Tag Archives: Donald Trump

Hardware policies best way to manage AI safety?

Regulation of artificial intelligence (AI) has become very topical in the last couple of years. There was an AI safety summit in November 2023 at Bletchley Park in the UK (see my November 2, 2023 posting for more about that international meeting).

A very software approach?

This year (2024) has seen a rise in legislative and proposed legislative activity. I have some articles on a few of these activities. China was the first to enact regulations of any kind on AI according to Matt Sheehan’s February 27, 2024 paper for the Carnegie Endowment for International Peace,

In 2021 and 2022, China became the first country to implement detailed, binding regulations on some of the most common applications of artificial intelligence (AI). These rules formed the foundation of China’s emerging AI governance regime, an evolving policy architecture that will affect everything from frontier AI research to the functioning of the world’s second-largest economy, from large language models in Africa to autonomous vehicles in Europe.

The Chinese Communist Party (CCP) and the Chinese government started that process with the 2021 rules on recommendation algorithms, an omnipresent use of the technology that is often overlooked in international AI governance discourse. Those rules imposed new obligations on companies to intervene in content recommendations, granted new rights to users being recommended content, and offered protections to gig workers subject to algorithmic scheduling. The Chinese party-state quickly followed up with a new regulation on “deep synthesis,” the use of AI to generate synthetic media such as deepfakes. Those rules required AI providers to watermark AI-generated content and ensure that content does not violate people’s “likeness rights” or harm the “nation’s image.” Together, these two regulations also created and amended China’s algorithm registry, a regulatory tool that would evolve into a cornerstone of the country’s AI governance regime.

The UK has adopted a more generalized approach focused on encouraging innovation according to Valeria Gallo’s and Suchitra Nair’s February 21, 2024 article for Deloitte (a British professional services firm also considered one of the big four accounting firms worldwide),

At a glance

The UK Government has adopted a cross-sector and outcome-based framework for regulating AI, underpinned by five core principles. These are safety, security and robustness, appropriate transparency and explainability, fairness, accountability and governance, and contestability and redress.

Regulators will implement the framework in their sectors/domains by applying existing laws and issuing supplementary regulatory guidance. Selected regulators will publish their AI annual strategic plans by 30th April [2024], providing businesses with much-needed direction.

Voluntary safety and transparency measures for developers of highly capable AI models and systems will also supplement the framework and the activities of individual regulators.

The framework will not be codified into law for now, but the Government anticipates the need for targeted legislative interventions in the future. These interventions will address gaps in the current regulatory framework, particularly regarding the risks posed by complex General Purpose AI and the key players involved in its development.

Organisations must prepare for increased AI regulatory activity over the next year, including guidelines, information gathering, and enforcement. International firms will inevitably have to navigate regulatory divergence.

While most of the focus appears to be on the software (e.g., General Purpose AI), the UK framework does not preclude hardware.

The European Union (EU) is preparing to pass its own AI regulation act through the European Parliament in 2024 according to a December 19, 2023 “EU AI Act: first regulation on artificial intelligence” article update, Note: Links have been removed,

As part of its digital strategy, the EU wants to regulate artificial intelligence (AI) to ensure better conditions for the development and use of this innovative technology. AI can create many benefits, such as better healthcare; safer and cleaner transport; more efficient manufacturing; and cheaper and more sustainable energy.

In April 2021, the European Commission proposed the first EU regulatory framework for AI. It says that AI systems that can be used in different applications are analysed and classified according to the risk they pose to users. The different risk levels will mean more or less regulation.

The agreed text is expected to be finally adopted in April 2024. It will be fully applicable 24 months after entry into force, but some parts will be applicable sooner:

*The ban of AI systems posing unacceptable risks will apply six months after the entry into force

*Codes of practice will apply nine months after entry into force

*Rules on general-purpose AI systems that need to comply with transparency requirements will apply 12 months after the entry into force

High-risk systems will have more time to comply with the requirements as the obligations concerning them will become applicable 36 months after the entry into force.

