Tag Archives: University of Washington

Machine learning programs learn bias

The notion of bias in artificial intelligence (AI)/algorithms/robots is gaining prominence (links to other posts featuring algorithms and bias are at the end of this post). The latest research concerns machine learning where an artificial intelligence system trains itself with ordinary human language from the internet. From an April 13, 2017 American Association for the Advancement of Science (AAAS) news release on EurekAlert,

As artificial intelligence systems “learn” language from existing texts, they exhibit the same biases that humans do, a new study reveals. The results not only provide a tool for studying prejudicial attitudes and behavior in humans, but also emphasize how language is intimately intertwined with historical biases and cultural stereotypes. A common way to measure biases in humans is the Implicit Association Test (IAT), where subjects are asked to pair two concepts they find similar, in contrast to two concepts they find different; their response times can vary greatly, indicating how well they associated one word with another (for example, people are more likely to associate “flowers” with “pleasant,” and “insects” with “unpleasant”). Here, Aylin Caliskan and colleagues developed a similar way to measure biases in AI systems that acquire language from human texts; rather than measuring lag time, however, they used the statistical number of associations between words, analyzing roughly 2.2 million words in total. Their results demonstrate that AI systems retain biases seen in humans. For example, studies of human behavior show that the exact same resume is 50% more likely to result in an opportunity for an interview if the candidate’s name is European American rather than African-American. Indeed, the AI system was more likely to associate European American names with “pleasant” stimuli (e.g. “gift,” or “happy”). In terms of gender, the AI system also reflected human biases, where female words (e.g., “woman” and “girl”) were more associated than male words with the arts, compared to mathematics. In a related Perspective, Anthony G. Greenwald discusses these findings and how they could be used to further analyze biases in the real world.

There are more details about the research in this April 13, 2017 Princeton University news release on EurekAlert (also on ScienceDaily),

In debates over the future of artificial intelligence, many experts think of the new systems as coldly logical and objectively rational. But in a new study, researchers have demonstrated how machines can be reflections of us, their creators, in potentially problematic ways. Common machine learning programs, when trained with ordinary human language available online, can acquire cultural biases embedded in the patterns of wording, the researchers found. These biases range from the morally neutral, like a preference for flowers over insects, to the objectionable views of race and gender.

Identifying and addressing possible bias in machine learning will be critically important as we increasingly turn to computers for processing the natural language humans use to communicate, for instance in doing online text searches, image categorization and automated translations.

“Questions about fairness and bias in machine learning are tremendously important for our society,” said researcher Arvind Narayanan, an assistant professor of computer science and an affiliated faculty member at the Center for Information Technology Policy (CITP) at Princeton University, as well as an affiliate scholar at Stanford Law School’s Center for Internet and Society. “We have a situation where these artificial intelligence systems may be perpetuating historical patterns of bias that we might find socially unacceptable and which we might be trying to move away from.”

The paper, “Semantics derived automatically from language corpora contain human-like biases,” published April 14  [2017] in Science. Its lead author is Aylin Caliskan, a postdoctoral research associate and a CITP fellow at Princeton; Joanna Bryson, a reader at University of Bath, and CITP affiliate, is a coauthor.

As a touchstone for documented human biases, the study turned to the Implicit Association Test, used in numerous social psychology studies since its development at the University of Washington in the late 1990s. The test measures response times (in milliseconds) by human subjects asked to pair word concepts displayed on a computer screen. Response times are far shorter, the Implicit Association Test has repeatedly shown, when subjects are asked to pair two concepts they find similar, versus two concepts they find dissimilar.

Take flower types, like “rose” and “daisy,” and insects like “ant” and “moth.” These words can be paired with pleasant concepts, like “caress” and “love,” or unpleasant notions, like “filth” and “ugly.” People more quickly associate the flower words with pleasant concepts, and the insect terms with unpleasant ideas.

The Princeton team devised an experiment with a program where it essentially functioned like a machine learning version of the Implicit Association Test. Called GloVe, and developed by Stanford University researchers, the popular, open-source program is of the sort that a startup machine learning company might use at the heart of its product. The GloVe algorithm can represent the co-occurrence statistics of words in, say, a 10-word window of text. Words that often appear near one another have a stronger association than those words that seldom do.

The Stanford researchers turned GloVe loose on a huge trawl of contents from the World Wide Web, containing 840 billion words. Within this large sample of written human culture, Narayanan and colleagues then examined sets of so-called target words, like “programmer, engineer, scientist” and “nurse, teacher, librarian” alongside two sets of attribute words, such as “man, male” and “woman, female,” looking for evidence of the kinds of biases humans can unwittingly possess.

In the results, innocent, inoffensive biases, like for flowers over bugs, showed up, but so did examples along lines of gender and race. As it turned out, the Princeton machine learning experiment managed to replicate the broad substantiations of bias found in select Implicit Association Test studies over the years that have relied on live, human subjects.

For instance, the machine learning program associated female names more with familial attribute words, like “parents” and “wedding,” than male names. In turn, male names had stronger associations with career attributes, like “professional” and “salary.” Of course, results such as these are often just objective reflections of the true, unequal distributions of occupation types with respect to gender–like how 77 percent of computer programmers are male, according to the U.S. Bureau of Labor Statistics.

Yet this correctly distinguished bias about occupations can end up having pernicious, sexist effects. An example: when foreign languages are naively processed by machine learning programs, leading to gender-stereotyped sentences. The Turkish language uses a gender-neutral, third person pronoun, “o.” Plugged into the well-known, online translation service Google Translate, however, the Turkish sentences “o bir doktor” and “o bir hem?ire” with this gender-neutral pronoun are translated into English as “he is a doctor” and “she is a nurse.”

“This paper reiterates the important point that machine learning methods are not ‘objective’ or ‘unbiased’ just because they rely on mathematics and algorithms,” said Hanna Wallach, a senior researcher at Microsoft Research New York City, who was not involved in the study. “Rather, as long as they are trained using data from society and as long as society exhibits biases, these methods will likely reproduce these biases.”

Another objectionable example harkens back to a well-known 2004 paper by Marianne Bertrand of the University of Chicago Booth School of Business and Sendhil Mullainathan of Harvard University. The economists sent out close to 5,000 identical resumes to 1,300 job advertisements, changing only the applicants’ names to be either traditionally European American or African American. The former group was 50 percent more likely to be offered an interview than the latter. In an apparent corroboration of this bias, the new Princeton study demonstrated that a set of African American names had more unpleasantness associations than a European American set.

Computer programmers might hope to prevent cultural stereotype perpetuation through the development of explicit, mathematics-based instructions for the machine learning programs underlying AI systems. Not unlike how parents and mentors try to instill concepts of fairness and equality in children and students, coders could endeavor to make machines reflect the better angels of human nature.

“The biases that we studied in the paper are easy to overlook when designers are creating systems,” said Narayanan. “The biases and stereotypes in our society reflected in our language are complex and longstanding. Rather than trying to sanitize or eliminate them, we should treat biases as part of the language and establish an explicit way in machine learning of determining what we consider acceptable and unacceptable.”

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

Semantics derived automatically from language corpora contain human-like biases by Aylin Caliskan, Joanna J. Bryson, Arvind Narayanan. Science  14 Apr 2017: Vol. 356, Issue 6334, pp. 183-186 DOI: 10.1126/science.aal4230

This paper appears to be open access.

Links to more cautionary posts about AI,

Aug 5, 2009: Autonomous algorithms; intelligent windows; pretty nano pictures

June 14, 2016:  Accountability for artificial intelligence decision-making

Oct. 25, 2016 Removing gender-based stereotypes from algorithms

March 1, 2017: Algorithms in decision-making: a government inquiry in the UK

There’s also a book which makes some of the current use of AI programmes and big data quite accessible reading: Cathy O’Neal’s ‘Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy’.

Quadriplegic man reanimates a limb with implanted brain-recording and muscle-stimulating systems

It took me a few minutes to figure out why this item about a quadriplegic (also known as, tetraplegic) man is news. After all, I have a May 17, 2012 posting which features a video and information about a quadri(tetra)plegic woman who was drinking her first cup of coffee, independently, in many years. The difference is that she was using an external robotic arm and this man is using *his own arm*,

This Case Western Reserve University (CRWU) video accompanies a March 28, 2017 CRWU news release, (h/t ScienceDaily March 28, 2017 news item)

Bill Kochevar grabbed a mug of water, drew it to his lips and drank through the straw.

His motions were slow and deliberate, but then Kochevar hadn’t moved his right arm or hand for eight years.

And it took some practice to reach and grasp just by thinking about it.

Kochevar, who was paralyzed below his shoulders in a bicycling accident, is believed to be the first person with quadriplegia in the world to have arm and hand movements restored with the help of two temporarily implanted technologies.

A brain-computer interface with recording electrodes under his skull, and a functional electrical stimulation (FES) system* activating his arm and hand, reconnect his brain to paralyzed muscles.

Holding a makeshift handle pierced through a dry sponge, Kochevar scratched the side of his nose with the sponge. He scooped forkfuls of mashed potatoes from a bowl—perhaps his top goal—and savored each mouthful.

“For somebody who’s been injured eight years and couldn’t move, being able to move just that little bit is awesome to me,” said Kochevar, 56, of Cleveland. “It’s better than I thought it would be.”

Kochevar is the focal point of research led by Case Western Reserve University, the Cleveland Functional Electrical Stimulation (FES) Center at the Louis Stokes Cleveland VA Medical Center and University Hospitals Cleveland Medical Center (UH). A study of the work was published in the The Lancet March 28 [2017] at 6:30 p.m. U.S. Eastern time.

“He’s really breaking ground for the spinal cord injury community,” said Bob Kirsch, chair of Case Western Reserve’s Department of Biomedical Engineering, executive director of the FES Center and principal investigator (PI) and senior author of the research. “This is a major step toward restoring some independence.”

When asked, people with quadriplegia say their first priority is to scratch an itch, feed themselves or perform other simple functions with their arm and hand, instead of relying on caregivers.

“By taking the brain signals generated when Bill attempts to move, and using them to control the stimulation of his arm and hand, he was able to perform personal functions that were important to him,” said Bolu Ajiboye, assistant professor of biomedical engineering and lead study author.

Technology and training

The research with Kochevar is part of the ongoing BrainGate2* pilot clinical trial being conducted by a consortium of academic and VA institutions assessing the safety and feasibility of the implanted brain-computer interface (BCI) system in people with paralysis. Other investigational BrainGate research has shown that people with paralysis can control a cursor on a computer screen or a robotic arm (braingate.org).

“Every day, most of us take for granted that when we will to move, we can move any part of our body with precision and control in multiple directions and those with traumatic spinal cord injury or any other form of paralysis cannot,” said Benjamin Walter, associate professor of neurology at Case Western Reserve School of Medicine, clinical PI of the Cleveland BrainGate2 trial and medical director of the Deep Brain Stimulation Program at UH Cleveland Medical Center.

“The ultimate hope of any of these individuals is to restore this function,” Walter said. “By restoring the communication of the will to move from the brain directly to the body this work will hopefully begin to restore the hope of millions of paralyzed individuals that someday they will be able to move freely again.”

Jonathan Miller, assistant professor of neurosurgery at Case Western Reserve School of Medicine and director of the Functional and Restorative Neurosurgery Center at UH, led a team of surgeons who implanted two 96-channel electrode arrays—each about the size of a baby aspirin—in Kochevar’s motor cortex, on the surface of the brain.

The arrays record brain signals created when Kochevar imagines movement of his own arm and hand. The brain-computer interface extracts information from the brain signals about what movements he intends to make, then passes the information to command the electrical stimulation system.

To prepare him to use his arm again, Kochevar first learned how to use his brain signals to move a virtual-reality arm on a computer screen.

“He was able to do it within a few minutes,” Kirsch said. “The code was still in his brain.”

As Kochevar’s ability to move the virtual arm improved through four months of training, the researchers believed he would be capable of controlling his own arm and hand.

Miller then led a team that implanted the FES systems’ 36 electrodes that animate muscles in the upper and lower arm.

The BCI decodes the recorded brain signals into the intended movement command, which is then converted by the FES system into patterns of electrical pulses.

The pulses sent through the FES electrodes trigger the muscles controlling Kochevar’s hand, wrist, arm, elbow and shoulder. To overcome gravity that would otherwise prevent him from raising his arm and reaching, Kochevar uses a mobile arm support, which is also under his brain’s control.

New Capabilities

Eight years of muscle atrophy required rehabilitation. The researchers exercised Kochevar’s arm and hand with cyclical electrical stimulation patterns. Over 45 weeks, his strength, range of motion and endurance improved. As he practiced movements, the researchers adjusted stimulation patterns to further his abilities.

Kochevar can make each joint in his right arm move individually. Or, just by thinking about a task such as feeding himself or getting a drink, the muscles are activated in a coordinated fashion.

When asked to describe how he commanded the arm movements, Kochevar told investigators, “I’m making it move without having to really concentrate hard at it…I just think ‘out’…and it goes.”

Kocehvar is fitted with temporarily implanted FES technology that has a track record of reliable use in people. The BCI and FES system together represent early feasibility that gives the research team insights into the potential future benefit of the combined system.

Advances needed to make the combined technology usable outside of a lab are not far from reality, the researchers say. Work is underway to make the brain implant wireless, and the investigators are improving decoding and stimulation patterns needed to make movements more precise. Fully implantable FES systems have already been developed and are also being tested in separate clinical research.

Kochevar welcomes new technology—even if it requires more surgery—that will enable him to move better. “This won’t replace caregivers,” he said. “But, in the long term, people will be able, in a limited way, to do more for themselves.”

