lucid prose. The hardest parts were the ones that described procedures or algorithms, because these required the reader to “play computer” in their head, as Victor put it, that is, to strain to maintain a fragile mental picture of what was happening with each step of the algorithm.Victor’s redesign interleaved the explanatory text with little interactive diagrams that illustrated each step. In his version, you could see the algorithm at work on an example. You could even control it yourself….

For anyone interested in the evolution of how science is conducted and communicated, Somers’ article is a fascinating and in depth look at future possibilities.

Subregional R&D

I didn’t find this quite as compelling as the last time and that may be due to the fact that there’s less information and I think the 2012 report was the first to examine the Canadian R&D scene with a subregional (in their case, provinces) lens. On a high note, this report also covers cities (!) and regions, as well as, provinces.

Here’s the conclusion (from the report released April 10, 2018),

Ontario leads Canada in R&D investment and performance. The province accounts for almost half of R&D investment and personnel, research publications and collaborations, and patents. R&D activity in Ontario produces high-quality publications in each of Canada’s five R&D strengths, reflecting both the quantity and quality of universities in the province. Quebec lags Ontario in total investment, publications, and patents, but performs as well (citations) or better (R&D intensity) by some measures. Much like Ontario, Quebec researchers produce impactful publications across most of Canada’s five R&D strengths. Although it invests an amount similar to that of Alberta, British Columbia does so at a significantly higher intensity. British Columbia also produces more highly cited publications and patents, and is involved in more international research collaborations. R&D in British Columbia and Alberta clusters around Vancouver and Calgary in areas such as physics and ICT and in clinical medicine and energy, respectively. [emphasis mine] Smaller but vibrant R&D communities exist in the Prairies and Atlantic Canada [also referred to as the Maritime provinces or Maritimes] (and, to a lesser extent, in the Territories) in natural resource industries.

Globally, as urban populations expand exponentially, cities are likely to drive innovation and wealth creation at an increasing rate in the future. In Canada, R&D activity clusters around five large cities: Toronto, Montréal, Vancouver, Ottawa, and Calgary. These five cities create patents and high-tech companies at nearly twice the rate of other Canadian cities. They also account for half of clusters in the services sector, and many in advanced manufacturing.

Many clusters relate to natural resources and long-standing areas of economic and research strength. Natural resource clusters have emerged around the location of resources, such as forestry in British Columbia, oil and gas in Alberta, agriculture in Ontario, mining in Quebec, and maritime resources in Atlantic Canada. The automotive, plastics, and steel industries have the most individual clusters as a result of their economic success in Windsor, Hamilton, and Oshawa. Advanced manufacturing industries tend to be more concentrated, often located near specialized research universities. Strong connections between academia and industry are often associated with these clusters. R&D activity is distributed across the country, varying both between and within regions. It is critical to avoid drawing the wrong conclusion from this fact. This distribution does not imply the existence of a problem that needs to be remedied. Rather, it signals the benefits of diverse innovation systems, with differentiation driven by the needs of and resources available in each province. [pp.  132-133 Print; pp. 170-171 PDF]

Intriguingly, there’s no mention that in British Columbia (BC), there are leading areas of research: Visual & Performing Arts, Psychology & Cognitive Sciences, and Clinical Medicine (according to the table on p. 117 Print, p. 153 PDF).

As I said and hinted earlier, we’ve got brains; they’re just not the kind of brains that command respect.

Final comments

My hat’s off to the expert panel and staff of the Council of Canadian Academies. Combining two previous reports into one could not have been easy. As well, kudos to their attempts to broaden the discussion by mentioning initiative such as open science and for emphasizing the problems with bibliometrics, technometrics, and other measures. I have covered only parts of this assessment, (Competing in a Global Innovation Economy: The Current State of R&D in Canada), there’s a lot more to it including a substantive list of reference materials (bibliography).

While I have argued that perhaps the situation isn’t quite as bad as the headlines and statistics may suggest, there are some concerning trends for Canadians but we have to acknowledge that many countries have stepped up their research game and that’s good for all of us. You don’t get better at anything unless you work with and play with others who are better than you are. For example, both India and Italy surpassed us in numbers of published research papers. We slipped from 7th place to 9th. Thank you, Italy and India. (And, Happy ‘Italian Research in the World Day’ on April 15, 2018, the day’s inaugural year. In Italian: Piano Straordinario “Vivere all’Italiana” – Giornata della ricerca Italiana nel mondo.)

Unfortunately, the reading is harder going than previous R&D assessments in the CCA catalogue. And in the end, I can’t help thinking we’re just a little bit like Hedy Lamarr. Not really appreciated in all of our complexities although the expert panel and staff did try from time to time. Perhaps the government needs to find better ways of asking the questions.

***ETA April 12, 2018 at 1500 PDT: Talking about missing the obvious! I’ve been ranting on about how research strength in visual and performing arts and in philosophy and theology, etc. is perfectly fine and could lead to ‘traditional’ science breakthroughs without underlining the point by noting that Antheil was a musician, Lamarr was as an actress and they set the foundation for work by electrical engineers (or people with that specialty) for their signature work leading to WiFi, etc.***

There is, by the way, a Hedy-Canada connection. In 1998, she sued Canadian software company Corel, for its unauthorized use of her image on their Corel Draw 8 product packaging. She won.

More stuff

For those who’d like to see and hear the April 10, 2017 launch for “Competing in a Global Innovation Economy: The Current State of R&D in Canada” or the Third Assessment as I think of it, go here.

The report can be found here.

For anyone curious about ‘Bombshell: The Hedy Lamarr Story’ to be broadcast on May 18, 2018 as part of PBS’s American Masters series, there’s this trailer,

For the curious, I did find out more about the Hedy Lamarr and Corel Draw. John Lettice’s December 2, 1998 article The Rgister describes the suit and her subsequent victory in less than admiring terms,

Our picture doesn’t show glamorous actress Hedy Lamarr, who yesterday [Dec. 1, 1998] came to a settlement with Corel over the use of her image on Corel’s packaging. But we suppose that following the settlement we could have used a picture of Corel’s packaging. Lamarr sued Corel earlier this year over its use of a CorelDraw image of her. The picture had been produced by John Corkery, who was 1996 Best of Show winner of the Corel World Design Contest. Corel now seems to have come to an undisclosed settlement with her, which includes a five-year exclusive (oops — maybe we can’t use the pack-shot then) licence to use “the lifelike vector illustration of Hedy Lamarr on Corel’s graphic software packaging”. Lamarr, bless ‘er, says she’s looking forward to the continued success of Corel Corporation,  …

There’s this excerpt from a Sept. 21, 2015 posting (a pictorial essay of Lamarr’s life) by Shahebaz Khan on The Blaze Blog,

6. CorelDRAW:
For several years beginning in 1997, the boxes of Corel DRAW’s software suites were graced by a large Corel-drawn image of Lamarr. The picture won Corel DRAW’s yearly software suite cover design contest in 1996. Lamarr sued Corel for using the image without her permission. Corel countered that she did not own rights to the image. The parties reached an undisclosed settlement in 1998.

There’s also a Nov. 23, 1998 Corel Draw 8 product review by Mike Gorman on mymac.com, which includes a screenshot of the packaging that precipitated the lawsuit. Once they settled, it seems Corel used her image at least one more time.

The Hedy Lamarr of international research: Canada’s Third assessment of The State of Science and Technology and Industrial Research and Development in Canada (1 of 2)

Before launching into the assessment, a brief explanation of my theme: Hedy Lamarr was considered to be one of the great beauties of her day,

“Ziegfeld Girl” Hedy Lamarr 1941 MGM *M.V.
Titles: Ziegfeld Girl
People: Hedy Lamarr
Image courtesy mptvimages.com [downloaded from https://www.imdb.com/title/tt0034415/mediaviewer/rm1566611456]

Aside from starring in Hollywood movies and, before that, movies in Europe, she was also an inventor and not just any inventor (from a Dec. 4, 2017 article by Laura Barnett for The Guardian), Note: Links have been removed,

Let’s take a moment to reflect on the mercurial brilliance of Hedy Lamarr. Not only did the Vienna-born actor flee a loveless marriage to a Nazi arms dealer to secure a seven-year, $3,000-a-week contract with MGM, and become (probably) the first Hollywood star to simulate a female orgasm on screen – she also took time out to invent a device that would eventually revolutionise mobile communications.

As described in unprecedented detail by the American journalist and historian Richard Rhodes in his new book, Hedy’s Folly, Lamarr and her business partner, the composer George Antheil, were awarded a patent in 1942 for a “secret communication system”. It was meant for radio-guided torpedoes, and the pair gave to the US Navy. It languished in their files for decades before eventually becoming a constituent part of GPS, Wi-Fi and Bluetooth technology.

(The article goes on to mention other celebrities [Marlon Brando, Barbara Cartland, Mark Twain, etc] and their inventions.)

Lamarr’s work as an inventor was largely overlooked until the 1990’s when the technology community turned her into a ‘cultish’ favourite and from there her reputation grew and acknowledgement increased culminating in Rhodes’ book and the documentary by Alexandra Dean, ‘Bombshell: The Hedy Lamarr Story (to be broadcast as part of PBS’s American Masters series on May 18, 2018).

Canada as Hedy Lamarr

There are some parallels to be drawn between Canada’s S&T and R&D (science and technology; research and development) and Ms. Lamarr. Chief amongst them, we’re not always appreciated for our brains. Not even by people who are supposed to know better such as the experts on the panel for the ‘Third assessment of The State of Science and Technology and Industrial Research and Development in Canada’ (proper title: Competing in a Global Innovation Economy: The Current State of R&D in Canada) from the Expert Panel on the State of Science and Technology and Industrial Research and Development in Canada.

A little history

Before exploring the comparison to Hedy Lamarr further, here’s a bit more about the history of this latest assessment from the Council of Canadian Academies (CCA), from the report released April 10, 2018,

This assessment of Canada’s performance indicators in science, technology, research, and innovation comes at an opportune time. The Government of Canada has expressed a renewed commitment in several tangible ways to this broad domain of activity including its Innovation and Skills Plan, the announcement of five superclusters, its appointment of a new Chief Science Advisor, and its request for the Fundamental Science Review. More specifically, the 2018 Federal Budget demonstrated the government’s strong commitment to research and innovation with historic investments in science.

The CCA has a decade-long history of conducting evidence-based assessments about Canada’s research and development activities, producing seven assessments of relevance:

The State of Science and Technology in Canada (2006) [emphasis mine]
•Innovation and Business Strategy: Why Canada Falls Short (2009)
•Catalyzing Canada’s Digital Economy (2010)
•Informing Research Choices: Indicators and Judgment (2012)
The State of Science and Technology in Canada (2012) [emphasis mine]
The State of Industrial R&D in Canada (2013) [emphasis mine]
•Paradox Lost: Explaining Canada’s Research Strength and Innovation Weakness (2013)

Using similar methods and metrics to those in The State of Science and Technology in Canada (2012) and The State of Industrial R&D in Canada (2013), this assessment tells a similar and familiar story: Canada has much to be proud of, with world-class researchers in many domains of knowledge, but the rest of the world is not standing still. Our peers are also producing high quality results, and many countries are making significant commitments to supporting research and development that will position them to better leverage their strengths to compete globally. Canada will need to take notice as it determines how best to take action. This assessment provides valuable material for that conversation to occur, whether it takes place in the lab or the legislature, the bench or the boardroom. We also hope it will be used to inform public discussion. [p. ix Print, p. 11 PDF]

This latest assessment succeeds the general 2006 and 2012 reports, which were mostly focused on academic research, and combines it with an assessment of industrial research, which was previously separate. Also, this third assessment’s title (Competing in a Global Innovation Economy: The Current State of R&D in Canada) makes what was previously quietly declared in the text, explicit from the cover onwards. It’s all about competition, despite noises such as the 2017 Naylor report (Review of fundamental research) about the importance of fundamental research.