This EU initiative, like the UK framework, seems largely focused on AI software and according to the Wikipedia entry “Regulation of artificial intelligence,”

… The AI Act is expected to come into effect in late 2025 or early 2026.[109

I do have a few postings about Canadian regulatory efforts, which also seem to be focused on software but don’t preclude hardware. While the January 20, 2024 posting is titled “Canada’s voluntary code of conduct relating to advanced generative AI (artificial intelligence) systems,” information about legislative efforts is also included although you might find my May 1, 2023 posting titled “Canada, AI regulation, and the second reading of the Digital Charter Implementation Act, 2022 (Bill C-27)” offers more comprehensive information about Canada’s legislative progress or lack thereof.

The US is always to be considered in these matters and I have a November 2023 ‘briefing’ by Müge Fazlioglu on the International Association of Privacy Professionals (IAPP) website where she provides a quick overview of the international scene before diving deeper into US AI governance policy through the Barack Obama, Donald Trump, and Joe Biden administrations. There’s also this January 29, 2024 US White House “Fact Sheet: Biden-⁠Harris Administration Announces Key AI Actions Following President Biden’s Landmark Executive Order.”

What about AI and hardware?

A February 15, 2024 news item on ScienceDaily suggests that regulating hardware may be the most effective way of regulating AI,

Chips and datacentres — the ‘compute’ power driving the AI revolution — may be the most effective targets for risk-reducing AI policies as they have to be physically possessed, according to a new report.

A global registry tracking the flow of chips destined for AI supercomputers is one of the policy options highlighted by a major new report calling for regulation of “compute” — the hardware that underpins all AI — to help prevent artificial intelligence misuse and disasters.

Other technical proposals floated by the report include “compute caps” — built-in limits to the number of chips each AI chip can connect with — and distributing a “start switch” for AI training across multiple parties to allow for a digital veto of risky AI before it feeds on data.

The experts point out that powerful computing chips required to drive generative AI models are constructed via highly concentrated supply chains, dominated by just a handful of companies — making the hardware itself a strong intervention point for risk-reducing AI policies.

The report, published 14 February [2024], is authored by nineteen experts and co-led by three University of Cambridge institutes — the Leverhulme Centre for the Future of Intelligence (LCFI), the Centre for the Study of Existential Risk (CSER) and the Bennett Institute for Public Policy — along with OpenAI and the Centre for the Governance of AI.

A February 14, 2024 University of Cambridge press release by Fred Lewsey (also on EurekAlert), which originated the news item, provides more information about the ‘hardware approach to AI regulation’,

“Artificial intelligence has made startling progress in the last decade, much of which has been enabled by the sharp increase in computing power applied to training algorithms,” said Haydn Belfield, a co-lead author of the report from Cambridge’s LCFI. 

“Governments are rightly concerned about the potential consequences of AI, and looking at how to regulate the technology, but data and algorithms are intangible and difficult to control.

“AI supercomputers consist of tens of thousands of networked AI chips hosted in giant data centres often the size of several football fields, consuming dozens of megawatts of power,” said Belfield.

“Computing hardware is visible, quantifiable, and its physical nature means restrictions can be imposed in a way that might soon be nearly impossible with more virtual elements of AI.”

The computing power behind AI has grown exponentially since the “deep learning era” kicked off in earnest, with the amount of “compute” used to train the largest AI models doubling around every six months since 2010. The biggest AI models now use 350 million times more compute than thirteen years ago.

Government efforts across the world over the past year – including the US Executive Order on AI, EU AI Act, China’s Generative AI Regulation, and the UK’s AI Safety Institute – have begun to focus on compute when considering AI governance.

Outside of China, the cloud compute market is dominated by three companies, termed “hyperscalers”: Amazon, Microsoft, and Google. “Monitoring the hardware would greatly help competition authorities in keeping in check the market power of the biggest tech companies, and so opening the space for more innovation and new entrants,” said co-author Prof Diane Coyle from Cambridge’s Bennett Institute. 