There is more about the research in a March 29, 2017 article by Sarah Boseley for The Guardian,

Bill Kochevar, 53, has had electrical implants in the motor cortex of his brain and sensors inserted in his forearm, which allow the muscles of his arm and hand to be stimulated in response to signals from his brain, decoded by computer. After eight years, he is able to drink and feed himself without assistance.

“I think about what I want to do and the system does it for me,” Kochevar told the Guardian. “It’s not a lot of thinking about it. When I want to do something, my brain does what it does.”

The experimental technology, pioneered by the Case Western Reserve University in Cleveland, Ohio, is the first in the world to restore brain-controlled reaching and grasping in a person with complete paralysis.

For now, the process is relatively slow, but the scientists behind the breakthrough say this is proof of concept and that they hope to streamline the technology until it becomes a routine treatment for people with paralysis. In the future, they say, it will also be wireless and the electrical arrays and sensors will all be implanted under the skin and invisible.

A March 28, 2017 Lancet news release on EurekAlert provides a little more technical insight into the research and Kochevar’s efforts,

Although only tested with one participant, the study is a major advance and the first to restore brain-controlled reaching and grasping in a person with complete paralysis. The technology, which is only for experimental use in the USA, circumvents rather than repairs spinal injuries, meaning the participant relies on the device being implanted and switched on to move.

“Our research is at an early stage, but we believe that this neuro-prosthesis could offer individuals with paralysis the possibility of regaining arm and hand functions to perform day-to-day activities, offering them greater independence,” said lead author Dr Bolu Ajiboye, Case Western Reserve University, USA. “So far it has helped a man with tetraplegia to reach and grasp, meaning he could feed himself and drink. With further development, we believe the technology could give more accurate control, allowing a wider range of actions, which could begin to transform the lives of people living with paralysis.” [1]

Previous research has used similar elements of the neuro-prosthesis. For example, a brain-computer interface linked to electrodes on the skin has helped a person with less severe paralysis open and close his hand, while other studies have allowed participants to control a robotic arm using their brain signals. However, this is the first to restore reaching and grasping via the system in a person with a chronic spinal cord injury.

In this study, a 53 year-old man who had been paralysed below the shoulders for eight years underwent surgery to have the neuro-prosthesis fitted.

This involved brain surgery to place sensors in the motor cortex area of his brain responsible for hand movement – creating a brain-computer interface that learnt which movements his brain signals were instructing for. This initial stage took four months and included training using a virtual reality arm.

He then underwent another procedure placing 36 muscle stimulating electrodes into his upper and lower arm, including four that helped restore finger and thumb, wrist, elbow and shoulder movements. These were switched on 17 days after the procedure, and began stimulating the muscles for eight hours a week over 18 weeks to improve strength, movement and reduce muscle fatigue.

The researchers then wired the brain-computer interface to the electrical stimulators in his arm, using a decoder (mathematical algorithm) to translate his brain signals into commands for the electrodes in his arm. The electrodes stimulated the muscles to produce contractions, helping the participant intuitively complete the movements he was thinking of. The system also involved an arm support to stop gravity simply pulling his arm down.

During his training, the participant described how he controlled the neuro-prosthesis: “It’s probably a good thing that I’m making it move without having to really concentrate hard at it. I just think ‘out’ and it just goes.”

After 12 months of having the neuro-prosthesis fitted, the participant was asked to complete day-to-day tasks, including drinking a cup of coffee and feeding himself. First of all, he observed while his arm completed the action under computer control. During this, he thought about making the same movement so that the system could recognise the corresponding brain signals. The two systems were then linked and he was able to use it to drink a coffee and feed himself.

He successfully drank in 11 out of 12 attempts, and it took him roughly 20-40 seconds to complete the task. When feeding himself, he did so multiple times – scooping forkfuls of food and navigating his hand to his mouth to take several bites.

“Although similar systems have been used before, none of them have been as easy to adopt for day-to-day use and they have not been able to restore both reaching and grasping actions,” said Dr Ajiboye. “Our system builds on muscle stimulating electrode technology that is already available and will continue to improve with the development of new fully implanted and wireless brain-computer interface systems. This could lead to enhanced performance of the neuro-prosthesis with better speed, precision and control.” [1]

At the time of the study, the participant had had the neuro-prosthesis implanted for almost two years (717 days) and in this time experienced four minor, non-serious adverse events which were treated and resolved.

Despite its achievements, the neuro-prosthesis still had some limitations, including that movements made using it were slower and less accurate than those made using the virtual reality arm the participant used for training. When using the technology, the participant also needed to watch his arm as he lost his sense of proprioception – the ability to intuitively sense the position and movement of limbs – as a result of the paralysis.

Writing in a linked Comment, Dr Steve Perlmutter, University of Washington, USA, said: “The goal is futuristic: a paralysed individual thinks about moving her arm as if her brain and muscles were not disconnected, and implanted technology seamlessly executes the desired movement… This study is groundbreaking as the first report of a person executing functional, multi-joint movements of a paralysed limb with a motor neuro-prosthesis. However, this treatment is not nearly ready for use outside the lab. The movements were rough and slow and required continuous visual feedback, as is the case for most available brain-machine interfaces, and had restricted range due to the use of a motorised device to assist shoulder movements… Thus, the study is a proof-of-principle demonstration of what is possible, rather than a fundamental advance in neuro-prosthetic concepts or technology. But it is an exciting demonstration nonetheless, and the future of motor neuro-prosthetics to overcome paralysis is brighter.”

[1] Quote direct from author and cannot be found in the text of the Article.

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

Restoration of reaching and grasping movements through brain-controlled muscle stimulation in a person with tetraplegia: a proof-of-concept demonstration by A Bolu Ajiboye, Francis R Willett, Daniel R Young, William D Memberg, Brian A Murphy, Jonathan P Miller, Benjamin L Walter, Jennifer A Sweet, Harry A Hoyen, Michael W Keith, Prof P Hunter Peckham, John D Simeral, Prof John P Donoghue, Prof Leigh R Hochberg, Prof Robert F Kirsch. The Lancet DOI: http://dx.doi.org/10.1016/S0140-6736(17)30601-3 Published: 28 March 2017 [online?]

This paper is behind a paywall.

For anyone  who’s interested, you can find the BrainGate website here.

*I initially misidentified the nature of the achievement and stated that Kochevar used a “robotic arm, which is attached to his body” when it was his own reanimated arm. Corrected on April 25, 2017.

Vector Institute and Canada’s artificial intelligence sector

On the heels of the March 22, 2017 federal budget announcement of $125M for a Pan-Canadian Artificial Intelligence Strategy, the University of Toronto (U of T) has announced the inception of the Vector Institute for Artificial Intelligence in a March 28, 2017 news release by Jennifer Robinson (Note: Links have been removed),

A team of globally renowned researchers at the University of Toronto is driving the planning of a new institute staking Toronto’s and Canada’s claim as the global leader in AI.

Geoffrey Hinton, a University Professor Emeritus in computer science at U of T and vice-president engineering fellow at Google, will serve as the chief scientific adviser of the newly created Vector Institute based in downtown Toronto.

“The University of Toronto has long been considered a global leader in artificial intelligence research,” said U of T President Meric Gertler. “It’s wonderful to see that expertise act as an anchor to bring together researchers, government and private sector actors through the Vector Institute, enabling them to aim even higher in leading advancements in this fast-growing, critical field.”

As part of the Government of Canada’s Pan-Canadian Artificial Intelligence Strategy, Vector will share $125 million in federal funding with fellow institutes in Montreal and Edmonton. All three will conduct research and secure talent to cement Canada’s position as a world leader in AI.

In addition, Vector is expected to receive funding from the Province of Ontario and more than 30 top Canadian and global companies eager to tap this pool of talent to grow their businesses. The institute will also work closely with other Ontario universities with AI talent.

(See my March 24, 2017 posting; scroll down about 25% for the science part, including the Pan-Canadian Artificial Intelligence Strategy of the budget.)

Not obvious in last week’s coverage of the Pan-Canadian Artificial Intelligence Strategy is that the much lauded Hinton has been living in the US and working for Google. These latest announcements (Pan-Canadian AI Strategy and Vector Institute) mean that he’s moving back.

A March 28, 2017 article by Kate Allen for TorontoStar.com provides more details about the Vector Institute, Hinton, and the Canadian ‘brain drain’ as it applies to artificial intelligence, (Note:  A link has been removed)

Toronto will host a new institute devoted to artificial intelligence, a major gambit to bolster a field of research pioneered in Canada but consistently drained of talent by major U.S. technology companies like Google, Facebook and Microsoft.

The Vector Institute, an independent non-profit affiliated with the University of Toronto, will hire about 25 new faculty and research scientists. It will be backed by more than $150 million in public and corporate funding in an unusual hybridization of pure research and business-minded commercial goals.

The province will spend $50 million over five years, while the federal government, which announced a $125-million Pan-Canadian Artificial Intelligence Strategy in last week’s budget, is providing at least $40 million, backers say. More than two dozen companies have committed millions more over 10 years, including $5 million each from sponsors including Google, Air Canada, Loblaws, and Canada’s five biggest banks [Bank of Montreal (BMO). Canadian Imperial Bank of Commerce ({CIBC} President’s Choice Financial},  Royal Bank of Canada (RBC), Scotiabank (Tangerine), Toronto-Dominion Bank (TD Canada Trust)].

The mode of artificial intelligence that the Vector Institute will focus on, deep learning, has seen remarkable results in recent years, particularly in image and speech recognition. Geoffrey Hinton, considered the “godfather” of deep learning for the breakthroughs he made while a professor at U of T, has worked for Google since 2013 in California and Toronto.

Hinton will move back to Canada to lead a research team based at the tech giant’s Toronto offices and act as chief scientific adviser of the new institute.

Researchers trained in Canadian artificial intelligence labs fill the ranks of major technology companies, working on tools like instant language translation, facial recognition, and recommendation services. Academic institutions and startups in Toronto, Waterloo, Montreal and Edmonton boast leaders in the field, but other researchers have left for U.S. universities and corporate labs.

The goals of the Vector Institute are to retain, repatriate and attract AI talent, to create more trained experts, and to feed that expertise into existing Canadian companies and startups.

Hospitals are expected to be a major partner, since health care is an intriguing application for AI. Last month, researchers from Stanford University announced they had trained a deep learning algorithm to identify potentially cancerous skin lesions with accuracy comparable to human dermatologists. The Toronto company Deep Genomics is using deep learning to read genomes and identify mutations that may lead to disease, among other things.

Intelligent algorithms can also be applied to tasks that might seem less virtuous, like reading private data to better target advertising. Zemel [Richard Zemel, the institute’s research director and a professor of computer science at U of T] says the centre is creating an ethics working group [emphasis mine] and maintaining ties with organizations that promote fairness and transparency in machine learning. As for privacy concerns, “that’s something we are well aware of. We don’t have a well-formed policy yet but we will fairly soon.”

The institute’s annual funding pales in comparison to the revenues of the American tech giants, which are measured in tens of billions. The risk the institute’s backers are taking is simply creating an even more robust machine learning PhD mill for the U.S.

“They obviously won’t all stay in Canada, but Toronto industry is very keen to get them,” Hinton said. “I think Trump might help there.” Two researchers on Hinton’s new Toronto-based team are Iranian, one of the countries targeted by U.S. President Donald Trump’s travel bans.

Ethics do seem to be a bit of an afterthought. Presumably the Vector Institute’s ‘ethics working group’ won’t include any regular folks. Is there any thought to what the rest of us think about these developments? As there will also be some collaboration with other proposed AI institutes including ones at the University of Montreal (Université de Montréal) and the University of Alberta (Kate McGillivray’s article coming up shortly mentions them), might the ethics group be centered in either Edmonton or Montreal? Interestingly, two Canadians (Timothy Caulfield at the University of Alberta and Eric Racine at Université de Montréa) testified at the US Commission for the Study of Bioethical Issues Feb. 10 – 11, 2014 meeting, the Brain research, ethics, and nanotechnology. Still speculating here but I imagine Caulfield and/or Racine could be persuaded to extend their expertise in ethics and the human brain to AI and its neural networks.

Getting back to the topic at hand the ‘AI sceneCanada’, Allen’s article is worth reading in its entirety if you have the time.

Kate McGillivray’s March 29, 2017 article for the Canadian Broadcasting Corporation’s (CBC) news online provides more details about the Canadian AI situation and the new strategies,

With artificial intelligence set to transform our world, a new institute is putting Toronto to the front of the line to lead the charge.

The Vector Institute for Artificial Intelligence, made possible by funding from the federal government revealed in the 2017 budget, will move into new digs in the MaRS Discovery District by the end of the year.

Vector’s funding comes partially from a $125 million investment announced in last Wednesday’s federal budget to launch a pan-Canadian artificial intelligence strategy, with similar institutes being established in Montreal and Edmonton.

“[A.I.] cuts across pretty well every sector of the economy,” said Dr. Alan Bernstein, CEO and president of the Canadian Institute for Advanced Research, the organization tasked with administering the federal program.

“Silicon Valley and England and other places really jumped on it, so we kind of lost the lead a little bit. I think the Canadian federal government has now realized that,” he said.

Stopping up the brain drain

Critical to the strategy’s success is building a homegrown base of A.I. experts and innovators — a problem in the last decade, despite pioneering work on so-called “Deep Learning” by Canadian scholars such as Yoshua Bengio and Geoffrey Hinton, a former University of Toronto professor who will now serve as Vector’s chief scientific advisor.