One other quick comment, I did wonder in my July 1, 2016 posting (featuring the announcement of the third assessment) how combining two assessments would impact the size of the expert panel and the size of the final report,

Given the size of the 2012 assessment of science and technology at 232 pp. (PDF) and the 2013 assessment of industrial research and development at 220 pp. (PDF) with two expert panels, the imagination boggles at the potential size of the 2016 expert panel and of the 2016 assessment combining the two areas.

I got my answer with regard to the panel as noted in my Oct. 20, 2016 update (which featured a list of the members),

A few observations, given the size of the task, this panel is lean. As well, there are three women in a group of 13 (less than 25% representation) in 2016? It’s Ontario and Québec-dominant; only BC and Alberta rate a representative on the panel. I hope they will find ways to better balance this panel and communicate that ‘balanced story’ to the rest of us. On the plus side, the panel has representatives from the humanities, arts, and industry in addition to the expected representatives from the sciences.

The imbalance I noted then was addressed, somewhat, with the selection of the reviewers (from the report released April 10, 2018),

The CCA wishes to thank the following individuals for their review of this report:

Ronald Burnett, C.M., O.B.C., RCA, Chevalier de l’ordre des arts et des
lettres, President and Vice-Chancellor, Emily Carr University of Art and Design
(Vancouver, BC)

Michelle N. Chretien, Director, Centre for Advanced Manufacturing and Design
Technologies, Sheridan College; Former Program and Business Development
Manager, Electronic Materials, Xerox Research Centre of Canada (Brampton,
ON)

Lisa Crossley, CEO, Reliq Health Technologies, Inc. (Ancaster, ON)
Natalie Dakers, Founding President and CEO, Accel-Rx Health Sciences
Accelerator (Vancouver, BC)

Fred Gault, Professorial Fellow, United Nations University-MERIT (Maastricht,
Netherlands)

Patrick D. Germain, Principal Engineering Specialist, Advanced Aerodynamics,
Bombardier Aerospace (Montréal, QC)

Robert Brian Haynes, O.C., FRSC, FCAHS, Professor Emeritus, DeGroote
School of Medicine, McMaster University (Hamilton, ON)

Susan Holt, Chief, Innovation and Business Relationships, Government of
New Brunswick (Fredericton, NB)

Pierre A. Mohnen, Professor, United Nations University-MERIT and Maastricht
University (Maastricht, Netherlands)

Peter J. M. Nicholson, C.M., Retired; Former and Founding President and
CEO, Council of Canadian Academies (Annapolis Royal, NS)

Raymond G. Siemens, Distinguished Professor, English and Computer Science
and Former Canada Research Chair in Humanities Computing, University of
Victoria (Victoria, BC) [pp. xii- xiv Print; pp. 15-16 PDF]

The proportion of women to men as reviewers jumped up to about 36% (4 of 11 reviewers) and there are two reviewers from the Maritime provinces. As usual, reviewers external to Canada were from Europe. Although this time, they came from Dutch institutions rather than UK or German institutions. Interestingly and unusually, there was no one from a US institution. When will they start using reviewers from other parts of the world?

As for the report itself, it is 244 pp. (PDF). (For the really curious, I have a  December 15, 2016 post featuring my comments on the preliminary data for the third assessment.)

To sum up, they had a lean expert panel tasked with bringing together two inquiries and two reports. I imagine that was daunting. Good on them for finding a way to make it manageable.

Bibliometrics, patents, and a survey

I wish more attention had been paid to some of the issues around open science, open access, and open data, which are changing how science is being conducted. (I have more about this from an April 5, 2018 article by James Somers for The Atlantic but more about that later.) If I understand rightly, they may not have been possible due to the nature of the questions posed by the government when requested the assessment.

As was done for the second assessment, there is an acknowledgement that the standard measures/metrics (bibliometrics [no. of papers published, which journals published them; number of times papers were cited] and technometrics [no. of patent applications, etc.] of scientific accomplishment and progress are not the best and new approaches need to be developed and adopted (from the report released April 10, 2018),

It is also worth noting that the Panel itself recognized the limits that come from using traditional historic metrics. Additional approaches will be needed the next time this assessment is done. [p. ix Print; p. 11 PDF]

For the second assessment and as a means of addressing some of the problems with metrics, the panel decided to take a survey which the panel for the third assessment has also done (from the report released April 10, 2018),

The Panel relied on evidence from multiple sources to address its charge, including a literature review and data extracted from statistical agencies and organizations such as Statistics Canada and the OECD. For international comparisons, the Panel focused on OECD countries along with developing countries that are among the top 20 producers of peer-reviewed research publications (e.g., China, India, Brazil, Iran, Turkey). In addition to the literature review, two primary research approaches informed the Panel’s assessment:
•a comprehensive bibliometric and technometric analysis of Canadian research publications and patents; and,
•a survey of top-cited researchers around the world.

Despite best efforts to collect and analyze up-to-date information, one of the Panel’s findings is that data limitations continue to constrain the assessment of R&D activity and excellence in Canada. This is particularly the case with industrial R&D and in the social sciences, arts, and humanities. Data on industrial R&D activity continue to suffer from time lags for some measures, such as internationally comparable data on R&D intensity by sector and industry. These data also rely on industrial categories (i.e., NAICS and ISIC codes) that can obscure important trends, particularly in the services sector, though Statistics Canada’s recent revisions to how this data is reported have improved this situation. There is also a lack of internationally comparable metrics relating to R&D outcomes and impacts, aside from those based on patents.

For the social sciences, arts, and humanities, metrics based on journal articles and other indexed publications provide an incomplete and uneven picture of research contributions. The expansion of bibliometric databases and methodological improvements such as greater use of web-based metrics, including paper views/downloads and social media references, will support ongoing, incremental improvements in the availability and accuracy of data. However, future assessments of R&D in Canada may benefit from more substantive integration of expert review, capable of factoring in different types of research outputs (e.g., non-indexed books) and impacts (e.g., contributions to communities or impacts on public policy). The Panel has no doubt that contributions from the humanities, arts, and social sciences are of equal importance to national prosperity. It is vital that such contributions are better measured and assessed. [p. xvii Print; p. 19 PDF]

My reading: there’s a problem and we’re not going to try and fix it this time. Good luck to those who come after us. As for this line: “The Panel has no doubt that contributions from the humanities, arts, and social sciences are of equal importance to national prosperity.” Did no one explain that when you use ‘no doubt’, you are introducing doubt? It’s a cousin to ‘don’t take this the wrong way’ and ‘I don’t mean to be rude but …’ .

Good news

This is somewhat encouraging (from the report released April 10, 2018),

Canada’s international reputation for its capacity to participate in cutting-edge R&D is strong, with 60% of top-cited researchers surveyed internationally indicating that Canada hosts world-leading infrastructure or programs in their fields. This share increased by four percentage points between 2012 and 2017. Canada continues to benefit from a highly educated population and deep pools of research skills and talent. Its population has the highest level of educational attainment in the OECD in the proportion of the population with
a post-secondary education. However, among younger cohorts (aged 25 to 34), Canada has fallen behind Japan and South Korea. The number of researchers per capita in Canada is on a par with that of other developed countries, andincreased modestly between 2004 and 2012. Canada’s output of PhD graduates has also grown in recent years, though it remains low in per capita terms relative to many OECD countries. [pp. xvii-xviii; pp. 19-20]

Don’t let your head get too big

Most of the report observes that our international standing is slipping in various ways such as this (from the report released April 10, 2018),

In contrast, the number of R&D personnel employed in Canadian businesses
dropped by 20% between 2008 and 2013. This is likely related to sustained and
ongoing decline in business R&D investment across the country. R&D as a share
of gross domestic product (GDP) has steadily declined in Canada since 2001,
and now stands well below the OECD average (Figure 1). As one of few OECD
countries with virtually no growth in total national R&D expenditures between
2006 and 2015, Canada would now need to more than double expenditures to
achieve an R&D intensity comparable to that of leading countries.

Low and declining business R&D expenditures are the dominant driver of this
trend; however, R&D spending in all sectors is implicated. Government R&D
expenditures declined, in real terms, over the same period. Expenditures in the
higher education sector (an indicator on which Canada has traditionally ranked
highly) are also increasing more slowly than the OECD average. Significant
erosion of Canada’s international competitiveness and capacity to participate
in R&D and innovation is likely to occur if this decline and underinvestment
continue.

Between 2009 and 2014, Canada produced 3.8% of the world’s research
publications, ranking ninth in the world. This is down from seventh place for
the 2003–2008 period. India and Italy have overtaken Canada although the
difference between Italy and Canada is small. Publication output in Canada grew
by 26% between 2003 and 2014, a growth rate greater than many developed
countries (including United States, France, Germany, United Kingdom, and
Japan), but below the world average, which reflects the rapid growth in China
and other emerging economies. Research output from the federal government,
particularly the National Research Council Canada, dropped significantly
between 2009 and 2014.(emphasis mine)  [p. xviii Print; p. 20 PDF]

For anyone unfamiliar with Canadian politics,  2009 – 2014 were years during which Stephen Harper’s Conservatives formed the government. Justin Trudeau’s Liberals were elected to form the government in late 2015.

During Harper’s years in government, the Conservatives were very interested in changing how the National Research Council of Canada operated and, if memory serves, the focus was on innovation over research. Consequently, the drop in their research output is predictable.

Given my interest in nanotechnology and other emerging technologies, this popped out (from the report released April 10, 2018),

When it comes to research on most enabling and strategic technologies, however, Canada lags other countries. Bibliometric evidence suggests that, with the exception of selected subfields in Information and Communication Technologies (ICT) such as Medical Informatics and Personalized Medicine, Canada accounts for a relatively small share of the world’s research output for promising areas of technology development. This is particularly true for Biotechnology, Nanotechnology, and Materials science [emphasis mine]. Canada’s research impact, as reflected by citations, is also modest in these areas. Aside from Biotechnology, none of the other subfields in Enabling and Strategic Technologies has an ARC rank among the top five countries. Optoelectronics and photonics is the next highest ranked at 7th place, followed by Materials, and Nanoscience and Nanotechnology, both of which have a rank of 9th. Even in areas where Canadian researchers and institutions played a seminal role in early research (and retain a substantial research capacity), such as Artificial Intelligence and Regenerative Medicine, Canada has lost ground to other countries.

Arguably, our early efforts in artificial intelligence wouldn’t have garnered us much in the way of ranking and yet we managed some cutting edge work such as machine learning. I’m not suggesting the expert panel should have or could have found some way to measure these kinds of efforts but I’m wondering if there could have been some acknowledgement in the text of the report. I’m thinking a couple of sentences in a paragraph about the confounding nature of scientific research where areas that are ignored for years and even decades then become important (e.g., machine learning) but are not measured as part of scientific progress until after they are universally recognized.