The report provides “sketches” of possible directions for compute governance, highlighting the analogy between AI training and uranium enrichment. “International regulation of nuclear supplies focuses on a vital input that has to go through a lengthy, difficult and expensive process,” said Belfield. “A focus on compute would allow AI regulation to do the same.”

Policy ideas are divided into three camps: increasing the global visibility of AI computing; allocating compute resources for the greatest benefit to society; enforcing restrictions on computing power.

For example, a regularly-audited international AI chip registry requiring chip producers, sellers, and resellers to report all transfers would provide precise information on the amount of compute possessed by nations and corporations at any one time.

The report even suggests a unique identifier could be added to each chip to prevent industrial espionage and “chip smuggling”.

“Governments already track many economic transactions, so it makes sense to increase monitoring of a commodity as rare and powerful as an advanced AI chip,” said Belfield. However, the team point out that such approaches could lead to a black market in untraceable “ghost chips”.

Other suggestions to increase visibility – and accountability – include reporting of large-scale AI training by cloud computing providers, and privacy-preserving “workload monitoring” to help prevent an arms race if massive compute investments are made without enough transparency.  

“Users of compute will engage in a mixture of beneficial, benign and harmful activities, and determined groups will find ways to circumvent restrictions,” said Belfield. “Regulators will need to create checks and balances that thwart malicious or misguided uses of AI computing.”

These might include physical limits on chip-to-chip networking, or cryptographic technology that allows for remote disabling of AI chips in extreme circumstances. One suggested approach would require the consent of multiple parties to unlock AI compute for particularly risky training runs, a mechanism familiar from nuclear weapons.

AI risk mitigation policies might see compute prioritised for research most likely to benefit society – from green energy to health and education. This could even take the form of major international AI “megaprojects” that tackle global issues by pooling compute resources.

The report’s authors are clear that their policy suggestions are “exploratory” rather than fully fledged proposals and that they all carry potential downsides, from risks of proprietary data leaks to negative economic impacts and the hampering of positive AI development.

They offer five considerations for regulating AI through compute, including the exclusion of small-scale and non-AI computing, regular revisiting of compute thresholds, and a focus on privacy preservation.

Added Belfield: “Trying to govern AI models as they are deployed could prove futile, like chasing shadows. Those seeking to establish AI regulation should look upstream to compute, the source of the power driving the AI revolution. If compute remains ungoverned it poses severe risks to society.”

You can find the report, “Computing Power and the Governance of Artificial Intelligence” on the University of Cambridge’s Centre for the Study of Existential Risk.

Authors include: Girish Sastry, Lennart Heim, Haydn Belfield, Markus Anderljung, Miles Brundage, Julian Hazell, Cullen O’Keefe, Gillian K. Hadfield, Richard Ngo, Konstantin Pilz, George Gor, Emma Bluemke, Sarah Shoker, Janet Egan, Robert F. Trager, Shahar Avin, Adrian Weller, Yoshua Bengio, and Diane Coyle.

The authors are associated with these companies/agencies: OpenAI, Centre for the Governance of AI (GovAI), Leverhulme Centre for the Future of Intelligence at the Uni. of Cambridge, Oxford Internet Institute, Institute for Law & AI, University of Toronto Vector Institute for AI, Georgetown University, ILINA Program, Harvard Kennedy School (of Government), *AI Governance Institute,* Uni. of Oxford, Centre for the Study of Existential Risk at Uni. of Cambridge, Uni. of Cambridge, Uni. of Montreal / Mila, Bennett Institute for Public Policy at the Uni. of Cambridge.

“The ILINIA program is dedicated to providing an outstanding platform for Africans to learn and work on questions around maximizing wellbeing and responding to global catastrophic risks” according to the organization’s homepage.

*As for the AI Governance Institute, I believe that should be the Centre for the Governance of AI at Oxford University since the associated academic is Robert F. Trager from the University of Oxford.

As the months (years?) fly by, I guess we’ll find out if this hardware approach gains any traction where AI regulation is concerned.