With few university faculty positions in Canada and with many innovative companies headquartered elsewhere, it has been tough to keep the few graduates specializing in A.I. in town.

“We were paying to educate people and shipping them south,” explained Ed Clark, chair of the Vector Institute and business advisor to Ontario Premier Kathleen Wynne.

The existence of that “fantastic science” will lean heavily on how much buy-in Vector and Canada’s other two A.I. centres get.

Toronto’s portion of the $125 million is a “great start,” said Bernstein, but taken alone, “it’s not enough money.”

“My estimate of the right amount of money to make a difference is a half a billion or so, and I think we will get there,” he said.

Jessica Murphy’s March 29, 2017 article for the British Broadcasting Corporation’s (BBC) news online offers some intriguing detail about the Canadian AI scene,

Canadian researchers have been behind some recent major breakthroughs in artificial intelligence. Now, the country is betting on becoming a big player in one of the hottest fields in technology, with help from the likes of Google and RBC [Royal Bank of Canada].

In an unassuming building on the University of Toronto’s downtown campus, Geoff Hinton laboured for years on the “lunatic fringe” of academia and artificial intelligence, pursuing research in an area of AI called neural networks.

Also known as “deep learning”, neural networks are computer programs that learn in similar way to human brains. The field showed early promise in the 1980s, but the tech sector turned its attention to other AI methods after that promise seemed slow to develop.

“The approaches that I thought were silly were in the ascendancy and the approach that I thought was the right approach was regarded as silly,” says the British-born [emphasis mine] professor, who splits his time between the university and Google, where he is a vice-president of engineering fellow.

Neural networks are used by the likes of Netflix to recommend what you should binge watch and smartphones with voice assistance tools. Google DeepMind’s AlphaGo AI used them to win against a human in the ancient game of Go in 2016.

Foteini Agrafioti, who heads up the new RBC Research in Machine Learning lab at the University of Toronto, said those recent innovations made AI attractive to researchers and the tech industry.

“Anything that’s powering Google’s engines right now is powered by deep learning,” she says.

Developments in the field helped jumpstart innovation and paved the way for the technology’s commercialisation. They also captured the attention of Google, IBM and Microsoft, and kicked off a hiring race in the field.

The renewed focus on neural networks has boosted the careers of early Canadian AI machine learning pioneers like Hinton, the University of Montreal’s Yoshua Bengio, and University of Alberta’s Richard Sutton.

Money from big tech is coming north, along with investments by domestic corporations like banking multinational RBC and auto parts giant Magna, and millions of dollars in government funding.

Former banking executive Ed Clark will head the institute, and says the goal is to make Toronto, which has the largest concentration of AI-related industries in Canada, one of the top five places in the world for AI innovation and business.

The founders also want it to serve as a magnet and retention tool for top talent aggressively head-hunted by US firms.

Clark says they want to “wake up” Canadian industry to the possibilities of AI, which is expected to have a massive impact on fields like healthcare, banking, manufacturing and transportation.

Google invested C$4.5m (US$3.4m/£2.7m) last November [2016] in the University of Montreal’s Montreal Institute for Learning Algorithms.

Microsoft is funding a Montreal startup, Element AI. The Seattle-based company also announced it would acquire Montreal-based Maluuba and help fund AI research at the University of Montreal and McGill University.

Thomson Reuters and General Motors both recently moved AI labs to Toronto.

RBC is also investing in the future of AI in Canada, including opening a machine learning lab headed by Agrafioti, co-funding a program to bring global AI talent and entrepreneurs to Toronto, and collaborating with Sutton and the University of Alberta’s Machine Intelligence Institute.

Canadian tech also sees the travel uncertainty created by the Trump administration in the US as making Canada more attractive to foreign talent. (One of Clark’s the selling points is that Toronto as an “open and diverse” city).

This may reverse the ‘brain drain’ but it appears Canada’s role as a ‘branch plant economy’ for foreign (usually US) companies could become an important discussion once more. From the ‘Foreign ownership of companies of Canada’ Wikipedia entry (Note: Links have been removed),

Historically, foreign ownership was a political issue in Canada in the late 1960s and early 1970s, when it was believed by some that U.S. investment had reached new heights (though its levels had actually remained stable for decades), and then in the 1980s, during debates over the Free Trade Agreement.

But the situation has changed, since in the interim period Canada itself became a major investor and owner of foreign corporations. Since the 1980s, Canada’s levels of investment and ownership in foreign companies have been larger than foreign investment and ownership in Canada. In some smaller countries, such as Montenegro, Canadian investment is sizable enough to make up a major portion of the economy. In Northern Ireland, for example, Canada is the largest foreign investor. By becoming foreign owners themselves, Canadians have become far less politically concerned about investment within Canada.

Of note is that Canada’s largest companies by value, and largest employers, tend to be foreign-owned in a way that is more typical of a developing nation than a G8 member. The best example is the automotive sector, one of Canada’s most important industries. It is dominated by American, German, and Japanese giants. Although this situation is not unique to Canada in the global context, it is unique among G-8 nations, and many other relatively small nations also have national automotive companies.

It’s interesting to note that sometimes Canadian companies are the big investors but that doesn’t change our basic position. And, as I’ve noted in other postings (including the March 24, 2017 posting), these government investments in science and technology won’t necessarily lead to a move away from our ‘branch plant economy’ towards an innovative Canada.

You can find out more about the Vector Institute for Artificial Intelligence here.

BTW, I noted that reference to Hinton as ‘British-born’ in the BBC article. He was educated in the UK and subsidized by UK taxpayers (from his Wikipedia entry; Note: Links have been removed),

Hinton was educated at King’s College, Cambridge graduating in 1970, with a Bachelor of Arts in experimental psychology.[1] He continued his study at the University of Edinburgh where he was awarded a PhD in artificial intelligence in 1977 for research supervised by H. Christopher Longuet-Higgins.[3][12]

It seems Canadians are not the only ones to experience  ‘brain drains’.

Finally, I wrote at length about a recent initiative taking place between the University of British Columbia (Vancouver, Canada) and the University of Washington (Seattle, Washington), the Cascadia Urban Analytics Cooperative in a Feb. 28, 2017 posting noting that the initiative is being funded by Microsoft to the tune $1M and is part of a larger cooperative effort between the province of British Columbia and the state of Washington. Artificial intelligence is not the only area where US technology companies are hedging their bets (against Trump’s administration which seems determined to terrify people from crossing US borders) by investing in Canada.

For anyone interested in a little more information about AI in the US and China, there’s today’s (March 31, 2017)earlier posting: China, US, and the race for artificial intelligence research domination.

The Canadian science scene and the 2017 Canadian federal budget

There’s not much happening in the 2017-18 budget in terms of new spending according to Paul Wells’ March 22, 2017 article for TheStar.com,

This is the 22nd or 23rd federal budget I’ve covered. And I’ve never seen the like of the one Bill Morneau introduced on Wednesday [March 22, 2017].

Not even in the last days of the Harper Conservatives did a budget provide for so little new spending — $1.3 billion in the current budget year, total, in all fields of government. That’s a little less than half of one per cent of all federal program spending for this year.

But times are tight. The future is a place where we can dream. So the dollars flow more freely in later years. In 2021-22, the budget’s fifth planning year, new spending peaks at $8.2 billion. Which will be about 2.4 per cent of all program spending.

He’s not alone in this 2017 federal budget analysis; CBC (Canadian Broadcasting Corporation) pundits, Chantal Hébert, Andrew Coyne, and Jennifer Ditchburn said much the same during their ‘At Issue’ segment of the March 22, 2017 broadcast of The National (news).

Before I focus on the science and technology budget, here are some general highlights from the CBC’s March 22, 2017 article on the 2017-18 budget announcement (Note: Links have been removed,

Here are highlights from the 2017 federal budget:

  • Deficit: $28.5 billion, up from $25.4 billion projected in the fall.
  • Trend: Deficits gradually decline over next five years — but still at $18.8 billion in 2021-22.
  • Housing: $11.2 billion over 11 years, already budgeted, will go to a national housing strategy.
  • Child care: $7 billion over 10 years, already budgeted, for new spaces, starting 2018-19.
  • Indigenous: $3.4 billion in new money over five years for infrastructure, health and education.
  • Defence: $8.4 billion in capital spending for equipment pushed forward to 2035.
  • Care givers: New care-giving benefit up to 15 weeks, starting next year.
  • Skills: New agency to research and measure skills development, starting 2018-19.
  • Innovation: $950 million over five years to support business-led “superclusters.”
  • Startups: $400 million over three years for a new venture capital catalyst initiative.
  • AI: $125 million to launch a pan-Canadian Artificial Intelligence Strategy.
  • Coding kids: $50 million over two years for initiatives to teach children to code.
  • Families: Option to extend parental leave up to 18 months.
  • Uber tax: GST to be collected on ride-sharing services.
  • Sin taxes: One cent more on a bottle of wine, five cents on 24 case of beer.
  • Bye-bye: No more Canada Savings Bonds.
  • Transit credit killed: 15 per cent non-refundable public transit tax credit phased out this year.

You can find the entire 2017-18 budget here.

Science and the 2017-18 budget

For anyone interested in the science news, you’ll find most of that in the 2017 budget’s Chapter 1 — Skills, Innovation and Middle Class jobs. As well, Wayne Kondro has written up a précis in his March 22, 2017 article for Science (magazine),

Finance officials, who speak on condition of anonymity during the budget lock-up, indicated the budgets of the granting councils, the main source of operational grants for university researchers, will be “static” until the government can assess recommendations that emerge from an expert panel formed in 2015 and headed by former University of Toronto President David Naylor to review basic science in Canada [highlighted in my June 15, 2016 posting ; $2M has been allocated for the advisor and associated secretariat]. Until then, the officials said, funding for the Natural Sciences and Engineering Research Council of Canada (NSERC) will remain at roughly $848 million, whereas that for the Canadian Institutes of Health Research (CIHR) will remain at $773 million, and for the Social Sciences and Humanities Research Council [SSHRC] at $547 million.

NSERC, though, will receive $8.1 million over 5 years to administer a PromoScience Program that introduces youth, particularly unrepresented groups like Aboriginal people and women, to science, technology, engineering, and mathematics through measures like “space camps and conservation projects.” CIHR, meanwhile, could receive modest amounts from separate plans to identify climate change health risks and to reduce drug and substance abuse, the officials added.

… Canada’s Innovation and Skills Plan, would funnel $600 million over 5 years allocated in 2016, and $112.5 million slated for public transit and green infrastructure, to create Silicon Valley–like “super clusters,” which the budget defined as “dense areas of business activity that contain large and small companies, post-secondary institutions and specialized talent and infrastructure.” …

… The Canadian Institute for Advanced Research will receive $93.7 million [emphasis mine] to “launch a Pan-Canadian Artificial Intelligence Strategy … (to) position Canada as a world-leading destination for companies seeking to invest in artificial intelligence and innovation.”

… Among more specific measures are vows to: Use $87.7 million in previous allocations to the Canada Research Chairs program to create 25 “Canada 150 Research Chairs” honoring the nation’s 150th year of existence, provide $1.5 million per year to support the operations of the office of the as-yet-unappointed national science adviser [see my Dec. 7, 2016 post for information about the job posting, which is now closed]; provide $165.7 million [emphasis mine] over 5 years for the nonprofit organization Mitacs to create roughly 6300 more co-op positions for university students and grads, and provide $60.7 million over five years for new Canadian Space Agency projects, particularly for Canadian participation in the National Aeronautics and Space Administration’s next Mars Orbiter Mission.

Kondros was either reading an earlier version of the budget or made an error regarding Mitacs (from the budget in the “A New, Ambitious Approach to Work-Integrated Learning” subsection),

Mitacs has set an ambitious goal of providing 10,000 work-integrated learning placements for Canadian post-secondary students and graduates each year—up from the current level of around 3,750 placements. Budget 2017 proposes to provide $221 million [emphasis mine] over five years, starting in 2017–18, to achieve this goal and provide relevant work experience to Canadian students.

As well, the budget item for the Pan-Canadian Artificial Intelligence Strategy is $125M.

Moving from Kondros’ précis, the budget (in the “Positioning National Research Council Canada Within the Innovation and Skills Plan” subsection) announces support for these specific areas of science,

Stem Cell Research

The Stem Cell Network, established in 2001, is a national not-for-profit organization that helps translate stem cell research into clinical applications, commercial products and public policy. Its research holds great promise, offering the potential for new therapies and medical treatments for respiratory and heart diseases, cancer, diabetes, spinal cord injury, multiple sclerosis, Crohn’s disease, auto-immune disorders and Parkinson’s disease. To support this important work, Budget 2017 proposes to provide the Stem Cell Network with renewed funding of $6 million in 2018–19.

Space Exploration

Canada has a long and proud history as a space-faring nation. As our international partners prepare to chart new missions, Budget 2017 proposes investments that will underscore Canada’s commitment to innovation and leadership in space. Budget 2017 proposes to provide $80.9 million on a cash basis over five years, starting in 2017–18, for new projects through the Canadian Space Agency that will demonstrate and utilize Canadian innovations in space, including in the field of quantum technology as well as for Mars surface observation. The latter project will enable Canada to join the National Aeronautics and Space Administration’s (NASA’s) next Mars Orbiter Mission.

Quantum Information

The development of new quantum technologies has the potential to transform markets, create new industries and produce leading-edge jobs. The Institute for Quantum Computing is a world-leading Canadian research facility that furthers our understanding of these innovative technologies. Budget 2017 proposes to provide the Institute with renewed funding of $10 million over two years, starting in 2017–18.