Still, point taken about our diminishing returns in ’emerging’ technologies and sciences (from the report released April 10, 2018),

The impression that emerges from these data is sobering. With the exception of selected ICT subfields, such as Medical Informatics, bibliometric evidence does not suggest that Canada excels internationally in most of these research areas. In areas such as Nanotechnology and Materials science, Canada lags behind other countries in levels of research output and impact, and other countries are outpacing Canada’s publication growth in these areas — leading to declining shares of world publications. Even in research areas such as AI, where Canadian researchers and institutions played a foundational role, Canadian R&D activity is not keeping pace with that of other countries and some researchers trained in Canada have relocated to other countries (Section 4.4.1). There are isolated exceptions to these trends, but the aggregate data reviewed by this Panel suggest that Canada is not currently a world leader in research on most emerging technologies.

The Hedy Lamarr treatment

We have ‘good looks’ (arts and humanities) but not the kind of brains (physical sciences and engineering) that people admire (from the report released April 10, 2018),

Canada, relative to the world, specializes in subjects generally referred to as the
humanities and social sciences (plus health and the environment), and does
not specialize as much as others in areas traditionally referred to as the physical
sciences and engineering. Specifically, Canada has comparatively high levels
of research output in Psychology and Cognitive Sciences, Public Health and
Health Services, Philosophy and Theology, Earth and Environmental Sciences,
and Visual and Performing Arts. [emphases mine] It accounts for more than 5% of world researchin these fields. Conversely, Canada has lower research output than expected
in Chemistry, Physics and Astronomy, Enabling and Strategic Technologies,
Engineering, and Mathematics and Statistics. The comparatively low research
output in core areas of the natural sciences and engineering is concerning,
and could impair the flexibility of Canada’s research base, preventing research
institutions and researchers from being able to pivot to tomorrow’s emerging
research areas. [p. xix Print; p. 21 PDF]

Couldn’t they have used a more buoyant tone? After all, science was known as ‘natural philosophy’ up until the 19th century. As for visual and performing arts, let’s include poetry as a performing and literary art (both have been the case historically and cross-culturally) and let’s also note that one of the great physics texts, (De rerum natura by Lucretius) was a multi-volume poem (from Lucretius’ Wikipedia entry; Note: Links have been removed).

His poem De rerum natura (usually translated as “On the Nature of Things” or “On the Nature of the Universe”) transmits the ideas of Epicureanism, which includes Atomism [the concept of atoms forming materials] and psychology. Lucretius was the first writer to introduce Roman readers to Epicurean philosophy.[15] The poem, written in some 7,400 dactylic hexameters, is divided into six untitled books, and explores Epicurean physics through richly poetic language and metaphors. Lucretius presents the principles of atomism; the nature of the mind and soul; explanations of sensation and thought; the development of the world and its phenomena; and explains a variety of celestial and terrestrial phenomena. The universe described in the poem operates according to these physical principles, guided by fortuna, “chance”, and not the divine intervention of the traditional Roman deities.[16]

Should you need more proof that the arts might have something to contribute to physical sciences, there’s this in my March 7, 2018 posting,

It’s not often you see research that combines biologically inspired engineering and a molecular biophysicist with a professional animator who worked at Peter Jackson’s (Lord of the Rings film trilogy, etc.) Park Road Post film studio. An Oct. 18, 2017 news item on ScienceDaily describes the project,

Like many other scientists, Don Ingber, M.D., Ph.D., the Founding Director of the Wyss Institute, [emphasis mine] is concerned that non-scientists have become skeptical and even fearful of his field at a time when technology can offer solutions to many of the world’s greatest problems. “I feel that there’s a huge disconnect between science and the public because it’s depicted as rote memorization in schools, when by definition, if you can memorize it, it’s not science,” says Ingber, who is also the Judah Folkman Professor of Vascular Biology at Harvard Medical School and the Vascular Biology Program at Boston Children’s Hospital, and Professor of Bioengineering at the Harvard Paulson School of Engineering and Applied Sciences (SEAS). [emphasis mine] “Science is the pursuit of the unknown. We have a responsibility to reach out to the public and convey that excitement of exploration and discovery, and fortunately, the film industry is already great at doing that.”

“Not only is our physics-based simulation and animation system as good as other data-based modeling systems, it led to the new scientific insight [emphasis mine] that the limited motion of the dynein hinge focuses the energy released by ATP hydrolysis, which causes dynein’s shape change and drives microtubule sliding and axoneme motion,” says Ingber. “Additionally, while previous studies of dynein have revealed the molecule’s two different static conformations, our animation visually depicts one plausible way that the protein can transition between those shapes at atomic resolution, which is something that other simulations can’t do. The animation approach also allows us to visualize how rows of dyneins work in unison, like rowers pulling together in a boat, which is difficult using conventional scientific simulation approaches.”

It comes down to how we look at things. Yes, physical sciences and engineering are very important. If the report is to be believed we have a very highly educated population and according to PISA scores our students rank highly in mathematics, science, and reading skills. (For more information on Canada’s latest PISA scores from 2015 see this OECD page. As for PISA itself, it’s an OECD [Organization for Economic Cooperation and Development] programme where 15-year-old students from around the world are tested on their reading, mathematics, and science skills, you can get some information from my Oct. 9, 2013 posting.)

Is it really so bad that we choose to apply those skills in fields other than the physical sciences and engineering? It’s a little bit like Hedy Lamarr’s problem except instead of being judged for our looks and having our inventions dismissed, we’re being judged for not applying ourselves to physical sciences and engineering and having our work in other closely aligned fields dismissed as less important.

Canada’s Industrial R&D: an oft-told, very sad story

Bemoaning the state of Canada’s industrial research and development efforts has been a national pastime as long as I can remember. Here’s this from the report released April 10, 2018,

There has been a sustained erosion in Canada’s industrial R&D capacity and competitiveness. Canada ranks 33rd among leading countries on an index assessing the magnitude, intensity, and growth of industrial R&D expenditures. Although Canada is the 11th largest spender, its industrial R&D intensity (0.9%) is only half the OECD average and total spending is declining (−0.7%). Compared with G7 countries, the Canadian portfolio of R&D investment is more concentrated in industries that are intrinsically not as R&D intensive. Canada invests more heavily than the G7 average in oil and gas, forestry, machinery and equipment, and finance where R&D has been less central to business strategy than in many other industries. …  About 50% of Canada’s industrial R&D spending is in high-tech sectors (including industries such as ICT, aerospace, pharmaceuticals, and automotive) compared with the G7 average of 80%. Canadian Business Enterprise Expenditures on R&D (BERD) intensity is also below the OECD average in these sectors. In contrast, Canadian investment in low and medium-low tech sectors is substantially higher than the G7 average. Canada’s spending reflects both its long-standing industrial structure and patterns of economic activity.

R&D investment patterns in Canada appear to be evolving in response to global and domestic shifts. While small and medium-sized enterprises continue to perform a greater share of industrial R&D in Canada than in the United States, between 2009 and 2013, there was a shift in R&D from smaller to larger firms. Canada is an increasingly attractive place to conduct R&D. Investment by foreign-controlled firms in Canada has increased to more than 35% of total R&D investment, with the United States accounting for more than half of that. [emphasis mine]  Multinational enterprises seem to be increasingly locating some of their R&D operations outside their country of ownership, possibly to gain proximity to superior talent. Increasing foreign-controlled R&D, however, also could signal a long-term strategic loss of control over intellectual property (IP) developed in this country, ultimately undermining the government’s efforts to support high-growth firms as they scale up. [pp. xxii-xxiii Print; pp. 24-25 PDF]

Canada has been known as a ‘branch plant’ economy for decades. For anyone unfamiliar with the term, it means that companies from other countries come here, open up a branch and that’s how we get our jobs as we don’t have all that many large companies here. Increasingly, multinationals are locating R&D shops here.

While our small to medium size companies fund industrial R&D, it’s large companies (multinationals) which can afford long-term and serious investment in R&D. Luckily for companies from other countries, we have a well-educated population of people looking for jobs.

In 2017, we opened the door more widely so we can scoop up talented researchers and scientists from other countries, from a June 14, 2017 article by Beckie Smith for The PIE News,

Universities have welcomed the inclusion of the work permit exemption for academic stays of up to 120 days in the strategy, which also introduces expedited visa processing for some highly skilled professions.

Foreign researchers working on projects at a publicly funded degree-granting institution or affiliated research institution will be eligible for one 120-day stay in Canada every 12 months.

And universities will also be able to access a dedicated service channel that will support employers and provide guidance on visa applications for foreign talent.

The Global Skills Strategy, which came into force on June 12 [2017], aims to boost the Canadian economy by filling skills gaps with international talent.

As well as the short term work permit exemption, the Global Skills Strategy aims to make it easier for employers to recruit highly skilled workers in certain fields such as computer engineering.

“Employers that are making plans for job-creating investments in Canada will often need an experienced leader, dynamic researcher or an innovator with unique skills not readily available in Canada to make that investment happen,” said Ahmed Hussen, Minister of Immigration, Refugees and Citizenship.

“The Global Skills Strategy aims to give those employers confidence that when they need to hire from abroad, they’ll have faster, more reliable access to top talent.”

Coincidentally, Microsoft, Facebook, Google, etc. have announced, in 2017, new jobs and new offices in Canadian cities. There’s a also Chinese multinational telecom company Huawei Canada which has enjoyed success in Canada and continues to invest here (from a Jan. 19, 2018 article about security concerns by Matthew Braga for the Canadian Broadcasting Corporation (CBC) online news,

For the past decade, Chinese tech company Huawei has found no shortage of success in Canada. Its equipment is used in telecommunications infrastructure run by the country’s major carriers, and some have sold Huawei’s phones.

The company has struck up partnerships with Canadian universities, and say it is investing more than half a billion dollars in researching next generation cellular networks here. [emphasis mine]

While I’m not thrilled about using patents as an indicator of progress, this is interesting to note (from the report released April 10, 2018),

Canada produces about 1% of global patents, ranking 18th in the world. It lags further behind in trademark (34th) and design applications (34th). Despite relatively weak performance overall in patents, Canada excels in some technical fields such as Civil Engineering, Digital Communication, Other Special Machines, Computer Technology, and Telecommunications. [emphases mine] Canada is a net exporter of patents, which signals the R&D strength of some technology industries. It may also reflect increasing R&D investment by foreign-controlled firms. [emphasis mine] [p. xxiii Print; p. 25 PDF]

Getting back to my point, we don’t have large companies here. In fact, the dream for most of our high tech startups is to build up the company so it’s attractive to buyers, sell, and retire (hopefully before the age of 40). Strangely, the expert panel doesn’t seem to share my insight into this matter,

Canada’s combination of high performance in measures of research output and impact, and low performance on measures of industrial R&D investment and innovation (e.g., subpar productivity growth), continue to be viewed as a paradox, leading to the hypothesis that barriers are impeding the flow of Canada’s research achievements into commercial applications. The Panel’s analysis suggests the need for a more nuanced view. The process of transforming research into innovation and wealth creation is a complex multifaceted process, making it difficult to point to any definitive cause of Canada’s deficit in R&D investment and productivity growth. Based on the Panel’s interpretation of the evidence, Canada is a highly innovative nation, but significant barriers prevent the translation of innovation into wealth creation. The available evidence does point to a number of important contributing factors that are analyzed in this report. Figure 5 represents the relationships between R&D, innovation, and wealth creation.