Charles Lieber, nanoscientist, and the US Dept. of Justice

Charles Lieber, professor at Harvard University and one of the world’s leading researchers in nanotechnology went on trial on Tuesday, December 14, 2021.

Accused of hiding his ties to a People’s Republic of China (PRC)-run recruitment programme, Lieber is probably the highest profile academic and one of the few who was not born in China or has familial origins in China to be charged under the auspices of the US Department of Justice’s ‘China Initiative’.

This US National Public Radio (NPR) December 14, 2021 audio excerpt provides a brief summary of the situation by Ryan Lucas,

A December 14, 2021 article by Jess Aloe, Eileen Guo, and Antonio Regalado for the Massachusetts Institute of Technology (MIT) Technology Review lays out the situation in more detail (Note: A link has been removed),

In January of 2020, agents arrived at Harvard University looking for Charles Lieber, a renowned nanotechnology researcher who chaired the school’s department of chemistry and chemical biology. They were there to arrest him on charges of hiding his financial ties with a university in China. By arresting Lieber steps from Harvard Yard, authorities were sending a loud message to the academic community: failing to disclose such links is a serious crime.

Now Lieber is set to go on trial beginning December 14 [2021] in federal court in Boston. He has pleaded not guilty, and hundreds of academics have signed letters of support. In fact, some critics say it’s the Justice Department’s China Initiative—a far-reaching effort started in 2018 to combat Chinese economic espionage and trade-secret theft—that should be on trial, not Lieber. They are calling the prosecutions fundamentally flawed, a witch hunt that misunderstands the open-book nature of basic science and that is selectively destroying scientific careers over financial misdeeds and paperwork errors without proof of actual espionage or stolen technology.

For their part, prosecutors believe they have a tight case. They allege that Lieber was recruited into China’s Thousand Talents Plan—a program aimed at attracting top scientists—and paid handsomely to establish a research laboratory at the Wuhan University of Technology, but hid the affiliation from US grant agencies when asked about it (read a copy of the indictment here). Lieber is facing six felony charges: two counts of making false statements to investigators, two counts of filing a false tax return, and two counts of failing to report a foreign bank account. [emphases mine; Note: None of these charges have been proved in court]

The case against Lieber could be a bellwether for the government, which has several similar cases pending against US professors alleging that they didn’t disclose their China affiliations to granting agencies.

As for the China Initiative (from the MIT Technology Review December 14, 2021 article),

The China Initiative was announced in 2018 by Jeff Sessions, then the Trump administration’s attorney general, as a central component of the administration’s tough stance toward China.

An MIT Technology Review investigation published earlier this month [December 2021] found that the China Initiative is an umbrella for various types of prosecutions somehow connected to China, with targets ranging from a Chinese national who ran a turtle-smuggling ring to state-sponsored hackers believed to be behind some of the biggest data breaches in history. In total, MIT Technology Review identified 77 cases brought under the initiative; of those, a quarter have led to guilty pleas or convictions, but nearly two-thirds remain pending.

The government’s prosecution of researchers like Lieber for allegedly hiding ties to Chinese institutions has been the most controversial, and fastest-growing, aspect of the government’s efforts. In 2020, half of the 31 new cases brought under the China Initiative were cases against scientists or researchers. These cases largely did not accuse the defendants of violating the Economic Espionage Act.

… hundreds of academics across the country, from institutions including Stanford University and Princeton University,signed a letter calling on Attorney General Merrick Garland to end the China Initiative. The initiative, they wrote, has drifted from its original mission of combating Chinese intellectual-property theft and is instead harming American research competitiveness by discouraging scholars from coming to or staying in the US.

Lieber’s case is the second [emphasis mine] China Initiative prosecution of an academic to end up in the courtroom. The only previous person to face trial [emphasis mine] on research integrity charges, University of Tennessee–Knoxville professor Anming Hu, was acquitted of all charges [emphasis mine] by a judge in June [2021] after a deadlocked jury led to a mistrial.