Social Innovation

Through community-college partnerships, the Community and College Social Innovation Fund fosters positive social outcomes, such as the integration of vulnerable populations into Canadian communities. Following the success of this pilot program, Budget 2017 proposes to invest $10 million over two years, starting in 2017–18, to continue this work.

International Research Collaborations

The Canadian Institute for Advanced Research (CIFAR) connects Canadian researchers with collaborative research networks led by eminent Canadian and international researchers on topics that touch all humanity. Past collaborations facilitated by CIFAR are credited with fostering Canada’s leadership in artificial intelligence and deep learning. Budget 2017 proposes to provide renewed and enhanced funding of $35 million over five years, starting in 2017–18.

Earlier this week, I highlighted Canada’s strength in the field of regenerative medicine, specifically stem cells in a March 21, 2017 posting. The $6M in the current budget doesn’t look like increased funding but rather a one-year extension. I’m sure they’re happy to receive it  but I imagine it’s a little hard to plan major research projects when you’re not sure how long your funding will last.

As for Canadian leadership in artificial intelligence, that was news to me. Here’s more from the budget,

Canada a Pioneer in Deep Learning in Machines and Brains

CIFAR’s Learning in Machines & Brains program has shaken up the field of artificial intelligence by pioneering a technique called “deep learning,” a computer technique inspired by the human brain and neural networks, which is now routinely used by the likes of Google and Facebook. The program brings together computer scientists, biologists, neuroscientists, psychologists and others, and the result is rich collaborations that have propelled artificial intelligence research forward. The program is co-directed by one of Canada’s foremost experts in artificial intelligence, the Université de Montréal’s Yoshua Bengio, and for his many contributions to the program, the University of Toronto’s Geoffrey Hinton, another Canadian leader in this field, was awarded the title of Distinguished Fellow by CIFAR in 2014.

Meanwhile, from chapter 1 of the budget in the subsection titled “Preparing for the Digital Economy,” there is this provision for children,

Providing educational opportunities for digital skills development to Canadian girls and boys—from kindergarten to grade 12—will give them the head start they need to find and keep good, well-paying, in-demand jobs. To help provide coding and digital skills education to more young Canadians, the Government intends to launch a competitive process through which digital skills training organizations can apply for funding. Budget 2017 proposes to provide $50 million over two years, starting in 2017–18, to support these teaching initiatives.

I wonder if BC Premier Christy Clark is heaving a sigh of relief. At the 2016 #BCTECH Summit, she announced that students in BC would learn to code at school and in newly enhanced coding camp programmes (see my Jan. 19, 2016 posting). Interestingly, there was no mention of additional funding to support her initiative. I guess this money from the federal government comes at a good time as we will have a provincial election later this spring where she can announce the initiative again and, this time, mention there’s money for it.

Attracting brains from afar

Ivan Semeniuk in his March 23, 2017 article (for the Globe and Mail) reads between the lines to analyze the budget’s possible impact on Canadian science,

But a between-the-lines reading of the budget document suggests the government also has another audience in mind: uneasy scientists from the United States and Britain.

The federal government showed its hand at the 2017 #BCTECH Summit. From a March 16, 2017 article by Meera Bains for the CBC news online,

At the B.C. tech summit, Navdeep Bains, Canada’s minister of innovation, said the government will act quickly to fast track work permits to attract highly skilled talent from other countries.

“We’re taking the processing time, which takes months, and reducing it to two weeks for immigration processing for individuals [who] need to come here to help companies grow and scale up,” Bains said.

“So this is a big deal. It’s a game changer.”

That change will happen through the Global Talent Stream, a new program under the federal government’s temporary foreign worker program.  It’s scheduled to begin on June 12, 2017.

U.S. companies are taking notice and a Canadian firm, True North, is offering to help them set up shop.

“What we suggest is that they think about moving their operations, or at least a chunk of their operations, to Vancouver, set up a Canadian subsidiary,” said the company’s founder, Michael Tippett.

“And that subsidiary would be able to house and accommodate those employees.”

Industry experts says while the future is unclear for the tech sector in the U.S., it’s clear high tech in B.C. is gearing up to take advantage.

US business attempts to take advantage of Canada’s relative stability and openness to immigration would seem to be the motive for at least one cross border initiative, the Cascadia Urban Analytics Cooperative. From my Feb. 28, 2017 posting,

There was some big news about the smallest version of the Cascadia region on Thursday, Feb. 23, 2017 when the University of British Columbia (UBC) , the University of Washington (state; UW), and Microsoft announced the launch of the Cascadia Urban Analytics Cooperative. From the joint Feb. 23, 2017 news release (read on the UBC website or read on the UW website),

In an expansion of regional cooperation, the University of British Columbia and the University of Washington today announced the establishment of the Cascadia Urban Analytics Cooperative to use data to help cities and communities address challenges from traffic to homelessness. The largest industry-funded research partnership between UBC and the UW, the collaborative will bring faculty, students and community stakeholders together to solve problems, and is made possible thanks to a $1-million gift from Microsoft.

Today’s announcement follows last September’s [2016] Emerging Cascadia Innovation Corridor Conference in Vancouver, B.C. The forum brought together regional leaders for the first time to identify concrete opportunities for partnerships in education, transportation, university research, human capital and other areas.

A Boston Consulting Group study unveiled at the conference showed the region between Seattle and Vancouver has “high potential to cultivate an innovation corridor” that competes on an international scale, but only if regional leaders work together. The study says that could be possible through sustained collaboration aided by an educated and skilled workforce, a vibrant network of research universities and a dynamic policy environment.

It gets better, it seems Microsoft has been positioning itself for a while if Matt Day’s analysis is correct (from my Feb. 28, 2017 posting),

Matt Day in a Feb. 23, 2017 article for the The Seattle Times provides additional perspective (Note: Links have been removed),

Microsoft’s effort to nudge Seattle and Vancouver, B.C., a bit closer together got an endorsement Thursday [Feb. 23, 2017] from the leading university in each city.

The partnership has its roots in a September [2016] conference in Vancouver organized by Microsoft’s public affairs and lobbying unit [emphasis mine.] That gathering was aimed at tying business, government and educational institutions in Microsoft’s home region in the Seattle area closer to its Canadian neighbor.

Microsoft last year [2016] opened an expanded office in downtown Vancouver with space for 750 employees, an outpost partly designed to draw to the Northwest more engineers than the company can get through the U.S. guest worker system [emphasis mine].

This was all prior to President Trump’s legislative moves in the US, which have at least one Canadian observer a little more gleeful than I’m comfortable with. From a March 21, 2017 article by Susan Lum  for CBC News online,

U.S. President Donald Trump’s efforts to limit travel into his country while simultaneously cutting money from science-based programs provides an opportunity for Canada’s science sector, says a leading Canadian researcher.

“This is Canada’s moment. I think it’s a time we should be bold,” said Alan Bernstein, president of CIFAR [which on March 22, 2017 was awarded $125M to launch the Pan Canada Artificial Intelligence Strategy in the Canadian federal budget announcement], a global research network that funds hundreds of scientists in 16 countries.

Bernstein believes there are many reasons why Canada has become increasingly attractive to scientists around the world, including the political climate in the United States and the Trump administration’s travel bans.

Thankfully, Bernstein calms down a bit,

“It used to be if you were a bright young person anywhere in the world, you would want to go to Harvard or Berkeley or Stanford, or what have you. Now I think you should give pause to that,” he said. “We have pretty good universities here [emphasis mine]. We speak English. We’re a welcoming society for immigrants.”​

Bernstein cautions that Canada should not be seen to be poaching scientists from the United States — but there is an opportunity.

“It’s as if we’ve been in a choir of an opera in the back of the stage and all of a sudden the stars all left the stage. And the audience is expecting us to sing an aria. So we should sing,” Bernstein said.

Bernstein said the federal government, with this week’s so-called innovation budget, can help Canada hit the right notes.

“Innovation is built on fundamental science, so I’m looking to see if the government is willing to support, in a big way, fundamental science in the country.”

Pretty good universities, eh? Thank you, Dr. Bernstein, for keeping some of the boosterism in check. Let’s leave the chest thumping to President Trump and his cronies.

Ivan Semeniuk’s March 23, 2017 article (for the Globe and Mail) provides more details about the situation in the US and in Britain,

Last week, Donald Trump’s first budget request made clear the U.S. President would significantly reduce or entirely eliminate research funding in areas such as climate science and renewable energy if permitted by Congress. Even the National Institutes of Health, which spearheads medical research in the United States and is historically supported across party lines, was unexpectedly targeted for a $6-billion (U.S.) cut that the White House said could be achieved through “efficiencies.”

In Britain, a recent survey found that 42 per cent of academics were considering leaving the country over worries about a less welcoming environment and the loss of research money that a split with the European Union is expected to bring.

In contrast, Canada’s upbeat language about science in the budget makes a not-so-subtle pitch for diversity and talent from abroad, including $117.6-million to establish 25 research chairs with the aim of attracting “top-tier international scholars.”

For good measure, the budget also includes funding for science promotion and $2-million annually for Canada’s yet-to-be-hired Chief Science Advisor, whose duties will include ensuring that government researchers can speak freely about their work.

“What we’ve been hearing over the last few months is that Canada is seen as a beacon, for its openness and for its commitment to science,” said Ms. Duncan [Kirsty Duncan, Minister of Science], who did not refer directly to either the United States or Britain in her comments.

Providing a less optimistic note, Erica Alini in her March 22, 2017 online article for Global News mentions a perennial problem, the Canadian brain drain,

The budget includes a slew of proposed reforms and boosted funding for existing training programs, as well as new skills-development resources for unemployed and underemployed Canadians not covered under current EI-funded programs.

There are initiatives to help women and indigenous people get degrees or training in science, technology, engineering and mathematics (the so-called STEM subjects) and even to teach kids as young as kindergarten-age to code.

But there was no mention of how to make sure Canadians with the right skills remain in Canada, TD’s DePratto {Toronto Dominion Bank} Economics; TD is currently experiencing a scandal {March 13, 2017 Huffington Post news item}] told Global News.

Canada ranks in the middle of the pack compared to other advanced economies when it comes to its share of its graduates in STEM fields, but the U.S. doesn’t shine either, said DePratto [Brian DePratto, senior economist at TD .

The key difference between Canada and the U.S. is the ability to retain domestic talent and attract brains from all over the world, he noted.

To be blunt, there may be some opportunities for Canadian science but it does well to remember (a) US businesses have no particular loyalty to Canada and (b) all it takes is an election to change any perceived advantages to disadvantages.

Digital policy and intellectual property issues

Dubbed by some as the ‘innovation’ budget (official title:  Building a Strong Middle Class), there is an attempt to address a longstanding innovation issue (from a March 22, 2017 posting by Michael Geist on his eponymous blog (Note: Links have been removed),

The release of today’s [march 22, 2017] federal budget is expected to include a significant emphasis on innovation, with the government revealing how it plans to spend (or re-allocate) hundreds of millions of dollars that is intended to support innovation. Canada’s dismal innovation record needs attention, but spending our way to a more innovative economy is unlikely to yield the desired results. While Navdeep Bains, the Innovation, Science and Economic Development Minister, has talked for months about the importance of innovation, Toronto Star columnist Paul Wells today delivers a cutting but accurate assessment of those efforts:

“This government is the first with a minister for innovation! He’s Navdeep Bains. He frequently posts photos of his meetings on Twitter, with the hashtag “#innovation.” That’s how you know there is innovation going on. A year and a half after he became the minister for #innovation, it’s not clear what Bains’s plans are. It’s pretty clear that within the government he has less than complete control over #innovation. There’s an advisory council on economic growth, chaired by the McKinsey guru Dominic Barton, which periodically reports to the government urging more #innovation.

There’s a science advisory panel, chaired by former University of Toronto president David Naylor, that delivered a report to Science Minister Kirsty Duncan more than three months ago. That report has vanished. One presumes that’s because it offered some advice. Whatever Bains proposes, it will have company.”

Wells is right. Bains has been very visible with plenty of meetings and public photo shoots but no obvious innovation policy direction. This represents a missed opportunity since Bains has plenty of policy tools at his disposal that could advance Canada’s innovation framework without focusing on government spending.

For example, Canada’s communications system – wireless and broadband Internet access – falls directly within his portfolio and is crucial for both business and consumers. Yet Bains has been largely missing in action on the file. He gave approval for the Bell – MTS merger that virtually everyone concedes will increase prices in the province and make the communications market less competitive. There are potential policy measures that could bring new competitors into the market (MVNOs [mobile virtual network operators] and municipal broadband) and that could make it easier for consumers to switch providers (ban on unlocking devices). Some of this falls to the CRTC, but government direction and emphasis would make a difference.

Even more troubling has been his near total invisibility on issues relating to new fees or taxes on Internet access and digital services. Canadian Heritage Minister Mélanie Joly has taken control of the issue with the possibility that Canadians could face increased costs for their Internet access or digital services through mandatory fees to contribute to Canadian content.  Leaving aside the policy objections to such an approach (reducing affordable access and the fact that foreign sources now contribute more toward Canadian English language TV production than Canadian broadcasters and distributors), Internet access and e-commerce are supposed to be Bains’ issue and they have a direct connection to the innovation file. How is it possible for the Innovation, Science and Economic Development Minister to have remained silent for months on the issue?