The Panel concluded that many factors commonly identified as points of concern do not adequately explain the overall weakness in Canada’s innovation performance compared with other countries. [emphasis mine] Academia-business linkages appear relatively robust in quantitative terms given the extent of cross-sectoral R&D funding and increasing academia-industry partnerships, though the volume of academia-industry interactions does not indicate the nature or the quality of that interaction, nor the extent to which firms are capitalizing on the research conducted and the resulting IP. The educational system is high performing by international standards and there does not appear to be a widespread lack of researchers or STEM (science, technology, engineering, and mathematics) skills. IP policies differ across universities and are unlikely to explain a divergence in research commercialization activity between Canadian and U.S. institutions, though Canadian universities and governments could do more to help Canadian firms access university IP and compete in IP management and strategy. Venture capital availability in Canada has improved dramatically in recent years and is now competitive internationally, though still overshadowed by Silicon Valley. Technology start-ups and start-up ecosystems are also flourishing in many sectors and regions, demonstrating their ability to build on research advances to develop and deliver innovative products and services.

You’ll note there’s no mention of a cultural issue where start-ups are designed for sale as soon as possible and this isn’t new. Years ago, there was an accounting firm that published a series of historical maps (the last one I saw was in 2005) of technology companies in the Vancouver region. Technology companies were being developed and sold to large foreign companies from the 19th century to present day.

Part 2

How to get people to trust artificial intelligence

Vyacheslav Polonski’s (University of Oxford researcher) January 10, 2018 piece (originally published Jan. 9, 2018 on The Conversation) on phys.org isn’t a gossip article although there are parts that could be read that way. Before getting to what I consider the juicy bits (Note: Links have been removed),

Artificial intelligence [AI] can already predict the future. Police forces are using it to map when and where crime is likely to occur [Note: See my Nov. 23, 2017 posting about predictive policing in Vancouver for details about the first Canadian municipality to introduce the technology]. Doctors can use it to predict when a patient is most likely to have a heart attack or stroke. Researchers are even trying to give AI imagination so it can plan for unexpected consequences.

Many decisions in our lives require a good forecast, and AI agents are almost always better at forecasting than their human counterparts. Yet for all these technological advances, we still seem to deeply lack confidence in AI predictions. Recent cases show that people don’t like relying on AI and prefer to trust human experts, even if these experts are wrong.

The part (juicy bits) that satisfied some of my long held curiosity was this section on Watson and its life as a medical adjunct (Note: Links have been removed),

IBM’s attempt to promote its supercomputer programme to cancer doctors (Watson for Onology) was a PR [public relations] disaster. The AI promised to deliver top-quality recommendations on the treatment of 12 cancers that accounted for 80% of the world’s cases. As of today, over 14,000 patients worldwide have received advice based on its calculations.

But when doctors first interacted with Watson they found themselves in a rather difficult situation. On the one hand, if Watson provided guidance about a treatment that coincided with their own opinions, physicians did not see much value in Watson’s recommendations. The supercomputer was simply telling them what they already know, and these recommendations did not change the actual treatment. This may have given doctors some peace of mind, providing them with more confidence in their own decisions. But IBM has yet to provide evidence that Watson actually improves cancer survival rates.

On the other hand, if Watson generated a recommendation that contradicted the experts’ opinion, doctors would typically conclude that Watson wasn’t competent. And the machine wouldn’t be able to explain why its treatment was plausible because its machine learning algorithms were simply too complex to be fully understood by humans. Consequently, this has caused even more mistrust and disbelief, leading many doctors to ignore the seemingly outlandish AI recommendations and stick to their own expertise.

As a result, IBM Watson’s premier medical partner, the MD Anderson Cancer Center, recently announced it was dropping the programme. Similarly, a Danish hospital reportedly abandoned the AI programme after discovering that its cancer doctors disagreed with Watson in over two thirds of cases.

The problem with Watson for Oncology was that doctors simply didn’t trust it. Human trust is often based on our understanding of how other people think and having experience of their reliability. …

It seems to me there might be a bit more to the doctors’ trust issues and I was surprised it didn’t seem to have occurred to Polonski. Then I did some digging (from Polonski’s webpage on the Oxford Internet Institute website),

Vyacheslav Polonski (@slavacm) is a DPhil [PhD] student at the Oxford Internet Institute. His research interests are located at the intersection of network science, media studies and social psychology. Vyacheslav’s doctoral research examines the adoption and use of social network sites, focusing on the effects of social influence, social cognition and identity construction.

Vyacheslav is a Visiting Fellow at Harvard University and a Global Shaper at the World Economic Forum. He was awarded the Master of Science degree with Distinction in the Social Science of the Internet from the University of Oxford in 2013. He also obtained the Bachelor of Science degree with First Class Honours in Management from the London School of Economics and Political Science (LSE) in 2012.

Vyacheslav was honoured at the British Council International Student of the Year 2011 awards, and was named UK’s Student of the Year 2012 and national winner of the Future Business Leader of the Year 2012 awards by TARGETjobs.

Previously, he has worked as a management consultant at Roland Berger Strategy Consultants and gained further work experience at the World Economic Forum, PwC, Mars, Bertelsmann and Amazon.com. Besides, he was involved in several start-ups as part of the 2012 cohort of Entrepreneur First and as part of the founding team of the London office of Rocket Internet. Vyacheslav was the junior editor of the bi-lingual book ‘Inspire a Nation‘ about Barack Obama’s first presidential election campaign. In 2013, he was invited to be a keynote speaker at the inaugural TEDx conference of IE University in Spain to discuss the role of a networked mindset in everyday life.

Vyacheslav is fluent in German, English and Russian, and is passionate about new technologies, social entrepreneurship, philanthropy, philosophy and modern art.

Research interests

Network science, social network analysis, online communities, agency and structure, group dynamics, social interaction, big data, critical mass, network effects, knowledge networks, information diffusion, product adoption

Positions held at the OII

  • DPhil student, October 2013 –
  • MSc Student, October 2012 – August 2013

Polonski doesn’t seem to have any experience dealing with, participating in, or studying the medical community. Getting a doctor to admit that his or her approach to a particular patient’s condition was wrong or misguided runs counter to their training and, by extension, the institution of medicine. Also, one of the biggest problems in any field is getting people to change and it’s not always about trust. In this instance, you’re asking a doctor to back someone else’s opinion after he or she has rendered theirs. This is difficult even when the other party is another human doctor let alone a form of artificial intelligence.

If you want to get a sense of just how hard it is to get someone to back down after they’ve committed to a position, read this January 10, 2018 essay by Lara Bazelon, an associate professor at the University of San Francisco School of Law. This is just one of the cases (Note: Links have been removed),

Davontae Sanford was 14 years old when he confessed to murdering four people in a drug house on Detroit’s East Side. Left alone with detectives in a late-night interrogation, Sanford says he broke down after being told he could go home if he gave them “something.” On the advice of a lawyer whose license was later suspended for misconduct, Sanders pleaded guilty in the middle of his March 2008 trial and received a sentence of 39 to 92 years in prison.

Sixteen days after Sanford was sentenced, a hit man named Vincent Smothers told the police he had carried out 12 contract killings, including the four Sanford had pleaded guilty to committing. Smothers explained that he’d worked with an accomplice, Ernest Davis, and he provided a wealth of corroborating details to back up his account. Smothers told police where they could find one of the weapons used in the murders; the gun was recovered and ballistics matched it to the crime scene. He also told the police he had used a different gun in several of the other murders, which ballistics tests confirmed. Once Smothers’ confession was corroborated, it was clear Sanford was innocent. Smothers made this point explicitly in an 2015 affidavit, emphasizing that Sanford hadn’t been involved in the crimes “in any way.”

Guess what happened? (Note: Links have been removed),

But Smothers and Davis were never charged. Neither was Leroy Payne, the man Smothers alleged had paid him to commit the murders. …

Davontae Sanford, meanwhile, remained behind bars, locked up for crimes he very clearly didn’t commit.

Police failed to turn over all the relevant information in Smothers’ confession to Sanford’s legal team, as the law required them to do. When that information was leaked in 2009, Sanford’s attorneys sought to reverse his conviction on the basis of actual innocence. Wayne County Prosecutor Kym Worthy fought back, opposing the motion all the way to the Michigan Supreme Court. In 2014, the court sided with Worthy, ruling that actual innocence was not a valid reason to withdraw a guilty plea [emphasis mine]. Sanford would remain in prison for another two years.

Doctors are just as invested in their opinions and professional judgments as lawyers  (just like  the prosecutor and the judges on the Michigan Supreme Court) are.

There is one more problem. From the doctor’s (or anyone else’s perspective), if the AI is making the decisions, why do he/she need to be there? At best it’s as if AI were turning the doctor into its servant or, at worst, replacing the doctor. Polonski alludes to the problem in one of his solutions to the ‘trust’ issue (Note: A link has been removed),

Research suggests involving people more in the AI decision-making process could also improve trust and allow the AI to learn from human experience. For example,one study showed people were given the freedom to slightly modify an algorithm felt more satisfied with its decisions, more likely to believe it was superior and more likely to use it in the future.

Having input into the AI decision-making process somewhat addresses one of the problems but the commitment to one’s own judgment even when there is overwhelming evidence to the contrary is a perennially thorny problem. The legal case mentioned here earlier is clearly one where the contrarian is wrong but it’s not always that obvious. As well, sometimes, people who hold out against the majority are right.

US Army

Getting back to building trust, it turns out the US Army Research Laboratory is also interested in transparency where AI is concerned (from a January 11, 2018 US Army news release on EurekAlert),

U.S. Army Research Laboratory [ARL] scientists developed ways to improve collaboration between humans and artificially intelligent agents in two projects recently completed for the Autonomy Research Pilot Initiative supported by the Office of Secretary of Defense. They did so by enhancing the agent transparency [emphasis mine], which refers to a robot, unmanned vehicle, or software agent’s ability to convey to humans its intent, performance, future plans, and reasoning process.

“As machine agents become more sophisticated and independent, it is critical for their human counterparts to understand their intent, behaviors, reasoning process behind those behaviors, and expected outcomes so the humans can properly calibrate their trust [emphasis mine] in the systems and make appropriate decisions,” explained ARL’s Dr. Jessie Chen, senior research psychologist.

The U.S. Defense Science Board, in a 2016 report, identified six barriers to human trust in autonomous systems, with ‘low observability, predictability, directability and auditability’ as well as ‘low mutual understanding of common goals’ being among the key issues.

In order to address these issues, Chen and her colleagues developed the Situation awareness-based Agent Transparency, or SAT, model and measured its effectiveness on human-agent team performance in a series of human factors studies supported by the ARPI. The SAT model deals with the information requirements from an agent to its human collaborator in order for the human to obtain effective situation awareness of the agent in its tasking environment. At the first SAT level, the agent provides the operator with the basic information about its current state and goals, intentions, and plans. At the second level, the agent reveals its reasoning process as well as the constraints/affordances that the agent considers when planning its actions. At the third SAT level, the agent provides the operator with information regarding its projection of future states, predicted consequences, likelihood of success/failure, and any uncertainty associated with the aforementioned projections.

In one of the ARPI projects, IMPACT, a research program on human-agent teaming for management of multiple heterogeneous unmanned vehicles, ARL’s experimental effort focused on examining the effects of levels of agent transparency, based on the SAT model, on human operators’ decision making during military scenarios. The results of a series of human factors experiments collectively suggest that transparency on the part of the agent benefits the human’s decision making and thus the overall human-agent team performance. More specifically, researchers said the human’s trust in the agent was significantly better calibrated — accepting the agent’s plan when it is correct and rejecting it when it is incorrect– when the agent had a higher level of transparency.