Ken Dilanian wrote an October 19, 2021 article for (US) National Broadcasting Corporation’s (NBC) news online about Hu’s eventual acquittal and about the China Inititative (Note: Dilanian’s timeline for the acquittal differs from the timeline in the MIT Technology Review),

The federal government brought the full measure of its legal might against Anming Hu, a nanotechnology expert at the University of Tennessee.

But the Justice Department’s efforts to convict Hu as part of its program to crack down on illicit technology transfer to China failed — spectacularly. A judge acquitted him last month [September 2021] after a lengthy trial offered little evidence of anything other than a paperwork misunderstanding, according to local newspaper coverage. It was the second trial, after the first ended in a hung jury.

“The China Initiative has turned up very little by way of clear espionage and the transfer of genuinely strategic information to the PRC,” said Robert Daly, a China expert at the Wilson Center, referring to the country by its formal name, the People’s Republic of China. “They are mostly process crimes, disclosure issues. A growing number of voices are calling for an end to the China initiative because it’s seen as discriminatory.”

The China Initiative began under President Donald Trump’s attorney general, Jeff Sessions, in 2018. But concerns about Chinese espionage in the United States — and the transfer of technology to China through business and academic relationships — are bipartisan.

John Demers, who departed in June [2021] as head of the Justice Department’s National Security Division, said in an interview that the problem of technology transfer at universities is real. But he said he also believes conflict of interest and disclosure rules were not rigorously enforced for many years. For that reason, he recommended an amnesty program offering academics with undisclosed foreign ties a chance to come clean and avoid penalties. So far, the Biden administration has not implemented such a program.

When I first featured the Lieber case in a January 28, 2020 posting I was more focused on the financial elements,

ETA January 28, 2020 at 1645 hours: I found a January 28, 2020 article by Antonio Regalado for the MIT Technology Review which provides a few more details about Lieber’s situation,

“…

Big money: According to the charging document, Lieber, starting in 2011,  agreed to help set up a research lab at the Wuhan University of Technology and “make strategic visionary and creative research proposals” so that China could do cutting-edge science.

He was well paid for it. Lieber earned a salary when he visited China worth up to $50,000 per month, as well as $150,000 a year in expenses in addition to research funds. According to the complaint, he got paid by way of a Chinese bank account but also was known to send emails asking for cash instead.

Harvard eventually wised up to the existence of a Wuhan lab using its name and logo, but when administrators confronted Lieber, he lied and said he didn’t know about a formal joint program, according to the government complaint.

This is messy not least because Lieber and the members of his Harvard lab have done some extraordinary work as per my November 15, 2019 (Human-machine interfaces and ultra-small nanoprobes) posting about injectable electronics.

World’s first ever graphene-enhanced sports shoes/sneakers/running shoes/runners/trainers

Regardless of what these shoes are called, they contain, apparently, some graphene. As to why you as a consumer might find that important, here’s more from a June 20, 2018 news item on Nanowerk,

The world’s first-ever sports shoes to utilise graphene – the strongest material on the planet – have been unveiled by The University of Manchester and British brand inov-8.

Collaborating with graphene experts at National Graphene Institute, the brand has been able to develop a graphene-enhanced rubber. They have developed rubber outsoles for running and fitness shoes that in testing have outlasted 1,000 miles and are scientifically proven to be 50% harder wearing.

The National Graphene Institute (located at the UK’s University of Manchester) June 20, 2018 press release, which originated the news item, provides a few details, none of them particularly technical or scientific, no mention of studies, etc.  (Note: Links have been removed),

Graphene is 200 times stronger than steel and at only a single atom thick it is the thinnest possible material, meaning it has many unique properties. inov-8 is the first brand in the world to use the superlative material in sports footwear, with its G-SERIES shoes available to pre-order from June 22nd [2018] ahead of going on sale from July 12th [2018].

The company first announced its intent to revolutionise the sports footwear industry in December last year. Six months of frenzied anticipation later, inov-8 has now removed all secrecy and let the world see these game-changing shoes.