Bains has been largely missing on trade related innovation issues as well. My Globe and Mail column today focuses on a digital-era NAFTA, pointing to likely U.S. demands on data localization, data transfers, e-commerce rules, and net neutrality.  These are all issues that fall under Bains’ portfolio and will impact investment in Canadian networks and digital services. There are innovation opportunities for Canada here, but Bains has been content to leave the policy issues to others, who will be willing to sacrifice potential gains in those areas.

Intellectual property policy is yet another area that falls directly under Bains’ mandate with an obvious link to innovation, but he has done little on the file. Canada won a huge NAFTA victory late last week involving the Canadian patent system, which was challenged by pharmaceutical giant Eli Lilly. Why has Bains not promoted the decision as an affirmation of how Canada’s intellectual property rules?

On the copyright front, the government is scheduled to conduct a review of the Copyright Act later this year, but it is not clear whether Bains will take the lead or again cede responsibility to Joly. The Copyright Act is statutorily under the Industry Minister and reform offers the chance to kickstart innovation. …

For anyone who’s not familiar with this area, innovation is often code for commercialization of science and technology research efforts. These days, digital service and access policies and intellectual property policies are all key to research and innovation efforts.

The country that’s most often (except in mainstream Canadian news media) held up as an example of leadership in innovation is Estonia. The Economist profiled the country in a July 31, 2013 article and a July 7, 2016 article on apolitical.co provides and update.

Conclusions

Science monies for the tri-council science funding agencies (NSERC, SSHRC, and CIHR) are more or less flat but there were a number of line items in the federal budget which qualify as science funding. The $221M over five years for Mitacs, the $125M for the Pan-Canadian Artificial Intelligence Strategy, additional funding for the Canada research chairs, and some of the digital funding could also be included as part of the overall haul. This is in line with the former government’s (Stephen Harper’s Conservatives) penchant for keeping the tri-council’s budgets under control while spreading largesse elsewhere (notably the Perimeter Institute, TRIUMF [Canada’s National Laboratory for Particle and Nuclear Physics], and, in the 2015 budget, $243.5-million towards the Thirty Metre Telescope (TMT) — a massive astronomical observatory to be constructed on the summit of Mauna Kea, Hawaii, a $1.5-billion project). This has lead to some hard feelings in the past with regard to ‘big science’ projects getting what some have felt is an undeserved boost in finances while the ‘small fish’ are left scrabbling for the ever-diminishing (due to budget cuts in years past and inflation) pittances available from the tri-council agencies.

Mitacs, which started life as a federally funded Network Centre for Excellence focused on mathematics, has since shifted focus to become an innovation ‘champion’. You can find Mitacs here and you can find the organization’s March 2016 budget submission to the House of Commons Standing Committee on Finance here. At the time, they did not request a specific amount of money; they just asked for more.

The amount Mitacs expects to receive this year is over $40M which represents more than double what they received from the federal government and almost of 1/2 of their total income in the 2015-16 fiscal year according to their 2015-16 annual report (see p. 327 for the Mitacs Statement of Operations to March 31, 2016). In fact, the federal government forked over $39,900,189. in the 2015-16 fiscal year to be their largest supporter while Mitacs’ total income (receipts) was $81,993,390.

It’s a strange thing but too much money, etc. can be as bad as too little. I wish the folks Mitacs nothing but good luck with their windfall.

I don’t see anything in the budget that encourages innovation and investment from the industrial sector in Canada.

Finallyl, innovation is a cultural issue as much as it is a financial issue and having worked with a number of developers and start-up companies, the most popular business model is to develop a successful business that will be acquired by a large enterprise thereby allowing the entrepreneurs to retire before the age of 30 (or 40 at the latest). I don’t see anything from the government acknowledging the problem let alone any attempts to tackle it.

All in all, it was a decent budget with nothing in it to seriously offend anyone.

Singing posters and talking shirts can communicate with you via car radio or smartphones

Singing posters and talking shirts haven’t gone beyond the prototype stage yet but I imagine University of Washington engineers are hoping this will happen sooner rather than later. In the meantime, they are  presenting their work at a conference according to a March 1, 2017 news item on ScienceDaily,

Imagine you’re waiting in your car and a poster for a concert from a local band catches your eye. What if you could just tune your car to a radio station and actually listen to that band’s music? Or perhaps you see the poster on the side of a bus stop. What if it could send your smartphone a link for discounted tickets or give you directions to the venue?

Going further, imagine you go for a run, and your shirt can sense your perspiration and send data on your vital signs directly to your phone.

A new technique pioneered by University of Washington engineers makes these “smart” posters and clothing a reality by allowing them to communicate directly with your car’s radio or your smartphone. For instance, bus stop billboards could send digital content about local attractions. A street sign could broadcast the name of an intersection or notice that it is safe to cross a street, improving accessibility for the disabled. In addition, clothing with integrated sensors could monitor vital signs and send them to a phone. [emphasis mine]

“What we want to do is enable smart cities and fabrics where everyday objects in outdoor environments — whether it’s posters or street signs or even the shirt you’re wearing — can ‘talk’ to you by sending information to your phone or car,” said lead faculty and UW assistant professor of computer science and engineering Shyam Gollakota.

“The challenge is that radio technologies like WiFi, Bluetooth and conventional FM radios would last less than half a day with a coin cell battery when transmitting,” said co-author and UW electrical engineering doctoral student Vikram Iyer. “So we developed a new way of communication where we send information by reflecting ambient FM radio signals that are already in the air, which consumes close to zero power.”

The UW team has — for the first time — demonstrated how to apply a technique called “backscattering” to outdoor FM radio signals. The new system transmits messages by reflecting and encoding audio and data in these signals that are ubiquitous in urban environments, without affecting the original radio transmissions. Results are published in a paper to be presented in Boston at the 14th USENIX Symposium on Networked Systems Design and Implementation in March [2017].

The team demonstrated that a “singing poster” for the band Simply Three placed at a bus stop could transmit a snippet of the band’s music, as well as an advertisement for the band, to a smartphone at a distance of 12 feet or to a car over 60 feet away. They overlaid the audio and data on top of ambient news signals from a local NPR radio station.

The University of Washington has produced a video demonstration of the technology

A March 1, 2017 University of Washington news release (also on EurekAlert), which originated the news item, explains further (Note: Links have been removed),

“FM radio signals are everywhere. You can listen to music or news in your car and it’s a common way for us to get our information,” said co-author and UW computer science and engineering doctoral student Anran Wang. “So what we do is basically make each of these everyday objects into a mini FM radio station at almost zero power.”

Such ubiquitous low-power connectivity can also enable smart fabric applications such as clothing integrated with sensors to monitor a runner’s gait and vital signs that transmits the information directly to a user’s phone. In a second demonstration, the researchers from the UW Networks & Mobile Systems Lab used conductive thread to sew an antenna into a cotton T-shirt, which was able to use ambient radio signals to transmit data to a smartphone at rates up to 3.2 kilobits per second.

The system works by taking an everyday FM radio signal broadcast from an urban radio tower. The “smart” poster or T-shirt uses a low-power reflector to manipulate the signal in a way that encodes the desired audio or data on top of the FM broadcast to send a “message” to the smartphone receiver on an unoccupied frequency in the FM radio band.

“Our system doesn’t disturb existing FM radio frequencies,” said co-author Joshua Smith, UW associate professor of computer science and engineering and of electrical engineering. “We send our messages on an adjacent band that no one is using — so we can piggyback on your favorite news or music channel without disturbing the original transmission.”

The team demonstrated three different methods for sending audio signals and data using FM backscatter: one simply overlays the new information on top of the existing signals, another takes advantage of unused portions of a stereo FM broadcast, and the third uses cooperation between two smartphones to decode the message.

“Because of the unique structure of FM radio signals, multiplying the original signal with the backscattered signal actually produces an additive frequency change,” said co-author Vamsi Talla, a UW postdoctoral researcher in computer science and engineering. “These frequency changes can be decoded as audio on the normal FM receivers built into cars and smartphones.”

In the team’s demonstrations, the total power consumption of the backscatter system was 11 microwatts, which could be easily supplied by a tiny coin-cell battery for a couple of years, or powered using tiny solar cells.

I cannot help but notice the interest in using this technology is for monitoring purposes, which could be benign or otherwise.

For anyone curious about the 14th USENIX Symposium on Networked Systems Design and Implementation being held March 27 – 29, 2017 in Boston, Massachusetts, you can find out more here.

Big data in the Cascadia region: a University of British Columbia (Canada) and University of Washington (US state) collaboration

Before moving onto the news and for anyone unfamiliar with the concept of the Cascadia region, it is an informally proposed political region or a bioregion, depending on your perspective. Adding to the lack of clarity, the region generally includes the province of British Columbia in Canada and the two US states, Washington and Oregon but Alaska (another US state) and the Yukon (a Canadian territory) may also be included, as well as, parts of California, Wyoming, Idaho, and Montana. (You can read more about the Cascadia bioregion here and the proposed political region here.)  While it sounds as if more of the US is part of the ‘Cascadia region’, British Columbia and the Yukon cover considerably more territory than all of the mentioned states combined, if you’re taking a landmass perspective.

Cascadia Urban Analytics Cooperative

There was some big news about the smallest version of the Cascadia region on Thursday, Feb. 23, 2017 when the University of British Columbia (UBC) , the University of Washington (state; UW), and Microsoft announced the launch of the Cascadia Urban Analytics Cooperative. From the joint Feb. 23, 2017 news release (read on the UBC website or read on the UW website),

In an expansion of regional cooperation, the University of British Columbia and the University of Washington today announced the establishment of the Cascadia Urban Analytics Cooperative to use data to help cities and communities address challenges from traffic to homelessness. The largest industry-funded research partnership between UBC and the UW, the collaborative will bring faculty, students and community stakeholders together to solve problems, and is made possible thanks to a $1-million gift from Microsoft.

“Thanks to this generous gift from Microsoft, our two universities are poised to help transform the Cascadia region into a technological hub comparable to Silicon Valley and Boston,” said Professor Santa J. Ono, President of the University of British Columbia. “This new partnership transcends borders and strives to unleash our collective brain power, to bring about economic growth that enriches the lives of Canadians and Americans as well as urban communities throughout the world.”

“We have an unprecedented opportunity to use data to help our communities make decisions, and as a result improve people’s lives and well-being. That commitment to the public good is at the core of the mission of our two universities, and we’re grateful to Microsoft for making a community-minded contribution that will spark a range of collaborations,” said UW President Ana Mari Cauce.

Today’s announcement follows last September’s [2016] Emerging Cascadia Innovation Corridor Conference in Vancouver, B.C. The forum brought together regional leaders for the first time to identify concrete opportunities for partnerships in education, transportation, university research, human capital and other areas.

A Boston Consulting Group study unveiled at the conference showed the region between Seattle and Vancouver has “high potential to cultivate an innovation corridor” that competes on an international scale, but only if regional leaders work together. The study says that could be possible through sustained collaboration aided by an educated and skilled workforce, a vibrant network of research universities and a dynamic policy environment.

Microsoft President Brad Smith, who helped convene the conference, said, “We believe that joint research based on data science can help unlock new solutions for some of the most pressing issues in both Vancouver and Seattle. But our goal is bigger than this one-time gift. We hope this investment will serve as a catalyst for broader and more sustainable efforts between these two institutions.”

As part of the Emerging Cascadia conference, British Columbia Premier Christy Clark and Washington Governor Jay Inslee signed a formal agreement that committed the two governments to work closely together to “enhance meaningful and results-driven innovation and collaboration.”  The agreement outlined steps the two governments will take to collaborate in several key areas including research and education.

“Increasingly, tech is not just another standalone sector of the economy, but fully integrated into everything from transportation to social work,” said Premier Clark. “That’s why we’ve invested in B.C.’s thriving tech sector, but committed to working with our neighbours in Washington – and we’re already seeing the results.”

“This data-driven collaboration among some of our smartest and most creative thought-leaders will help us tackle a host of urgent issues,” Gov. Inslee said. “I’m encouraged to see our partnership with British Columbia spurring such interesting cross-border dialogue and excited to see what our students and researchers come up with.”

The Cascadia Urban Analytics Cooperative will revolve around four main programs:

  • The Cascadia Data Science for Social Good (DSSG) Summer Program, which builds on the success of the DSSG program at the UW eScience Institute. The cooperative will coordinate a joint summer program for students across UW and UBC campuses where they work with faculty to create and incubate data-intensive research projects that have concrete benefits for urban communities. One past DSSG project analyzed data from Seattle’s regional transportation system – ORCA – to improve its effectiveness, particularly for low-income transit riders. Another project sought to improve food safety by text mining product reviews to identify unsafe products.
  • Cascadia Data Science for Social Good Scholar Symposium, which will foster innovation and collaboration by bringing together scholars from UBC and the UW involved in projects utilizing technology to advance the social good. The first symposium will be hosted at UW in 2017.
  • Sustained Research Partnerships designed to establish the Pacific Northwest as a center of expertise and activity in urban analytics. The cooperative will support sustained research partnerships between UW and UBC researchers, providing technical expertise, stakeholder engagement and seed funding.
  • Responsible Data Management Systems and Services to ensure data integrity, security and usability. The cooperative will develop new software, systems and services to facilitate data management and analysis, as well as ensure projects adhere to best practices in fairness, accountability and transparency.

At UW, the Cascadia Urban Analytics Collaborative will be overseen by Urbanalytics (urbanalytics.uw.edu), a new research unit in the Information School focused on responsible urban data science. The Collaborative builds on previous investments in data-intensive science through the UW eScience Institute (escience.washington.edu) and investments in urban scholarship through Urban@UW (urban.uw.edu), and also aligns with the UW’s Population Health Initiative (uw.edu/populationhealth) that is addressing the most persistent and emerging challenges in human health, environmental resiliency and social and economic equity. The gift counts toward the UW’s Be Boundless – For Washington, For the World campaign (uw.edu/boundless).