The other project related to agent transparency that Chen and her colleagues performed under the ARPI was Autonomous Squad Member, on which ARL collaborated with Naval Research Laboratory scientists. The ASM is a small ground robot that interacts with and communicates with an infantry squad. As part of the overall ASM program, Chen’s group developed transparency visualization concepts, which they used to investigate the effects of agent transparency levels on operator performance. Informed by the SAT model, the ASM’s user interface features an at a glance transparency module where user-tested iconographic representations of the agent’s plans, motivator, and projected outcomes are used to promote transparent interaction with the agent. A series of human factors studies on the ASM’s user interface have investigated the effects of agent transparency on the human teammate’s situation awareness, trust in the ASM, and workload. The results, consistent with the IMPACT project’s findings, demonstrated the positive effects of agent transparency on the human’s task performance without increase of perceived workload. The research participants also reported that they felt the ASM as more trustworthy, intelligent, and human-like when it conveyed greater levels of transparency.

Chen and her colleagues are currently expanding the SAT model into bidirectional transparency between the human and the agent.

“Bidirectional transparency, although conceptually straightforward–human and agent being mutually transparent about their reasoning process–can be quite challenging to implement in real time. However, transparency on the part of the human should support the agent’s planning and performance–just as agent transparency can support the human’s situation awareness and task performance, which we have demonstrated in our studies,” Chen hypothesized.

The challenge is to design the user interfaces, which can include visual, auditory, and other modalities, that can support bidirectional transparency dynamically, in real time, while not overwhelming the human with too much information and burden.

Interesting, yes? Here’s a link and a citation for the paper,

Situation Awareness-based Agent Transparency and Human-Autonomy Teaming Effectiveness by Jessie Y.C. Chen, Shan G. Lakhmani, Kimberly Stowers, Anthony R. Selkowitz, Julia L. Wright, and Michael Barnes. Theoretical Issues in Ergonomics Science May 2018. DOI 10.1080/1463922X.2017.1315750

This paper is behind a paywall.

Canada’s ‘Smart Cities’ will need new technology (5G wireless) and, maybe, graphene

I recently published [March 20, 2018] a piece on ‘smart cities’ both an art/science event in Toronto and a Canadian government initiative without mentioning the necessity of new technology to support all of the grand plans. On that note, it seems the Canadian federal government and two provincial (Québec and Ontario) governments are prepared to invest in one of the necessary ‘new’ technologies, 5G wireless. The Canadian Broadcasting Corporation’s (CBC) Shawn Benjamin reports about Canada’s 5G plans in suitably breathless (even in text only) tones of excitement in a March 19, 2018 article,

The federal, Ontario and Quebec governments say they will spend $200 million to help fund research into 5G wireless technology, the next-generation networks with download speeds 100 times faster than current ones can handle.

The so-called “5G corridor,” known as ENCQOR, will see tech companies such as Ericsson, Ciena Canada, Thales Canada, IBM and CGI kick in another $200 million to develop facilities to get the project up and running.

The idea is to set up a network of linked research facilities and laboratories that these companies — and as many as 1,000 more across Canada — will be able to use to test products and services that run on 5G networks.

Benjamin’s description of 5G is focused on what it will make possible in the future,

If you think things are moving too fast, buckle up, because a new 5G cellular network is just around the corner and it promises to transform our lives by connecting nearly everything to a new, much faster, reliable wireless network.

The first networks won’t be operational for at least a few years, but technology and telecom companies around the world are already planning to spend billions to make sure they aren’t left behind, says Lawrence Surtees, a communications analyst with the research firm IDC.

The new 5G is no tentative baby step toward the future. Rather, as Surtees puts it, “the move from 4G to 5G is a quantum leap.”

In a downtown Toronto soundstage, Alan Smithson recently demonstrated a few virtual reality and augmented reality projects that his company MetaVRse is working on.

The potential for VR and AR technology is endless, he said, in large part for its potential to help hurdle some of the walls we are already seeing with current networks.

Virtual Reality technology on the market today is continually increasing things like frame rates and screen resolutions in a constant quest to make their devices even more lifelike.

… They [current 4G networks] can’t handle the load. But 5G can do so easily, Smithson said, so much so that the current era of bulky augmented reality headsets could be replaced buy a pair of normal looking glasses.

In a 5G world, those internet-connected glasses will automatically recognize everyone you meet, and possibly be able to overlay their name in your field of vision, along with a link to their online profile. …

Benjamin also mentions ‘smart cities’,

In a University of Toronto laboratory, Professor Alberto Leon-Garcia researches connected vehicles and smart power grids. “My passion right now is enabling smart cities — making smart cities a reality — and that means having much more immediate and detailed sense of the environment,” he said.

Faster 5G networks will assist his projects in many ways, by giving planners more, instant data on things like traffic patterns, energy consumption, variou carbon footprints and much more.

Leon-Garcia points to a brightly lit map of Toronto [image embedded in Benjamin’s article] in his office, and explains that every dot of light represents a sensor transmitting real time data.

Currently, the network is hooked up to things like city buses, traffic cameras and the city-owned fleet of shared bicycles. He currently has thousands of data points feeding him info on his map, but in a 5G world, the network will support about a million sensors per square kilometre.

Very exciting but where is all this data going? What computers will be processing the information? Where are these sensors located? Benjamin does not venture into those waters nor does The Economist in a February 13, 2018 article about 5G, the Olympic Games in Pyeonchang, South Korea, but the magazine does note another barrier to 5G implementation,

“FASTER, higher, stronger,” goes the Olympic motto. So it is only appropriate that the next generation of wireless technology, “5G” for short, should get its first showcase at the Winter Olympics  under way in Pyeongchang, South Korea. Once fully developed, it is supposed to offer download speeds of at least 20 gigabits per second (4G manages about half that at best) and response times (“latency”) of below 1 millisecond. So the new networks will be able to transfer a high-resolution movie in two seconds and respond to requests in less than a hundredth of the time it takes to blink an eye. But 5G is not just about faster and swifter wireless connections.

The technology is meant to enable all sorts of new services. One such would offer virtual- or augmented-reality experiences. At the Olympics, for example, many contestants are being followed by 360-degree video cameras. At special venues sports fans can don virtual-reality goggles to put themselves right into the action. But 5G is also supposed to become the connective tissue for the internet of things, to link anything from smartphones to wireless sensors and industrial robots to self-driving cars. This will be made possible by a technique called “network slicing”, which allows operators quickly to create bespoke networks that give each set of devices exactly the connectivity they need.

Despite its versatility, it is not clear how quickly 5G will take off. The biggest brake will be economic. [emphasis mine] When the GSMA, an industry group, last year asked 750 telecoms bosses about the most salient impediment to delivering 5G, more than half cited the lack of a clear business case. People may want more bandwidth, but they are not willing to pay for it—an attitude even the lure of the fanciest virtual-reality applications may not change. …

That may not be the only brake, Dexter Johnson in a March 19, 2018 posting on his Nanoclast blog (on the IEEE [Institute of Electrical and Electronics Engineers] website), covers some of the others (Note: Links have been removed),

Graphene has been heralded as a “wonder material” for well over a decade now, and 5G has been marketed as the next big thing for at least the past five years. Analysts have suggested that 5G could be the golden ticket to virtual reality and artificial intelligence, and promised that graphene could improve technologies within electronics and optoelectronics.

But proponents of both graphene and 5G have also been accused of stirring up hype. There now seems to be a rising sense within industry circles that these glowing technological prospects will not come anytime soon.

At Mobile World Congress (MWC) in Barcelona last month [February 2018], some misgivings for these long promised technologies may have been put to rest, though, thanks in large part to each other.

In a meeting at MWC with Jari Kinaret, a professor at Chalmers University in Sweden and director of the Graphene Flagship, I took a guided tour around the Pavilion to see some of the technologies poised to have an impact on the development of 5G.

Being invited back to the MWC for three years is a pretty clear indication of how important graphene is to those who are trying to raise the fortunes of 5G. But just how important became more obvious to me in an interview with Frank Koppens, the leader of the quantum nano-optoelectronic group at Institute of Photonic Sciences (ICFO) just outside of Barcelona, last year.

He said: “5G cannot just scale. Some new technology is needed. And that’s why we have several companies in the Graphene Flagship that are putting a lot of pressure on us to address this issue.”

In a collaboration led by CNIT—a consortium of Italian universities and national laboratories focused on communication technologies—researchers from AMO GmbH, Ericsson, Nokia Bell Labs, and Imec have developed graphene-based photodetectors and modulators capable of receiving and transmitting optical data faster than ever before.

The aim of all this speed for transmitting data is to support the ultrafast data streams with extreme bandwidth that will be part of 5G. In fact, at another section during MWC, Ericsson was presenting the switching of a 100 Gigabits per second (Gbps) channel based on the technology.

“The fact that Ericsson is demonstrating another version of this technology demonstrates that from Ericsson’s point of view, this is no longer just research” said Kinaret.

It’s no mystery why the big mobile companies are jumping on this technology. Not only does it provide high-speed data transmission, but it also does it 10 times more efficiently than silicon or doped silicon devices, and will eventually do it more cheaply than those devices, according to Vito Sorianello, senior researcher at CNIT.

Interestingly, Ericsson is one of the tech companies mentioned with regard to Canada’s 5G project, ENCQOR and Sweden’s Chalmers University, as Dexter Johnson notes, is the lead institution for the Graphene Flagship.. One other fact to note, Canada’s resources include graphite mines with ‘premium’ flakes for producing graphene. Canada’s graphite mines are located (as far as I know) in only two Canadian provinces, Ontario and Québec, which also happen to be pitching money into ENCQOR. My March 21, 2018 posting describes the latest entry into the Canadian graphite mining stakes.

As for the questions I posed about processing power, etc. It seems the South Koreans have found answers of some kind but it’s hard to evaluate as I haven’t found any additional information about 5G and its implementation in South Korea. If anyone has answers, please feel free to leave them in the ‘comments’. Thank you.

smARTcities SALON in Vaughan, Ontario, Canada on March 22, 2018

Thank goodness for the March 15, 2018 notice from the Art/Sci Salon in Toronto (received via email) announcing an event on smart cities being held in the nearby city of Vaughan (it borders Toronto to the north). It’s led me on quite the chase as I’ve delved into a reference to Smart City projects taking place across the country and the results follow after this bit about the event.

smARTcities SALON

From the announcement,

SMARTCITIES SALON

Smart City projects are currently underway across the country, including
Google SideWalk at Toronto Harbourfront. Canada’s first Smart Hospital
is currently under construction in the City of Vaughan. It’s an example
of the city working towards building a reputation as one of the world’s
leading Smart Cities, by adopting new technologies consistent with
priorities defined by citizen collaboration.

Hon. Maurizio Bevilacqua, P.C., Mayor chairs the Smart City Advisory
Task Force leading historic transformation in Vaughan. Working to become
a Smart City is a chance to encourage civic engagement, accelerate
economic growth, and generate efficiencies. His opening address will
outline some of the priorities and opportunities that our panel will
discuss.

PANELISTS

Lilian Radovac, PhD., Assistant Professor, Institute of Communication,
Culture, Information & Technology, University of Toronto. Lilian is a
historian of urban sounds and cultures and has a critical interest in
SmartCity initiatives in two of the cities she has called home: New York
City and Toronto..