Michael Price, inov-8 product and marketing director, said: “Over the last 18 months we have worked with the National Graphene Institute at The University of Manchester to bring the world’s toughest grip to the sports footwear market.

“Prior to this innovation, off-road runners and fitness athletes had to choose between a sticky rubber that works well in wet or sweaty conditions but wears down quicker and a harder rubber that is more durable but not quite as grippy. Through intensive research, hundreds of prototypes and thousands of hours of testing in both the field and laboratory, athletes now no longer need to compromise.”

Dr Aravind Vijayaraghavan, Reader in Nanomaterials at The University of Manchester, said: “Using graphene we have developed G-SERIES outsole rubbers that are scientifically tested to be 50% stronger, 50% more elastic and 50% harder wearing.

“We are delighted to put graphene on the shelves of 250 retail stores all over the world and make it accessible to everyone. Graphene is a versatile material with limitless potential and in coming years we expect to deliver graphene technologies in composites, coatings and sensors, many of which will further revolutionise sports products.”

The G-SERIES range is made up of three different shoes, each meticulously designed to meet the needs of athletes. THE MUDCLAW G 260 is for running over muddy mountains and obstacle courses, the TERRAULTRA G 260 for running long distances on hard-packed trails and the F-LITE G 290 for crossfitters working out in gyms. Each includes graphene-enhanced rubber outsoles and Kevlar – a material used in bulletproof vests – on the uppers.

Commenting on the patent-pending technology and the collaboration with The University of Manchester, inov-8 CEO Ian Bailey said: “This powerhouse forged in Northern England is going to take the world of sports footwear by storm. We’re combining science and innovation together with entrepreneurial speed and agility to go up against the major sports brands – and we’re going to win.

“We are at the forefront of a graphene sports footwear revolution and we’re not stopping at just rubber outsoles. This is a four-year innovation project which will see us incorporate graphene into 50% of our range and give us the potential to halve the weight of running/fitness shoes without compromising on performance or durability.”

Graphene is produced from graphite, which was first mined in the Lake District fells of Northern England more than 450 years ago. inov-8 too was forged in the same fells, albeit much more recently in 2003. The brand now trades in 68 countries worldwide.

The scientists who first isolated graphene from graphite were awarded the Nobel Prize in 2010. Building on their revolutionary work, a team of over 300 staff at The University of Manchester has pioneered projects into graphene-enhanced prototypes, from sports cars and medical devices to aeroplanes. Now the University can add graphene-enhanced sports footwear to its list of world-firsts.

A picture of the ‘shoes’ has been provided,

Courtesy: National Graphene Institute at University of Manchester

You can find the company inov-8 here. As for more information about their graphene-enhanced show, there’s this,from the company’s ‘graphene webpage‘,

1555Graphite was first mined in the Lake District fells of Northern England

2004Scientists at The University of Manchester isolate graphene from graphite.

2010The Nobel Prize is awarded to the scientists for their ground-breaking experiments with graphene.

2018inov-8 launch the first-ever sports footwear to utilise graphene, delivering the world’s toughest grip.

Ground-breaking technology

One atom thick carbon sheet

200 x stronger than steel

Thin, light, flexible, with limitless potential

inov-8 COLLABORATION WITH THE NATIONAL GRAPHENE INSTITUTE

Previously athletes had to choose between a sticky rubber that works well in wet or sweaty conditions but wears down quicker, and a harder rubber that is more durable but not quite as grippy. Through intensive research, hundreds of prototypes and thousands of hours of testing in both the field and laboratory, athletes now no longer need to compromise. The new rubber we have developed with the National Graphene Institute at The University of Manchester allows us to smash the limits of grip [sic]

The G-SERIES range is made up of three different shoes, each meticulously designed to meet the needs of athletes. Each includes graphene-enhanced rubber outsoles that deliver the world’s toughest grip and Kevlar – a material used in bulletproof vests – on the uppers.

Bulletproof material for running shoes?