The Collaborative also aligns with the UBC Sustainability Initiative (sustain.ubc.ca) that fosters partnerships beyond traditional boundaries of disciplines, sectors and geographies to address critical issues of our time, as well as the UBC Data Science Institute (dsi.ubc.ca), which aims to advance data science research to address complex problems across domains, including health, science and arts.

Brad Smith, President and Chief Legal Officer of Microsoft, wrote about the joint centre in a Feb. 23, 2017 posting on the Microsoft on the Issues blog (Note:,

The cities of Vancouver and Seattle share many strengths: a long history of innovation, world-class universities and a region rich in cultural and ethnic diversity. While both cities have achieved great success on their own, leaders from both sides of the border realize that tighter partnership and collaboration, through the creation of a Cascadia Innovation Corridor, will expand economic opportunity and prosperity well beyond what each community can achieve separately.

Microsoft supports this vision and today is making a $1 million investment in the Cascadia Urban Analytics Cooperative (CUAC), which is a new joint effort by the University of British Columbia (UBC) and the University of Washington (UW).  It will use data to help local cities and communities address challenges from traffic to homelessness and will be the region’s single largest university-based, industry-funded joint research project. While we recognize the crucial role that universities play in building great companies in the Pacific Northwest, whether it be in computing, life sciences, aerospace or interactive entertainment, we also know research, particularly data science, holds the key to solving some of Vancouver and Seattle’s most pressing issues. This grant will advance this work.

An Oct. 21, 2016 article by Hana Golightly for the Ubyssey newspaper provides a little more detail about the province/state agreement mentioned in the joint UBC/UW news release,

An agreement between BC Premier Christy Clark and Washington Governor Jay Inslee means UBC will be collaborating with the University of Washington (UW) more in the future.

At last month’s [Sept. 2016] Cascadia Conference, Clark and Inslee signed a Memorandum of Understanding with the goal of fostering the growth of the technology sector in both regions. Officially referred to as the Cascadia Innovation Corridor, this partnership aims to reduce boundaries across the region — economic and otherwise.

While the memorandum provides broad goals and is not legally binding, it sets a precedent of collaboration between businesses, governments and universities, encouraging projects that span both jurisdictions. Aiming to capitalize on the cultural commonalities of regional centres Seattle and Vancouver, the agreement prioritizes development in life sciences, clean technology, data analytics and high tech.

Metropolitan centres like Seattle and Vancouver have experienced a surge in growth that sees planners envisioning them as the next Silicon Valleys. Premier Clark and Governor Inslee want to strengthen the ability of their jurisdictions to compete in innovation on a global scale. Accordingly, the memorandum encourages the exploration of “opportunities to advance research programs in key areas of innovation and future technologies among the region’s major universities and institutes.”

A few more questions about the Cooperative

I had a few more questions about the Feb. 23, 2017 announcement, for which (from UBC) Gail C. Murphy, PhD, FRSC, Associate Vice President Research pro tem, Professor, Computer Science of UBC and (from UW) Bill Howe, Associate Professor, Information School, Adjunct Associate Professor, Computer Science & Engineering, Associate Director and Senior Data Science Fellow,, UW eScience Institute Program Director and Faculty Chair, UW Data Science Masters Degree have kindly provided answers (Gail Murphy’s replies are prefaced with [GM] and one indent and Bill Howe’s replies are prefaced with [BH] and two indents),

  • Do you have any projects currently underway? e.g. I see a summer programme is planned. Will there be one in summer 2017? What focus will it have?

[GM] UW and UBC will each be running the Data Science for Social Good program in the summer of 2017. UBC’s announcement of the program is available at: http://dsi.ubc.ca/data-science-social-good-dssg-fellowships

  • Is the $1M from Microsoft going to be given in cash or as ‘in kind goods’ or some combination?

[GM] The $1-million donation is in cash. Microsoft organized the Emerging Cascadia Innovation Corridor Conference in September 2017. It was at the conference that the idea for the partnership was hatched. Through this initiative, UBC and UW will continue to engage with Microsoft to further shared goals in promoting evidence-based innovation to improve life for people in the Cascadia region and beyond.

  • How will the money or goods be disbursed? e.g. Will each institution get 1/2 or is there some sort of joint account?

[GM] The institutions are sharing the funds but will be separately administering the funds they receive.

  • Is data going to be crossing borders? e.g. You mentioned some health care projects. In that case, will data from BC residents be accessed and subject to US rules and regulations? Will BC residents know that there data is being accessed by a 3rd party? What level of consent is required?

[GM] As you point out, there are many issues involved with transferring data across the border. Any projects involving private data will adhere to local laws and ethical frameworks set out by the institutions.

  • Privacy rules vary greatly between the US and Canada. How is that being addressed in this proposed new research?

[No Reply]

  • Will new software and other products be created and who will own them?

[GM] It is too soon for us to comment on whether new software or other products will be created. Any creation of software or other products within the institutions will be governed by institutional policy.

  • Will the research be made freely available?

[GM] UBC researchers must be able to publish the results of research as set out by UBC policy.

[BH] Research output at UW will be made available according to UW policy, but I’ll point out that Microsoft has long been a fantastic partner in advancing our efforts in open and reproducible science, open source software, and open access publishing. 

 UW’s discussion on open access policies is available online.

 

  • What percentage of public funds will be used to enable this project? Will the province of BC and the state of Washington be splitting the costs evenly?

[GM] It is too soon for us to report on specific percentages. At UBC, we will be looking to partner with appropriate funding agencies to support more research with this donation. Applications to funding agencies will involve review of any proposals as per the rules of the funding agency.

  • Will there be any social science and/or ethics component to this collaboration? The press conference referenced data science only.

[GM] We expect, but cannot yet confirm, that some of the projects will involve collaborations with faculty from a broad range of research areas at UBC.

[BH] We are indeed placing a strong emphasis on the intersection between data science, the social sciences, and data ethics.  As examples of activities in this space around UW:

* The Information School at UW (my home school) is actively recruiting a new faculty candidate in data ethics this year

* The Education Working Group at the eScience Institute has created a new campus-wide Data & Society seminar course.

* The Center for Statistics in the Social Sciences (CSSS), which represents the marriage of data science and the social sciences, has been a long-term partner in our activities.

More specifically for this collaboration, we are collecting requirements for new software that emphasizes responsible data science: properly managing sensitive data, combating algorithmic bias, protecting privacy, and more.

Microsoft has been a key partner in this work through their Civic Technology group, for which the Seattle arm is led by Graham Thompson.

  • What impact do you see the new US federal government’s current concerns over borders and immigrants hav[ing] on this project? e.g. Are people whose origins are in Iran, Syria, Yemen, etc. and who are residents of Canada going to be able to participate?

[GM] Students and others eligible to participate in research projects in Canada will be welcomed into the UBC projects. Our hope is that faculty and students working on the Cascadia Urban Analytics Cooperative will be able to exchange ideas freely and move freely back and forth across the border.

  • How will seed funding for Sustained Research Partnerships’ be disbursed? Will there be a joint committee making these decisions?

[GM] We are in the process of elaborating this part of the program. At UBC, we are already experiencing, enjoying and benefitting from increased interaction with the University of Washington and look forward to elaborating more aspects of the program together as the year unfolds.

I had to make a few formatting changes when transferring the answers from emails to this posting: my numbered questions (1-11) became bulleted points and ‘have’ in what was question 10 was changed to ‘having’. The content for the answers has been untouched.

I’m surprised no one answered the privacy question but perhaps they thought the other answers sufficed. Despite an answer to my question, I don’t understand how the universities are sharing the funds but that may just mean I’m having a bad day. (Or perhaps the folks at UBC are being overly careful after the scandals rocking the Vancouver campus over the last 18 months to two years (see Sophie Sutcliffe’s Dec. 3, 2015 opinion piece for the Ubyssey for details about the scandals).

Bill Howe’s response about open access (where you can read the journal articles for free) and open source (where you have free access to the software code) was interesting to me as I once worked for a company where the developers complained loud and long about Microsoft’s failure to embrace open source code. Howe’s response is particularly interesting given that Microsoft’s president is also the Chief Legal Officer whose portfolio of responsibilities (I imagine) includes patents.

Matt Day in a Feb. 23, 2017 article for the The Seattle Times provides additional perspective (Note: Links have been removed),

Microsoft’s effort to nudge Seattle and Vancouver, B.C., a bit closer together got an endorsement Thursday [Feb. 23, 2017] from the leading university in each city.

The University of Washington and the University of British Columbia announced the establishment of a joint data-science research unit, called the Cascadia Urban Analytics Cooperative, funded by a $1 million grant from Microsoft.

The collaboration will support study of shared urban issues, from health to transit to homelessness, drawing on faculty and student input from both universities.

The partnership has its roots in a September [2016] conference in Vancouver organized by Microsoft’s public affairs and lobbying unit [emphasis mine.] That gathering was aimed at tying business, government and educational institutions in Microsoft’s home region in the Seattle area closer to its Canadian neighbor.

Microsoft last year [2016]* opened an expanded office in downtown Vancouver with space for 750 employees, an outpost partly designed to draw to the Northwest more engineers than the company can get through the U.S. guest worker system [emphasis mine].

There’s nothing wrong with a business offering to contribute to the social good but it does well to remember that a business’s primary agenda is not the social good.  So in this case, it seems that public affairs and lobbying is really governmental affairs and that Microsoft has anticipated, for some time, greater difficulties with getting workers from all sorts of countries across the US border to work in Washington state making an outpost in British Columbia and closer relations between the constituencies quite advantageous. I wonder what else is on their agenda.

Getting back to UBC and UW, thank you to both Gail Murphy (in particular) and Bill Howe for taking the time to answer my questions. I very much appreciate it as answering 10 questions is a lot of work.

There were one area of interest (cities) that I did not broach with the either academic but will mention here.

Cities and their increasing political heft

Clearly Microsoft is focused on urban issues and that would seem to be the ‘flavour du jour’. There’s a May 31, 2016 piece on the TED website by Robert Muggah and Benjamin Fowler titled: ‘Why cities rule the world‘ (there are video talks embedded in the piece),

Cities are the the 21st century’s dominant form of civilization — and they’re where humanity’s struggle for survival will take place. Robert Muggah and Benjamin Barber spell out the possibilities.

Half the planet’s population lives in cities. They are the world’s engines, generating four-fifths of the global GDP. There are over 2,100 cities with populations of 250,000 people or more, including a growing number of mega-cities and sprawling, networked-city areas — conurbations, they’re called — with at least 10 million residents. As the economist Ed Glaeser puts it, “we are an urban species.”

But what makes cities so incredibly important is not just population or economics stats. Cities are humanity’s most realistic hope for future democracy to thrive, from the grassroots to the global. This makes them a stark contrast to so many of today’s nations, increasingly paralyzed by polarization, corruption and scandal.

In a less hyperbolic vein, Parag Khanna’s April 20,2016 piece for Quartz describes why he (and others) believe that megacities are where the future lies (Note: A link has been removed),

Cities are mankind’s most enduring and stable mode of social organization, outlasting all empires and nations over which they have presided. Today cities have become the world’s dominant demographic and economic clusters.

As the sociologist Christopher Chase-Dunn has pointed out, it is not population or territorial size that drives world-city status, but economic weight, proximity to zones of growth, political stability, and attractiveness for foreign capital. In other words, connectivity matters more than size. Cities thus deserve more nuanced treatment on our maps than simply as homogeneous black dots.

Within many emerging markets such as Brazil, Turkey, Russia, and Indonesia, the leading commercial hub or financial center accounts for at least one-third or more of national GDP. In the UK, London accounts for almost half Britain’s GDP. And in America, the Boston-New York-Washington corridor and greater Los Angeles together combine for about one-third of America’s GDP.

By 2025, there will be at least 40 such megacities. The population of the greater Mexico City region is larger than that of Australia, as is that of Chongqing, a collection of connected urban enclaves in China spanning an area the size of Austria. Cities that were once hundreds of kilometers apart have now effectively fused into massive urban archipelagos, the largest of which is Japan’s Taiheiyo Belt that encompasses two-thirds of Japan’s population in the Tokyo-Nagoya-Osaka megalopolis.

Great and connected cities, Saskia Sassen argues, belong as much to global networks as to the country of their political geography. Today the world’s top 20 richest cities have forged a super-circuit driven by capital, talent, and services: they are home to more than 75% of the largest companies, which in turn invest in expanding across those cities and adding more to expand the intercity network. Indeed, global cities have forged a league of their own, in many ways as denationalized as Formula One racing teams, drawing talent from around the world and amassing capital to spend on themselves while they compete on the same circuit.

The rise of emerging market megacities as magnets for regional wealth and talent has been the most significant contributor to shifting the world’s focal point of economic activity. McKinsey Global Institute research suggests that from now until 2025, one-third of world growth will come from the key Western capitals and emerging market megacities, one-third from the heavily populous middle-weight cities of emerging markets, and one-third from small cities and rural areas in developing countries.

Khanna’s megacities all exist within one country. If Vancouver and Seattle (and perhaps Portland?) were to become a become a megacity it would be one of the only or few to cross national borders.

Khanna has been mentioned here before in a Jan. 27, 2016 posting about cities and technology and a public engagement exercise with the National Research of Council of Canada (scroll down to the subsection titled: Cities rising in important as political entities).