Oren Berkovich is the CEO of Singularity University in Canada, an
educational institution and a global network of experts and
entrepreneurs that work together on solving the world’s biggest
challenges. As a catalyst for long-term growth Oren spends his time
connecting people with ideas to facilitate strategic conversations about
the future.

Frank Di Palma, the Chief Information Officer for the City of Vaughan,
is a graduate of York University with more than 20 years experience in
IT operations and services. Frank leads the many SmartCity initiatives
already underway at Vaughan City Hall.

Ron Wild, artist and Digital Art/Science Collaborator, will moderate the
discussion.

Audience Participation opportunities will enable attendees to forward
questions for consideration by the panel.

You can register for the smARTcities SALON here on Eventbrite,

Art Exhibition Reception

Following the panel discussion, the audience is invited to view the art exhibition ‘smARTcities; exploring the digital frontier.’ Works commissioned by Vaughan specifically for the exhibition, including the SmartCity Map and SmartHospital Map will be shown as well as other Art/Science-themed works. Many of these ‘maps’ were made by Ron in collaboration with mathematicians, scientists, and medical researchers, some of who will be in attendance. Further examples of Ron’s art can be found HERE

Please click through to buy a FREE ticket so we know how many guests to expect. Thank you.

This event can be reached by taking the subway up the #1 west line to the new Vaughan Metropolitan Centre terminal station. Take the #20 bus to the Vaughan Mills transfer loop; transfer there to the #4/A which will take you to the stop right at City Hall. Free parking is available for those coming by car. Car-pooling and ride-sharing is encouraged. The facility is fully accessible.

Here’s one of Wild’s pieces,

144×96″ triptych, Vaughan, 2018 Artist: mrowade (Ron Wild?)

I’m pretty sure that mrowade is Ron Wild.

Smart Cities, the rest of the country, and Vancouver

Much to my surprise, I covered the ‘Smart Cities’ story in its early (but not earliest) days (and before it was Smart Cities) in two posts: January 30, 2015 and January 27,2016 about the National Research Council of Canada (NRC) and its cities and technology public engagement exercises.

David Vogt in a July 12, 2016 posting on the Urban Opus website provides some catch up information,

Canada’s National Research Council (NRC) has identified Cities of the Future as a game-changing technology and economic opportunity.  Following a national dialogue, an Executive Summit was held in Toronto on March 31, 2016, resulting in an important summary report that will become the seed for Canadian R&D strategy in this sector.

The conclusion so far is that the opportunity for Canada is to muster leadership in the following three areas (in order):

  1. Better Infrastructure and Infrastructure Management
  2. Efficient Transportation; and
  3. Renewable Energy

The National Research Council (NRC) offers a more balanced view of the situation on its “NRC capabilities in smart infrastructure and cities of the future” webpage,

Key opportunities for Canada

North America is one of the most urbanised regions in the world (82 % living in urban areas in 2014).
With growing urbanisation, sustainable development challenges will be increasingly concentrated in cities, requiring technology solutions.
Smart cities are data-driven, relying on broadband and telecommunications, sensors, social media, data collection and integration, automation, analytics and visualization to provide real-time situational analysis.
Most infrastructure will be “smart” by 2030 and transportation systems will be intelligent, adaptive and connected.
Renewable energy, energy storage, power quality and load measurement will contribute to smart grid solutions that are integrated with transportation.
“Green”, sustainable and high-performing construction and infrastructure materials are in demand.

Canadian challenges

High energy use: Transportation accounts for roughly 23% of Canada’s total greenhouse gas emissions, followed closely by the energy consumption of buildings, which accounts for 12% of Canada’s greenhouse gas emissions (Canada’s United Nations Framework Convention on Climate Change report).
Traffic congestion in Canadian cities is increasing, contributing to loss of productivity, increased stress for citizens as well as air and noise pollution.
Canadian cities are susceptible to extreme weather and events related to climate change (e.g., floods, storms).
Changing demographics: aging population (need for accessible transportation options, housing, medical and recreational services) and diverse (immigrant) populations.
Financial and jurisdictional issues: the inability of municipalities (who have primary responsibility) to finance R&D or large-scale solutions without other government assistance.

Opportunities being examined
Living lab

Test bed for smart city technology in order to quantify and demonstrate the benefits of smart cities.
Multiple partnering opportunities (e.g. municipalities, other government organizations, industry associations, universities, social sciences, urban planning).

The integrated city

Efficient transportation: integration of personal mobility and freight movement as key city and inter-city infrastructure.
Efficient and integrated transportation systems linked to city infrastructure.
Planning urban environments for mobility while repurposing redundant infrastructures (converting parking to the food-water-energy nexus) as population shifts away from personal transportation.

FOOD-WATER-ENERGY NEXUS

Sustainable urban bio-cycling.
‎System approach to the development of the technology platforms required to address the nexus.

Key enabling platform technologies
Artificial intelligence

Computer vision and image understanding
Adaptive robots; future robotic platforms for part manufacturing
Understanding human emotions from language
Next generation information extraction using deep learning
Speech recognition
Artificial intelligence to optimize talent management for human resources

Nanomaterials

Nanoelectronics
Nanosensing
Smart materials
Nanocomposites
Self-assembled nanostructures
Nanoimprint
Nanoplasmonic
Nanoclay
Nanocoating

Big data analytics

Predictive equipment maintenance
Energy management
Artificial intelligence for optimizing energy storage and distribution
Understanding and tracking of hazardous chemical elements
Process and design optimization

Printed electronics for Internet of Things

Inks and materials
Printing technologies
Large area, flexible, stretchable, printed electronics components
Applications: sensors for Internet of Things, wearables, antenna, radio-frequency identification tags, smart surfaces, packaging, security, signage

If you’re curious about the government’s plan with regard to implementation, this NRC webpage provides some fascinating insight into their hopes if not the reality. (I have mentioned artificial intelligence and the federal government before in a March 16, 2018 posting about the federal budget and science; scroll down approximately 50% of the way to the subsection titled, Budget 2018: Who’s watching over us? and scan for Michael Karlin’s name.)

As for the current situation, there’s a Smart Cities Challenge taking place. Both Toronto and Vancouver have webpages dedicated to their response to the challenge. (You may want to check your own city’s website to find if it’s participating.)I have a preference for the Toronto page as they immediately state that they’re participating in this challenge and they provide an explanation for what they want from you. Vancouver’s page is by comparison a bit confusing with two videos being immediately presented to the reader and from there too many graphics competing for your attention. They do, however, offer something valuable, links to explanations for smart cities and for the challenge.

Here’s a description of the Smart Cities Challenge (from its webpage),

The Smart Cities Challenge

The Smart Cities Challenge is a pan-Canadian competition open to communities of all sizes, including municipalities, regional governments and Indigenous communities (First Nations, Métis and Inuit). The Challenge encourages communities to adopt a smart cities approach to improve the lives of their residents through innovation, data and connected technology.

  • One prize of up to $50 million open to all communities, regardless of population;
  • Two prizes of up to $10 million open to all communities with populations under 500,000 people; and
  • One prize of up to $5 million open to all communities with populations under 30,000 people.

Infrastructure Canada is engaging Indigenous leaders, communities and organizations to finalize the design of a competition specific to Indigenous communities that will reflect their unique realities and issues. Indigenous communities are also eligible to compete for all the prizes in the current competition.

The Challenge will be an open and transparent process. Communities that submit proposals will also post them online, so that residents and stakeholders can see them. An independent Jury will be appointed to select finalists and winners.

Applications are due by April 24, 2018. Communities interested in participating should visit the
Impact Canada Challenge Platform for the applicant guide and more information.

Finalists will be announced in the Summer of 2018 and winners in Spring 2019 according to the information on the Impact Canada Challenge Platform.

It’s not clear to me if she’s leading Vancouver’s effort to win the Smart Cities Challenge but Jessie Adcock’s (City of Vancouver Chief Digital Officer) Twitter feed certainly features information on the topic and, I suspect, if you’re looking for the most up-to-date information on Vancovuer’s participation, you’re more likely to find it on her feed than on the City of Vancouver’s Smart Cities Challenge webpage.

Tracking artificial intelligence

Researchers at Stanford University have developed an index for measuring (tracking) the progress made by artificial intelligence (AI) according to a January 9, 2018 news item on phys.org (Note: Links have been removed),

Since the term “artificial intelligence” (AI) was first used in print in 1956, the one-time science fiction fantasy has progressed to the very real prospect of driverless cars, smartphones that recognize complex spoken commands and computers that see.

In an effort to track the progress of this emerging field, a Stanford-led group of leading AI thinkers called the AI100 has launched an index that will provide a comprehensive baseline on the state of artificial intelligence and measure technological progress in the same way the gross domestic product and the S&P 500 index track the U.S. economy and the broader stock market.

For anyone curious about the AI100 initiative, I have a description of it in my Sept. 27, 2016 post highlighting the group’s first report or you can keep on reading.

Getting back to the matter at hand, a December 21, 2017 Stanford University press release by Andrew Myers, which originated the news item, provides more detail about the AI index,

“The AI100 effort realized that in order to supplement its regular review of AI, a more continuous set of collected metrics would be incredibly useful,” said Russ Altman, a professor of bioengineering and the faculty director of AI100. “We were very happy to seed the AI Index, which will inform the AI100 as we move forward.”

The AI100 was set in motion three years ago when Eric Horvitz, a Stanford alumnus and former president of the Association for the Advancement of Artificial Intelligence, worked with his wife, Mary Horvitz, to define and endow the long-term study. Its first report, released in the fall of 2016, sought to anticipate the likely effects of AI in an urban environment in the year 2030.

Among the key findings in the new index are a dramatic increase in AI startups and investment as well as significant improvements in the technology’s ability to mimic human performance.

Baseline metrics

The AI Index tracks and measures at least 18 independent vectors in academia, industry, open-source software and public interest, plus technical assessments of progress toward what the authors call “human-level performance” in areas such as speech recognition, question-answering and computer vision – algorithms that can identify objects and activities in 2D images. Specific metrics in the index include evaluations of academic papers published, course enrollment, AI-related startups, job openings, search-term frequency and media mentions, among others.

“In many ways, we are flying blind in our discussions about artificial intelligence and lack the data we need to credibly evaluate activity,” said Yoav Shoham, professor emeritus of computer science.

“The goal of the AI Index is to provide a fact-based measuring stick against which we can chart progress and fuel a deeper conversation about the future of the field,” Shoham said.

Shoham conceived of the index and assembled a steering committee including Ray Perrault from SRI International, Erik Brynjolfsson of the Massachusetts Institute of Technology and Jack Clark from OpenAI. The committee subsequently hired Calvin LeGassick as project manager.

“The AI Index will succeed only if it becomes a community effort,” Shoham said.

Although the authors say the AI Index is the first index to track either scientific or technological progress, there are many other non-financial indexes that provide valuable insight into equally hard-to-quantify fields. Examples include the Social Progress Index, the Middle East peace index and the Bangladesh empowerment index, which measure factors as wide-ranging as nutrition, sanitation, workload, leisure time, public sentiment and even public speaking opportunities.

Intriguing findings

Among the findings of this inaugural index is that the number of active AI startups has increased 14-fold since 2000. Venture capital investment has increased six times in the same period. In academia, publishing in AI has increased a similarly impressive nine times in the last 20 years while course enrollment has soared. Enrollment in the introductory AI-related machine learning course at Stanford, for instance, has grown 45-fold in the last 30 years.