Muggah/Fowler’s and Khanna’s 2016 pieces are well worth reading if you have the time.

For what it’s worth, I’m inclined to agree that cities will be and are increasing in political  importance along with this area of development:

Algorithms and big data

Concerns are being raised about how big data is being utilized so I was happy to see specific initiatives to address ethics issues in Howe’s response. For anyone not familiar with the concerns, here’s an excerpt from Cathy O’Neal’s Oct. 18, 2016 article for Wired magazine,

The age of Big Data has generated new tools and ideas on an enormous scale, with applications spreading from marketing to Wall Street, human resources, college admissions, and insurance. At the same time, Big Data has opened opportunities for a whole new class of professional gamers and manipulators, who take advantage of people using the power of statistics.

I should know. I was one of them.

Information is power, and in the age of corporate surveillance, profiles on every active American consumer means that the system is slanted in favor of those with the data. This data helps build tailor-made profiles that can be used for or against someone in a given situation. Insurance companies, which historically sold car insurance based on driving records, have more recently started using such data-driven profiling methods. A Florida insurance company has been found to charge people with low credit scores and good driving records more than people with high credit scores and a drunk driving conviction. It’s become standard practice for insurance companies to charge people not what they represent as a risk, but what they can get away with. The victims, of course, are those least likely to be able to afford the extra cost, but who need a car to get to work.

Big data profiling techniques are exploding in the world of politics. It’s estimated that over $1 billion will be spent on digital political ads in this election cycle, almost 50 times as much as was spent in 2008; this field is a growing part of the budget for presidential as well as down-ticket races. Political campaigns build scoring systems on potential voters—your likelihood of voting for a given party, your stance on a given issue, and the extent to which you are persuadable on that issue. It’s the ultimate example of asymmetric information, and the politicians can use what they know to manipulate your vote or your donation.

I highly recommend reading O’Neal’s article and, if you have the time, her book ‘Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy’.

Finally

I look forward to hearing more about the Cascadia Urban Analytics Cooperative and the Cascadia Innovation Corridor as they develop. This has the potential to be very exciting although I do have some concerns such as MIcrosoft and its agendas, both stated and unstated. After all, the Sept. 2016 meeting was convened by Microsoft and its public affairs/lobbying group and the topic was innovation, which is code for business and as hinted earlier, business is not synonymous with social good. Having said that I’m not about to demonize business either. I just think a healthy dose of skepticism is called for. Good things can happen but we need to ensure they do.

Thankfully, my concerns regarding algorithms and big data seem to be shared in some quarters, unfortunately none of these quarters appear to be located at the University of British Columbia. I hope that’s over caution with regard to communication rather than a failure to recognize any pitfalls.

ETA Mar. 1, 2017: Interestingly, the UK House of Commons Select Committee on Science and Technology announced an inquiry into the use of algorithms in public and business decision-making on Feb. 28, 2017. As this posting as much too big already, I’ve posted about the UK inquire separately in a Mar. 1, 2017 posting.

*’2016′ added for clarity on March 24, 2017.

How might artificial intelligence affect urban life in 2030? A study

Peering into the future is always a chancy business as anyone who’s seen those film shorts from the 1950’s and 60’s which speculate exuberantly as to what the future will bring knows.

A sober approach (appropriate to our times) has been taken in a study about the impact that artificial intelligence might have by 2030. From a Sept. 1, 2016 Stanford University news release (also on EurekAlert) by Tom Abate (Note: Links have been removed),

A panel of academic and industrial thinkers has looked ahead to 2030 to forecast how advances in artificial intelligence (AI) might affect life in a typical North American city – in areas as diverse as transportation, health care and education ­– and to spur discussion about how to ensure the safe, fair and beneficial development of these rapidly emerging technologies.

Titled “Artificial Intelligence and Life in 2030,” this year-long investigation is the first product of the One Hundred Year Study on Artificial Intelligence (AI100), an ongoing project hosted by Stanford to inform societal deliberation and provide guidance on the ethical development of smart software, sensors and machines.

“We believe specialized AI applications will become both increasingly common and more useful by 2030, improving our economy and quality of life,” said Peter Stone, a computer scientist at the University of Texas at Austin and chair of the 17-member panel of international experts. “But this technology will also create profound challenges, affecting jobs and incomes and other issues that we should begin addressing now to ensure that the benefits of AI are broadly shared.”

The new report traces its roots to a 2009 study that brought AI scientists together in a process of introspection that became ongoing in 2014, when Eric and Mary Horvitz created the AI100 endowment through Stanford. AI100 formed a standing committee of scientists and charged this body with commissioning periodic reports on different aspects of AI over the ensuing century.

“This process will be a marathon, not a sprint, but today we’ve made a good start,” said Russ Altman, a professor of bioengineering and the Stanford faculty director of AI100. “Stanford is excited to host this process of introspection. This work makes practical contribution to the public debate on the roles and implications of artificial intelligence.”

The AI100 standing committee first met in 2015, led by chairwoman and Harvard computer scientist Barbara Grosz. It sought to convene a panel of scientists with diverse professional and personal backgrounds and enlist their expertise to assess the technological, economic and policy implications of potential AI applications in a societally relevant setting.

“AI technologies can be reliable and broadly beneficial,” Grosz said. “Being transparent about their design and deployment challenges will build trust and avert unjustified fear and suspicion.”

The report investigates eight domains of human activity in which AI technologies are beginning to affect urban life in ways that will become increasingly pervasive and profound by 2030.

The 28,000-word report includes a glossary to help nontechnical readers understand how AI applications such as computer vision might help screen tissue samples for cancers or how natural language processing will allow computerized systems to grasp not simply the literal definitions, but the connotations and intent, behind words.

The report is broken into eight sections focusing on applications of AI. Five examine application arenas such as transportation where there is already buzz about self-driving cars. Three other sections treat technological impacts, like the section on employment and workplace trends which touches on the likelihood of rapid changes in jobs and incomes.

“It is not too soon for social debate on how the fruits of an AI-dominated economy should be shared,” the researchers write in the report, noting also the need for public discourse.

“Currently in the United States, at least sixteen separate agencies govern sectors of the economy related to AI technologies,” the researchers write, highlighting issues raised by AI applications: “Who is responsible when a self-driven car crashes or an intelligent medical device fails? How can AI applications be prevented from [being used for] racial discrimination or financial cheating?”

The eight sections discuss:

Transportation: Autonomous cars, trucks and, possibly, aerial delivery vehicles may alter how we commute, work and shop and create new patterns of life and leisure in cities.

Home/service robots: Like the robotic vacuum cleaners already in some homes, specialized robots will clean and provide security in live/work spaces that will be equipped with sensors and remote controls.

Health care: Devices to monitor personal health and robot-assisted surgery are hints of things to come if AI is developed in ways that gain the trust of doctors, nurses, patients and regulators.

Education: Interactive tutoring systems already help students learn languages, math and other skills. More is possible if technologies like natural language processing platforms develop to augment instruction by humans.

Entertainment: The conjunction of content creation tools, social networks and AI will lead to new ways to gather, organize and deliver media in engaging, personalized and interactive ways.

Low-resource communities: Investments in uplifting technologies like predictive models to prevent lead poisoning or improve food distributions could spread AI benefits to the underserved.

Public safety and security: Cameras, drones and software to analyze crime patterns should use AI in ways that reduce human bias and enhance safety without loss of liberty or dignity.

Employment and workplace: Work should start now on how to help people adapt as the economy undergoes rapid changes as many existing jobs are lost and new ones are created.

“Until now, most of what is known about AI comes from science fiction books and movies,” Stone said. “This study provides a realistic foundation to discuss how AI technologies are likely to affect society.”

Grosz said she hopes the AI 100 report “initiates a century-long conversation about ways AI-enhanced technologies might be shaped to improve life and societies.”

You can find the A100 website here, and the group’s first paper: “Artificial Intelligence and Life in 2030” here. Unfortunately, I don’t have time to read the report but I hope to do so soon.

The AI100 website’s About page offered a surprise,

This effort, called the One Hundred Year Study on Artificial Intelligence, or AI100, is the brainchild of computer scientist and Stanford alumnus Eric Horvitz who, among other credits, is a former president of the Association for the Advancement of Artificial Intelligence.

In that capacity Horvitz convened a conference in 2009 at which top researchers considered advances in artificial intelligence and its influences on people and society, a discussion that illuminated the need for continuing study of AI’s long-term implications.

Now, together with Russ Altman, a professor of bioengineering and computer science at Stanford, Horvitz has formed a committee that will select a panel to begin a series of periodic studies on how AI will affect automation, national security, psychology, ethics, law, privacy, democracy and other issues.

“Artificial intelligence is one of the most profound undertakings in science, and one that will affect every aspect of human life,” said Stanford President John Hennessy, who helped initiate the project. “Given’s Stanford’s pioneering role in AI and our interdisciplinary mindset, we feel obliged and qualified to host a conversation about how artificial intelligence will affect our children and our children’s children.”

Five leading academicians with diverse interests will join Horvitz and Altman in launching this effort. They are:

  • Barbara Grosz, the Higgins Professor of Natural Sciences at HarvardUniversity and an expert on multi-agent collaborative systems;
  • Deirdre K. Mulligan, a lawyer and a professor in the School of Information at the University of California, Berkeley, who collaborates with technologists to advance privacy and other democratic values through technical design and policy;

    This effort, called the One Hundred Year Study on Artificial Intelligence, or AI100, is the brainchild of computer scientist and Stanford alumnus Eric Horvitz who, among other credits, is a former president of the Association for the Advancement of Artificial Intelligence.

    In that capacity Horvitz convened a conference in 2009 at which top researchers considered advances in artificial intelligence and its influences on people and society, a discussion that illuminated the need for continuing study of AI’s long-term implications.

    Now, together with Russ Altman, a professor of bioengineering and computer science at Stanford, Horvitz has formed a committee that will select a panel to begin a series of periodic studies on how AI will affect automation, national security, psychology, ethics, law, privacy, democracy and other issues.

    “Artificial intelligence is one of the most profound undertakings in science, and one that will affect every aspect of human life,” said Stanford President John Hennessy, who helped initiate the project. “Given’s Stanford’s pioneering role in AI and our interdisciplinary mindset, we feel obliged and qualified to host a conversation about how artificial intelligence will affect our children and our children’s children.”

    Five leading academicians with diverse interests will join Horvitz and Altman in launching this effort. They are:

    • Barbara Grosz, the Higgins Professor of Natural Sciences at HarvardUniversity and an expert on multi-agent collaborative systems;
    • Deirdre K. Mulligan, a lawyer and a professor in the School of Information at the University of California, Berkeley, who collaborates with technologists to advance privacy and other democratic values through technical design and policy;
    • Yoav Shoham, a professor of computer science at Stanford, who seeks to incorporate common sense into AI;
    • Tom Mitchell, the E. Fredkin University Professor and chair of the machine learning department at Carnegie Mellon University, whose studies include how computers might learn to read the Web;
    • and Alan Mackworth, a professor of computer science at the University of British Columbia [emphases mine] and the Canada Research Chair in Artificial Intelligence, who built the world’s first soccer-playing robot.

    I wasn’t expecting to see a Canadian listed as a member of the AI100 standing committee and then I got another surprise (from the AI100 People webpage),

    Study Panels

    Study Panels are planned to convene every 5 years to examine some aspect of AI and its influences on society and the world. The first study panel was convened in late 2015 to study the likely impacts of AI on urban life by the year 2030, with a focus on typical North American cities.

    2015 Study Panel Members

    • Peter Stone, UT Austin, Chair
    • Rodney Brooks, Rethink Robotics
    • Erik Brynjolfsson, MIT
    • Ryan Calo, University of Washington
    • Oren Etzioni, Allen Institute for AI
    • Greg Hager, Johns Hopkins University
    • Julia Hirschberg, Columbia University
    • Shivaram Kalyanakrishnan, IIT Bombay
    • Ece Kamar, Microsoft
    • Sarit Kraus, Bar Ilan University
    • Kevin Leyton-Brown, [emphasis mine] UBC [University of British Columbia]
    • David Parkes, Harvard
    • Bill Press, UT Austin
    • AnnaLee (Anno) Saxenian, Berkeley
    • Julie Shah, MIT
    • Milind Tambe, USC
    • Astro Teller, Google[X]
  • [emphases mine] and the Canada Research Chair in Artificial Intelligence, who built the world’s first soccer-playing robot.

I wasn’t expecting to see a Canadian listed as a member of the AI100 standing committee and then I got another surprise (from the AI100 People webpage),

Study Panels

Study Panels are planned to convene every 5 years to examine some aspect of AI and its influences on society and the world. The first study panel was convened in late 2015 to study the likely impacts of AI on urban life by the year 2030, with a focus on typical North American cities.

2015 Study Panel Members

  • Peter Stone, UT Austin, Chair
  • Rodney Brooks, Rethink Robotics
  • Erik Brynjolfsson, MIT
  • Ryan Calo, University of Washington
  • Oren Etzioni, Allen Institute for AI
  • Greg Hager, Johns Hopkins University
  • Julia Hirschberg, Columbia University
  • Shivaram Kalyanakrishnan, IIT Bombay
  • Ece Kamar, Microsoft
  • Sarit Kraus, Bar Ilan University
  • Kevin Leyton-Brown, [emphasis mine] UBC [University of British Columbia]
  • David Parkes, Harvard
  • Bill Press, UT Austin
  • AnnaLee (Anno) Saxenian, Berkeley
  • Julie Shah, MIT
  • Milind Tambe, USC
  • Astro Teller, Google[X]

I see they have representation from Israel, India, and the private sector as well. Refreshingly, there’s more than one woman on the standing committee and in this first study group. It’s good to see these efforts at inclusiveness and I’m particularly delighted with the inclusion of an organization from Asia. All too often inclusiveness means Europe, especially the UK. So, it’s good (and I think important) to see a different range of representation.