In technical metrics, image and speech recognition are both approaching, if not surpassing, human-level performance. The authors noted that AI systems have excelled in such real-world applications as object detection, the ability to understand and answer questions and classification of photographic images of skin cancer cells

Shoham noted that the report is still very U.S.-centric and will need a greater international presence as well as a greater diversity of voices. He said he also sees opportunities to fold in government and corporate investment in addition to the venture capital funds that are currently included.

In terms of human-level performance, the AI Index suggests that in some ways AI has already arrived. This is true in game-playing applications including chess, the Jeopardy! game show and, most recently, the game of Go. Nonetheless, the authors note that computers continue to lag considerably in the ability to generalize specific information into deeper meaning.

“AI has made truly amazing strides in the past decade,” Shoham said, “but computers still can’t exhibit the common sense or the general intelligence of even a 5-year-old.”

The AI Index was made possible by funding from AI100, Google, Microsoft and Toutiao. Data supporting the various metrics were provided by Elsevier, TrendKite, Indeed.com, Monster.com, the Google Trends Team, the Google Brain Team, Sand Hill Econometrics, VentureSource, Crunchbase, Electronic Frontier Foundation, EuroMatrix, Geoff Sutcliffe, Kevin Leyton-Brown and Holger Hoose.

You can find the AI Index here. They’re featuring their 2017 report but you can also find data (on the menu bar on the upper right side of your screen), along with a few provisos. I was curious as to whether any AI had been used to analyze the data and/or write the report. A very cursory look at the 2017 report did not answer that question. I’m fascinated by the failure to address what I think is an obvious question. It suggests that even very, very bright people can become blind and I suspect that’s why the group seems quite eager to get others involved, from the 2017 AI Index Report,

As the report’s limitations illustrate, the AI Index will always paint a partial picture. For this reason, we include subjective commentary from a cross-section of AI experts. This Expert Forum helps animate the story behind the data in the report and adds interpretation the report lacks.

Finally, where the experts’ dialogue ends, your opportunity to Get Involved begins [emphasis mine]. We will need the feedback and participation of a larger community to address the issues identified in this report, uncover issues we have omitted, and build a productive process for tracking activity and progress in Artificial Intelligence. (p. 8)

Unfortunately, it’s not clear how one becomes involved. Is there a forum or do you get in touch with one of the team leaders?

I wish them good luck with their project and imagine that these minor hiccups will be dealt with in near term.

China is world leader in nanotechnology and in other fields too?

State of Chinese nanoscience/nanotechnology

China claims to be the world leader in the field in a white paper announced in an August 29, 2017 Springer Nature press release,

Springer Nature, the National Center for Nanoscience and Technology, China and the National Science Library of the Chinese Academy of Sciences (CAS) released in both Chinese and English a white paper entitled “Small Science in Big China: An overview of the state of Chinese nanoscience and technology” at NanoChina 2017, an international conference on nanoscience and technology held August 28 and 29 in Beijing. The white paper looks at the rapid growth of China’s nanoscience research into its current role as the world’s leader [emphasis mine], examines China’s strengths and challenges, and makes some suggestions for how its contribution to the field can continue to thrive.

The white paper points out that China has become a strong contributor to nanoscience research in the world, and is a powerhouse of nanotechnology R&D. Some of China’s basic research is leading the world. China’s applied nanoscience research and the industrialization of nanotechnologies have also begun to take shape. These achievements are largely due to China’s strong investment in nanoscience and technology. China’s nanoscience research is also moving from quantitative increase to quality improvement and innovation, with greater emphasis on the applications of nanotechnologies.

“China took an initial step into nanoscience research some twenty years ago, and has since grown its commitment at an unprecedented rate, as it has for scientific research as a whole. Such a growth is reflected both in research quantity and, importantly, in quality. Therefore, I regard nanoscience as a window through which to observe the development of Chinese science, and through which we could analyze how that rapid growth has happened. Further, the experience China has gained in developing nanoscience and related technologies is a valuable resource for the other countries and other fields of research to dig deep into and draw on,” said Arnout Jacobs, President, Greater China, Springer Nature.

The white paper explores at China’s research output relative to the rest of the world in terms of research paper output, research contribution contained in the Nano database, and finally patents, providing insight into China’s strengths and expertise in nano research. The white paper also presents the results of a survey of experts from the community discussing the outlook for and challenges to the future of China’s nanoscience research.

China nano research output: strong rise in quantity and quality

In 1997, around 13,000 nanoscience-related papers were published globally. By 2016, this number had risen to more than 154,000 nano-related research papers. This corresponds to a compound annual growth rate of 14% per annum, almost four times the growth in publications across all areas of research of 3.7%. Over the same period of time, the nano-related output from China grew from 820 papers in 1997 to over 52,000 papers in 2016, a compound annual growth rate of 24%.

China’s contribution to the global total has been growing steadily. In 1997, Chinese researchers co-authored just 6% of the nano-related papers contained in the Science Citation Index (SCI). By 2010, this grew to match the output of the United States. They now contribute over a third of the world’s total nanoscience output — almost twice that of the United States.

Additionally, China’s share of the most cited nanoscience papers has kept increasing year on year, with a compound annual growth rate of 22% — more than three times the global rate. It overtook the United States in 2014 and its contribution is now many times greater than that of any other country in the world, manifesting an impressive progression in both quantity and quality.

The rapid growth of nanoscience in China has been enabled by consistent and strong financial support from the Chinese government. As early as 1990, the State Science and Technology Committee, the predecessor of the Ministry of Science and Technology (MOST), launched the Climbing Up project on nanomaterial science. During the 1990s, the National Natural Science Foundation of China (NSFC) also funded nearly 1,000 small-scale projects in nanoscience. In the National Guideline on Medium- and Long-Term Program for Science and Technology Development (for 2006−2020) issued in early 2006 by the Chinese central government, nanoscience was identified as one of four areas of basic research and received the largest proportion of research budget out of the four areas. The brain boomerang, with more and more foreign-trained Chinese researchers returning from overseas, is another contributor to China’s rapid rise in nanoscience.

The white paper clarifies the role of Chinese institutions, including CAS, in driving China’s rise to become the world’s leader in nanoscience. Currently, CAS is the world’s largest producer of high impact nano research, contributing more than twice as many papers in the 1% most-cited nanoscience literature than its closest competitors. In addition to CAS, five other Chinese institutions are ranked among the global top 20 in terms of output of top cited 1% nanoscience papers — Tsinghua University, Fudan University, Zhejiang University, University of Science and Technology of China and Peking University.

Nano database reveals advantages and focus of China’s nano research

The Nano database (http://nano.nature.com) is a comprehensive platform that has been recently developed by Nature Research – part of Springer Nature – which contains nanoscience-related papers published in 167 peer-reviewed journals including Advanced Materials, Nano Letters, Nature, Science and more. Analysis of the Nano database of nanomaterial-containing articles published in top 30 journals during 2014–2016 shows that Chinese scientists explore a wide range of nanomaterials, the five most common of which are nanostructured materials, nanoparticles, nanosheets, nanodevices and nanoporous materials.

In terms of the research of applications, China has a clear leading edge in catalysis research, which is the most popular area of the country’s quality nanoscience papers. Chinese nano researchers also contributed significantly to nanomedicine and energy-related applications. China is relatively weaker in nanomaterials for electronics applications, compared to other research powerhouses, but robotics and lasers are emerging applications areas of nanoscience in China, and nanoscience papers addressing photonics and data storage applications also see strong growth in China. Over 80% of research from China listed in the database explicitly mentions applications of the nanostructures and nanomaterials described, notably higher than from most other leading nations such as the United States, Germany, the UK, Japan and France.

Nano also reveals the extent of China’s international collaborations in nano research. China has seen the percentage of its internationally collaborated papers increasing from 36% in 2014 to 44% in 2016. This level of international collaboration, similar to that of South Korea, is still much lower than that of the western countries, and the rate of growth is also not as fast as those in the United States, France and Germany.

The United States is China’s biggest international collaborator, contributing to 55% of China’s internationally collaborated papers on nanoscience that are included in the top 30 journals in the Nano database. Germany, Australia and Japan follow in a descending order as China’s collaborators on nano-related quality papers.

China’s patent output: topping the world, mostly applied domestically

Analysis of the Derwent Innovation Index (DII) database of Clarivate Analytics shows that China’s accumulative total number of patent applications for the past 20 years, amounting to 209,344 applications, or 45% of the global total, is more than twice as many as that of the United States, the second largest contributor to nano-related patents. China surpassed the United States and ranked the top in the world since 2008.

Five Chinese institutions, including the CAS, Zhejiang University, Tsinghua University, Hon Hai Precision Industry Co., Ltd. and Tianjin University can be found among the global top 10 institutional contributors to nano-related patent applications. CAS has been at the top of the global rankings since 2008, with a total of 11,218 patent applications for the past 20 years. Interestingly, outside of China, most of the other big institutional contributors among the top 10 are commercial enterprises, while in China, research or academic institutions are leading in patent applications.

However, the number of nano-related patents China applied overseas is still very low, accounting for only 2.61% of its total patent applications for the last 20 years cumulatively, whereas the proportion in the United States is nearly 50%. In some European countries, including the UK and France, more than 70% of patent applications are filed overseas.

China has high numbers of patent applications in several popular technical areas for nanotechnology use, and is strongest in patents for polymer compositions and macromolecular compounds. In comparison, nano-related patent applications in the United States, South Korea and Japan are mainly for electronics or semiconductor devices, with the United States leading the world in the cumulative number of patents for semiconductor devices.

Outlook, opportunities and challenges

The white paper highlights that the rapid rise of China’s research output and patent applications has painted a rosy picture for the development of Chinese nanoscience, and in both the traditionally strong subjects and newly emerging areas, Chinese nanoscience shows great potential.

Several interviewed experts in the survey identify catalysis and catalytic nanomaterials as the most promising nanoscience area for China. The use of nanotechnology in the energy and medical sectors was also considered very promising.

Some of the interviewed experts commented that the industrial impact of China’s nanotechnology is limited and there is still a gap between nanoscience research and the industrialization of nanotechnologies. Therefore, they recommended that the government invest more in applied research to drive the translation of nanoscience research and find ways to encourage enterprises to invest more in R&D.

As more and more young scientists enter the field, the competition for research funding is becoming more intense. However, this increasing competition for funding was not found to concern most interviewed young scientists, rather, they emphasized that the soft environment is more important. They recommended establishing channels that allow the suggestions or creative ideas of the young to be heard. Also, some interviewed young researchers commented that they felt that the current evaluation system was geared towards past achievements or favoured overseas experience, and recommended the development of an improved talent selection mechanism to ensure a sustainable growth of China’s nanoscience.

I have taken a look at the white paper and found it to be well written. It also provides a brief but thorough history of nanotechnology/nanoscience even adding a bit of historical information that was new to me. As for the rest of the white paper, it relies on bibliometrics (number of published papers and number of citations) and number of patents filed to lay the groundwork for claiming Chinese leadership in nanotechnology. As I’ve stated many times before, these are problematic measures but as far as I can determine they are almost the only ones we have. Frankly, as a Canadian, it doesn’t much matter to me since Canada no matter how you slice or dice it is always in a lower tier relative to science leadership in major fields. It’s the Americans who might feel inclined to debate leadership with regard to nanotechnology and other major fields and I leave it to to US commentators to take up the cudgels should they be inclined. The big bonuses here are the history, the glimpse into the Chinese perspective on the field of nanotechnology/nanoscience, and the analysis of weaknesses and strengths.