As for the content of report, should anyone have opinions about it, please do let me know your thoughts in the blog comments.

Music videos for teaching science and a Baba Brinkman update

I have two news bits concerning science and music.

Music videos and science education

Researchers in the US and New Zealand have published a study on how effective music videos are for teaching science. Hint: there are advantages but don’t expect perfection. From a May 25, 2016 news item on ScienceDaily,

Does “edutainment” such as content-rich music videos have any place in the rapidly changing landscape of science education? A new study indicates that students can indeed learn serious science content from such videos.

The study, titled ‘Leveraging the power of music to improve science education’ and published by International Journal of Science Education, examined over 1,000 students in a three-part experiment, comparing learners’ understanding and engagement in response to 24 musical and non-musical science videos.

A May 25, 2016 Taylor & Francis (publishers) press release, which originated the news item, quickly gets to the point,

The central findings were that (1) across ages and genders, K-16 students who viewed music videos improved their scores on quizzes about content covered in the videos, and (2) students preferred music videos to non-musical videos covering equivalent content.  Additionally, the results hinted that videos with music might lead to superior long-term retention of the content.

“We tested most of these students outside of their normal classrooms,” commented lead author Greg Crowther, Ph.D., a lecturer at the University of Washington.  “The students were not forced by their teachers to watch these videos, and they didn’t have the spectre of a low course grade hanging over their heads.  Yet they clearly absorbed important information, which highlights the great potential of music to deliver key content in an appealing package.”

The study was inspired by the classroom experiences of Crowther and co-author Tom McFadden [emphasis mine], who teaches science at the Nueva School in California.  “Tom and I, along with many others, write songs for and with our students, and we’ve had a lot of fun doing that,” said Crowther.  “But rather than just assuming that this works, we wanted to see whether we could document learning gains in an objective way.”

The findings of this study have implications for teacher practitioners, policy-makers and researchers who are looking for innovative ways to improve science education.  “Music will always be a supplement to, rather than a substitute for, more traditional forms of teaching,” said Crowther.  “But teachers who want to connect with their students through music now have some additional data on their side.”

The paper is quite interesting (two of the studies were run in the US and one in New Zealand) and I notice that Don McFadden of the Science Rap Academy is one of the authors (more about him later); here’s a link to and a citation for the paper,

Leveraging the power of music to improve science education by Gregory J. Crowther, Tom McFadden, Jean S. Fleming, & Katie Davis.  International Journal of Science Education
Volume 38, Issue 1, 2016 pages 73-95. DOI: 10.1080/09500693.2015.1126001 Published online: 18 Jan 2016

This paper is open access. As I noted earlier, the research is promising but science music videos are not the answer to all science education woes.

One of my more recent pieces featuring Tom McFadden and his Science Rap Academy is this April 21, 2015 posting. The 2016 edition of the academy started in January 2016 according to David Bruggeman’s Jan. 27, 2016 posting on his Pasco Phronesis blog. You can find the Science Rap Academy’s YouTube channel here and the playlist here.

Canadian science rappers and musicians

I promised the latest about Baba Brinkman and here it is (from a May 14, 2016 notice received via email,

Not many people know this, but Dylan Thomas [legendary Welsh poet] was one of my early influences as a poet and one of the reasons I was inspired to pursue versification as a career. Well now Literature Wales has commissioned me to write and record a new rap/poem in celebration of Dylan Day 2016 (today [May 14, 20160) which I dutifully did. You can watch the video here to check out what a hip-hop flow and a Thomas poem have in common.

In other news, I’ll be performing a couple of one-off show over the next few weeks. Rap Guide to Religion is on at NECSS in New York on May 15 (tomorrow) [Note: Link removed as the event date has now been passed] and Rap Guide to Evolution is at the Reason Rally in DC June 2nd [2016]. I’m also continuing with the off-Broadway run of Rap Guide to Climate Chaos, recording the climate chaos album and looking to my next round of writing and touring, so if you have ideas about venues I could play please send me a note.

You can find out more about Baba Brinkman (a Canadian rapper who has written and  performed many science raps and lives in New York) here.

There’s another Canadian who produces musical science videos, Tim Blais (physicist and Montréaler) who was most recently featured here in a Feb. 12, 2016 posting. You can find a selection of Blais’ videos on his A Capella Science channel on YouTube.

Light-captured energetics (harvesting light for optoelectronics)

Comparing graphene to a tiger is unusual but that’s what researcher Sanfeng Wu does—eventually—in a May 13, 2016 University of Washington news release (also on EurekAlert) about his work,

In the quest to harvest light for electronics, the focal point is the moment when photons — light particles — encounter electrons, those negatively-charged subatomic particles that form the basis of our modern electronic lives. If conditions are right when electrons and photons meet, an exchange of energy can occur. Maximizing that transfer of energy is the key to making efficient light-captured energetics possible.

“This is the ideal, but finding high efficiency is very difficult,” said University of Washington physics doctoral student Sanfeng Wu. “Researchers have been looking for materials that will let them do this — one way is to make each absorbed photon transfer all of its energy to many electrons, instead of just one electron in traditional devices.”

In traditional light-harvesting methods, energy from one photon only excites one electron or none depending on the absorber’s energy gap, transferring just a small portion of light energy into electricity. The remaining energy is lost as heat. But in a paper released May 13 in Science Advances, Wu, UW associate professor Xiaodong Xu and colleagues at four other institutions describe one promising approach to coax photons into stimulating multiple electrons. Their method exploits some surprising quantum-level interactions to give one photon multiple potential electron partners. Wu and Xu, who has appointments in the UW’s Department of Materials Science & Engineering and the Department of Physics, made this surprising discovery using graphene.

There has been intense research on graphene’s electrical properties but the researchers’ discovery adds a new property to be investigated (from the news release),

“Graphene is a substance with many exciting properties,” said Wu, the paper’s lead author. “For our purposes, it shows a very efficient interaction with light.”

Graphene is a two-dimensional hexagonal lattice of carbon atoms bonded to one another, and electrons are able to move easily within graphene. The researchers took a single layer of graphene — just one sheet of carbon atoms thick — and sandwiched it between two thin layers of a material called boron-nitride.

Boron-nitride is a material that has excited a great deal of interest in the last 12 to 18 months (from the news release),

“Boron-nitride has a lattice structure that is very similar to graphene, but has very different chemical properties,” said Wu. “Electrons do not flow easily within boron-nitride; it essentially acts as an insulator.”

Xu and Wu discovered that when the graphene layer’s lattice is aligned with the layers of boron-nitride, a type of “superlattice” is created with properties allowing efficient optoelectronics that researchers had sought. These properties rely on quantum mechanics, the occasionally baffling rules that govern interactions between all known particles of matter. Wu and Xu detected unique quantum regions within the superlattice known as Van Hove singularities.

Here’s an animated .gif illustrating the superlattice in action,

The Moire superlattice they created by aligning graphene and boron-nitride. Credit: Sanfeng Wu.

The Moire superlattice they created by aligning graphene and boron-nitride. Credit: Sanfeng Wu.

The news release goes on to describe the Van Hove singularities within the superlattice and to mention the ‘tiger’,

“These are regions of huge electron density of states, and they were not accessed in either the graphene or boron-nitride alone,” said Wu. “We only created these high electron density regions in an accessible way when both layers were aligned together.”

When Xu and Wu directed energetic photons toward the superlattice, they discovered that those Van Hove singularities were sites where one energized photon could transfer its energy to multiple electrons that are subsequently collected by electrodes— not just one electron or none with the remaining energy lost as heat. By a conservative estimate, Xu and Wu report that within this superlattice one photon could “kick” as many as five electrons to flow as current.

With the discovery of collecting multiple electrons upon the absorption of one photon, researchers may be able to create highly efficient devices that could harvest light with a large energy profit. Future work would need to uncover how to organize the excited electrons into electrical current for optimizing the energy-converting efficiency and remove some of the more cumbersome properties of their superlattice, such as the need for a magnetic field. But they believe this efficient process between photons and electrons represents major progress.

“Graphene is a tiger with great potential for optoelectronics, but locked in a cage,” said Wu. “The singularities in this superlattice are a key to unlocking that cage and releasing graphene’s potential for light harvesting application.”

H/t to a May 13, 2016 news item on phys.org.

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

Multiple hot-carrier collection in photo-excited graphene Moiré superlattices by Sanfeng Wu, Lei Wang, You Lai, Wen-Yu Shan, Grant Aivazian, Xian Zhang, Takashi Taniguchi, Kenji Watanabe, Di Xiao, Cory Dean, James Hone, Zhiqiang Li, and Xiaodong Xu. Science Advances 13 May 2016: Vol. 2, no. 5, e1600002 DOI: 10.1126/sciadv.1600002

This paper is open access.

Performances Tom Hanks never gave

The answer to the question, “What makes Tom Hanks look like Tom  Hanks?” leads to machine learning and algorithms according to a Dec. 7, 2015 University of Washington University news release (also on EurekAlert) Note: Link have been removed,

Tom Hanks has appeared in many acting roles over the years, playing young and old, smart and simple. Yet we always recognize him as Tom Hanks.

Why? Is it his appearance? His mannerisms? The way he moves?

University of Washington researchers have demonstrated that it’s possible for machine learning algorithms to capture the “persona” and create a digital model of a well-photographed person like Tom Hanks from the vast number of images of them available on the Internet.

With enough visual data to mine, the algorithms can also animate the digital model of Tom Hanks to deliver speeches that the real actor never performed.

“One answer to what makes Tom Hanks look like Tom Hanks can be demonstrated with a computer system that imitates what Tom Hanks will do,” said lead author Supasorn Suwajanakorn, a UW graduate student in computer science and engineering.

As for the performances Tom Hanks never gave, the news release offers more detail,

The technology relies on advances in 3-D face reconstruction, tracking, alignment, multi-texture modeling and puppeteering that have been developed over the last five years by a research group led by UW assistant professor of computer science and engineering Ira Kemelmacher-Shlizerman. The new results will be presented in a paper at the International Conference on Computer Vision in Chile on Dec. 16.

The team’s latest advances include the ability to transfer expressions and the way a particular person speaks onto the face of someone else — for instance, mapping former president George W. Bush’s mannerisms onto the faces of other politicians and celebrities.

Here’s a video demonstrating how former President Bush’s speech and mannerisms have mapped onto other famous faces including Hanks’s,

The research team has future plans for this technology (from the news release)

It’s one step toward a grand goal shared by the UW computer vision researchers: creating fully interactive, three-dimensional digital personas from family photo albums and videos, historic collections or other existing visuals.

As virtual and augmented reality technologies develop, they envision using family photographs and videos to create an interactive model of a relative living overseas or a far-away grandparent, rather than simply Skyping in two dimensions.

“You might one day be able to put on a pair of augmented reality glasses and there is a 3-D model of your mother on the couch,” said senior author Kemelmacher-Shlizerman. “Such technology doesn’t exist yet — the display technology is moving forward really fast — but how do you actually re-create your mother in three dimensions?”

One day the reconstruction technology could be taken a step further, researchers say.

“Imagine being able to have a conversation with anyone you can’t actually get to meet in person — LeBron James, Barack Obama, Charlie Chaplin — and interact with them,” said co-author Steve Seitz, UW professor of computer science and engineering. “We’re trying to get there through a series of research steps. One of the true tests is can you have them say things that they didn’t say but it still feels like them? This paper is demonstrating that ability.”

Existing technologies to create detailed three-dimensional holograms or digital movie characters like Benjamin Button often rely on bringing a person into an elaborate studio. They painstakingly capture every angle of the person and the way they move — something that can’t be done in a living room.

Other approaches still require a person to be scanned by a camera to create basic avatars for video games or other virtual environments. But the UW computer vision experts wanted to digitally reconstruct a person based solely on a random collection of existing images.

To reconstruct celebrities like Tom Hanks, Barack Obama and Daniel Craig, the machine learning algorithms mined a minimum of 200 Internet images taken over time in various scenarios and poses — a process known as learning ‘in the wild.’

“We asked, ‘Can you take Internet photos or your personal photo collection and animate a model without having that person interact with a camera?'” said Kemelmacher-Shlizerman. “Over the years we created algorithms that work with this kind of unconstrained data, which is a big deal.”

Suwajanakorn more recently developed techniques to capture expression-dependent textures — small differences that occur when a person smiles or looks puzzled or moves his or her mouth, for example.

By manipulating the lighting conditions across different photographs, he developed a new approach to densely map the differences from one person’s features and expressions onto another person’s face. That breakthrough enables the team to ‘control’ the digital model with a video of another person, and could potentially enable a host of new animation and virtual reality applications.

“How do you map one person’s performance onto someone else’s face without losing their identity?” said Seitz. “That’s one of the more interesting aspects of this work. We’ve shown you can have George Bush’s expressions and mouth and movements, but it still looks like George Clooney.”

Here’s a link to and a citation for the paper presented at the conference in Chile,

What Makes Tom Hanks Look Like Tom Hanks by Supasorn Suwajanakorn, Steven M. Seitz, Ira Kemelmacher-Shlizerman for the 2015 ICCV conference, Dec. 13 – 15, 2015 in Chile.

You can find out more about the conference here.