Coming up fast on Google and Amazon

A November 16, 2017 article by Christina Bonnington for Slate explores the possibility that a Chinese tech giant, Baidu,  will provide Google and Amazon serious competition in their quests to dominate world markets (Note: Links have been removed,

raven_h
The company took a playful approach to the form—but it has functional reasons for the design, too. Baidu

 

One of the most interesting companies in tech right now isn’t based in Palo Alto, or San Francisco, or Seattle. Baidu, a Chinese company with headquarters in Beijing, is taking on America’s biggest and most innovative tech titans—with style.

Baidu, a titan in its own right, leapt onto the scene as a competitor to Google in the search engine space. Since then, the company, largely underappreciated here in the U.S., has focused on beefing up its artificial intelligence efforts. Former AI chief Andrew Ng, upon leaving the company in March, credited Baidu’s CEO Robin Li on being one of the first technology leaders to fully appreciate the value of deep learning. Baidu now has a 1,300 person AI group, and that investment in AI has helped the company catch up to older, more established companies like Google and Amazon—both in emerging spaces, such as autonomous vehicles, and in consumer tech, as its latest announcement shows.

On Thursday [November 16, 2017], Baidu debuted its entrants to the popular virtual assistant space: a connected speaker and two robots. Baidu aims for the speaker to compete against options such as Amazon’s Echo line, Google Home, and Apple HomePod. Inside, the $256 device will utilize Baidu’s DuerOS conversational artificial intelligence platform, which is already used in more than 100 different smart home brands’ products. DuerOS will let you use your voice to do things like ask the speaker for information, play music, or hail a cab. Called the Raven H, the speaker includes high-end audio components from Tymphany and a unique design jointly created by acquired startup Raven Tech and Swedish consumer electronics company Teenage Engineering.

While the focus is on exciting new technology products from Baidu, the subtext, such as it is, suggests US companies had best keep an eye on its Chinese competitor(s).

Dutch/Chinese partnership to produce nanoparticles at the touch of a button

Now back to China and nanotechnology leadership and the production of nanoparticles. This announcement was made in a November 17, 2017 news item on Azonano,

Delft University of Technology [Netherlands] spin-off VSPARTICLE enters the booming Chinese market with a radical technology that allows researchers to produce nanoparticles at the push of a button. VSPARTICLE’s nanoparticle generator uses atoms, the worlds’ smallest building blocks, to provide a controllable source of nanoparticles. The start-up from Delft signed a distribution agreement with Bio-Sun to make their VSP-G1 nanoparticle generator available in China.

A November 16, 2017 VSPARTICLE press release, which originated the news item,

“We are honoured to cooperate with VSPARTICLE and bring the innovative VSP-G1 nanoparticle generator into the Chinese market. The VSP-G1 will create new possibilities for researchers in catalysis, aerosol, healthcare and electronics,” says Yinghui Cai, CEO of Bio-Sun.

With an exponential growth in nanoparticle research in the last decade, China is one of the leading countries in the field of nanotechnology and its applications. Vincent Laban, CFO of VSPARTICLE, explains: “Due to its immense investments in IOT, sensors, semiconductor technology, renewable energy and healthcare applications, China will eventually become one of our biggest markets. The collaboration with Bio-Sun offers a valuable opportunity to enter the Chinese market at exactly the right time.”

NANOPARTICLES ARE THE BUILDING BLOCKS OF THE FUTURE

Increasingly, scientists are focusing on nanoparticles as a key technology in enabling the transition to a sustainable future. Nanoparticles are used to make new types of sensors and smart electronics; provide new imaging and treatment possibilities in healthcare; and reduce harmful waste in chemical processes.

CURRENT RESEARCH TOOLKIT LACKS A FAST WAY FOR MAKING SPECIFIC BUILDING BLOCKS

With the latest tools in nanotechnology, researchers are exploring the possibilities of building novel materials. This is, however, a trial-and-error method. Getting the right nanoparticles often is a slow struggle, as most production methods take a substantial amount of effort and time to develop.

VSPARTICLE’S VSP-G1 NANOPARTICLE GENERATOR

With the VSP-G1 nanoparticle generator, VSPARTICLE makes the production of nanoparticles as easy as pushing a button. . Easy and fast iterations enable researchers to fast forward their research cycle, and verify their hypotheses.

VSPARTICLE

Born out of the research labs of Delft University of Technology, with over 20 years of experience in the synthesis of aerosol, VSPARTICLE believes there is a whole new world of possibilities and materials at the nanoscale. The company was founded in 2014 and has an international sales network in Europe, Japan and China.

BIO-SUN

Bio-Sun was founded in Beijing in 2010 and is a leader in promoting nanotechnology and biotechnology instruments in China. It serves many renowned customers in life science, drug discovery and material science. Bio-Sun has four branch offices in Qingdao, Shanghai, Guangzhou and Wuhan City, and a nationwide sale network.

That’s all folks!

Memristors at Masdar

The Masdar Institute of Science and Technology (Abu Dhabi, United Arab Emirates; Masdar Institute Wikipedia entry) featured its work with memristors in an Oct. 1, 2017 Masdar Institute press release by Erica Solomon (for anyone who’s interested, I have a simple description of memristors and links to more posts about them after the press release),

Researchers Develop New Memristor Prototype Capable of Performing Complex Operations at High-Speed and Low Power, Could Lead to Advancements in Internet of Things, Portable Healthcare Sensing and other Embedded Technologies

Computer circuits in development at the Khalifa University of Science and Technology could make future computers much more compact, efficient and powerful thanks to advancements being made in memory technologies that combine processing and memory storage functions into one densely packed “memristor.”

Enabling faster, smaller and ultra-low-power computers with memristors could have a big impact on embedded technologies, which enable Internet of Things (IoT), artificial intelligence, and portable healthcare sensing systems, says Dr. Baker Mohammad, Associate Professor of Electrical and Computer Engineering. Dr. Mohammad co-authored a book on memristor technologies, which has just been released by Springer, a leading global scientific publisher of books and journals, with Class of 2017 PhD graduate Heba Abunahla. The book, titled Memristor Technology: Synthesis and Modeling for Sensing and Security Applications, provides readers with a single-source guide to fabricate, characterize and model memristor devices for sensing applications.

The pair also contributed to a paper on memristor research that was published in IEEE Transactions on Circuits and Systems I: Regular Papers earlier this month with Class of 2017 MSc graduate Muath Abu Lebdeh and Dr. Mahmoud Al-Qutayri, Professor of Electrical and Computer Engineering.PhD student Yasmin Halawani is also an active member of Dr. Mohammad’s research team.

Conventional computers rely on energy and time-consuming processes to move information back and forth between the computer central processing unit (CPU) and the memory, which are separately located. A memristor, which is an electrical resistor that remembers how much current flows through it, can bridge the gap between computation and storage. Instead of fetching data from the memory and sending that data to the CPU where it is then processed, memristors have the potential to store and process data simultaneously.

“Memristors allow computers to perform many operations at the same time without having to move data around, thereby reducing latency, energy requirements, costs and chip size,” Dr. Mohammad explained. “We are focused on extending the logic gate design of the current memristor architecture with one that leads to even greater reduction of latency, energy dissipation and size.”

Logic gates control an electronics logical operation on one or more binary inputs and typically produce a single binary output. That is why they are at the heart of what makes a computer work, allowing a CPU to carry out a given set of instructions, which are received as electrical signals, using one or a combination of the seven basic logical operations: AND, OR, NOT, XOR, XNOR, NAND and NOR.

The team’s latest work is aimed at advancing a memristor’s ability to perform a complex logic operation, known as the XNOR (Exclusive NOR) logic gate function, which is the most complex logic gate operation among the seven basic logic gates types.

Designing memristive logic gates is difficult, as they require that each electrical input and output be in the form of electrical resistance rather than electrical voltage.

“However, we were able to successfully design an XNOR logic gate prototype with a novel structure, by layering bipolar and unipolar memristor types in a novel heterogeneous structure, which led to a reduction in latency and energy consumption for a memristive XNOR logic circuit gate by 50% compared to state-of the art state full logic proposed by leading research institutes,” Dr. Mohammad revealed.

The team’s current work builds on five years of research in the field of memristors, which is expected to reach a market value of US$384 million by 2025, according to a recent report from Research and Markets. Up to now, the team has fabricated and characterized several memristor prototypes, assessing how different design structures influence efficiency and inform potential applications. Some innovative memristor technology applications the team discovered include machine vision, radiation sensing and diabetes detection. Two patents have already been issued by the US Patents and Trademark Office (USPTO) for novel memristor designs invented by the team, with two additional patents pending.

Their robust research efforts have also led to the publication of several papers on the technology in high impact journals, including The Journal of Physical Chemistry, Materials Chemistry and Physics, and IEEE TCAS. This strong technology base paved the way for undergraduate senior students Reem Aldahmani, Amani Alshkeili, and Reem Jassem Jaffar to build novel and efficient memristive sensing prototypes.

The memristor research is also set to get an additional boost thanks to the new University merger, which Dr. Mohammad believes could help expedite the team’s research and development efforts through convenient and continuous access to the wider range of specialized facilities and tools the new university has on offer.

The team’s prototype memristors are now in the laboratory prototype stage, and Dr. Mohammad plans to initiate discussions for internal partnership opportunities with the Khalifa University Robotics Institute, followed by external collaboration with leading semiconductor companies such as Abu Dhabi-owned GlobalFoundries, to accelerate the transfer of his team’s technology to the market.

With initial positive findings and the promise of further development through the University’s enhanced portfolio of research facilities, this project is a perfect demonstration of how the Khalifa University of Science and Technology is pushing the envelope of electronics and semiconductor technologies to help transform Abu Dhabi into a high-tech hub for research and entrepreneurship.

h/t Oct. 4, 2017 Nanowerk news item

Slightly restating it from the press release, a memristor is a nanoscale electrical component which mimics neural plasticity. Memristor combines the word ‘memory’ with ‘resistor’.

For those who’d like a little more, there are three components: capacitors, inductors, and resistors which make up an electrical circuit. The resistor is the circuit element which represents the resistance to the flow of electric current.  As for how this relates to the memristor (from the Memristor Wikipedia entry; Note: Links have been removed),

The memristor’s electrical resistance is not constant but depends on the history of current that had previously flowed through the device, i.e., its present resistance depends on how much electric charge has flowed in what direction through it in the past; the device remembers its history — the so-called non-volatility property.[2] When the electric power supply is turned off, the memristor remembers its most recent resistance until it is turned on again

The memristor could lead to more energy-saving devices but much of the current (pun noted) interest lies in its similarity to neural plasticity and its potential application on neuromorphic engineering (brainlike computing).

Here’s a sampling of some of the more recent memristor postings on this blog:

August 24, 2017: Neuristors and brainlike computing

June 28, 2017: Dr. Wei Lu and bio-inspired ‘memristor’ chips

May 2, 2017: Predicting how a memristor functions

December 30, 2016: Changing synaptic connectivity with a memristor

December 5, 2016: The memristor as computing device

November 1, 2016: The memristor as the ‘missing link’ in bioelectronic medicine?

You can find more by using ‘memristor’ as the search term in the blog search function or on the search engine of your choice.