As for Canadians eager to try out these shoes, you will likely have to go online or go to the US.  Given how recently (June 19, 2018) this occurred, I’m mentioning the US president’s (Donald Trump) comments that Canadians are notorious for buying shoes in the US and smuggling them across the border back into Canada. (Revelatory information for Canadians everywhere.) His bizarre comments occasioned this explanatory June 19, 2018 article by Jordan Weissmann for Slate.com,

During a characteristically rambling address before the National Federation of Independent Businesses on Tuesday [June 19, 2018], Donald Trump darted off into an odd tangent in which he suggested that Canadians were smuggling shoes across the U.S. border in order to avoid their country’s high tariffs.

There was a story two days ago in a major newspaper talking about people living in Canada coming into the United States and smuggling things back into Canada because the tariffs are so massive. The tariffs to get common items back into Canada are so high that they have to smuggle ‘em in. They buy shoes, then they wear ‘em. They scuff ‘em up. They make ‘em sound old or look old. No, we’re treated horribly. [emphasis mine]

Anyone engaged in this alleged practice would be avoiding payment to the Canadian government. How this constitutes poor treatment of the US government and/or US retailers is a bit a of puzzler.

Getting back to Weissman and his article, he focuses on the source of the US president’s ‘information’.

As for graphene-enhanced ‘shoes’, I hope they are as advertized.

A customized cruise experience with wearable technology (and decreased personal agency?)

The days when you went cruising to ‘get away from it all’ seem to have passed (if they ever really existed) with the introduction of wearable technology that will register your every preference and make life easier according to Cliff Kuang’s Oct. 19, 2017 article for Fast Company,

This month [October 2017], the 141,000-ton Regal Princess will push out to sea after a nine-figure revamp of mind-boggling scale. Passengers won’t be greeted by new restaurants, swimming pools, or onboard activities, but will instead step into a future augured by the likes of Netflix and Uber, where nearly everything is on demand and personally tailored. An ambitious new customization platform has been woven into the ship’s 19 passenger decks: some 7,000 onboard sensors and 4,000 “guest portals” (door-access panels and touch-screen TVs), all of them connected by 75 miles of internal cabling. As the Carnival-owned ship cruises to Nassau, Bahamas, and Grand Turk, its 3,500 passengers will have the option of carrying a quarter-size device, called the Ocean Medallion, which can be slipped into a pocket or worn on the wrist and is synced with a companion app.

The platform will provide a new level of service for passengers; the onboard sensors record their tastes and respond to their movements, and the app guides them around the ship and toward activities aligned with their preferences. Carnival plans to roll out the platform to another seven ships by January 2019. Eventually, the Ocean Medallion could be opening doors, ordering drinks, and scheduling activities for passengers on all 102 of Carnival’s vessels across 10 cruise lines, from the mass-market Princess ships to the legendary ocean liners of Cunard.

Kuang goes on to explain the reasoning behind this innovation,

The Ocean Medallion is Carnival’s attempt to address a problem that’s become increasingly vexing to the $35.5 billion cruise industry. Driven by economics, ships have exploded in size: In 1996, Carnival Destiny was the world’s largest cruise ship, carrying 2,600 passengers. Today, Royal Caribbean’s MS Harmony of the Seas carries up to 6,780 passengers and 2,300 crew. Larger ships expend less fuel per passenger; the money saved can then go to adding more amenities—which, in turn, are geared to attracting as many types of people as possible. Today on a typical ship you can do practically anything—from attending violin concertos to bungee jumping. And that’s just onboard. Most of a cruise is spent in port, where each day there are dozens of experiences available. This avalanche of choice can bury a passenger. It has also made personalized service harder to deliver. …

Kuang also wrote this brief description of how the technology works from the passenger’s perspective in an Oct. 19, 2017 item for Fast Company,

1. Pre-trip

On the web or on the app, you can book experiences, log your tastes and interests, and line up your days. That data powers the recommendations you’ll see. The Ocean Medallion arrives by mail and becomes the key to ship access.

2. Stateroom

When you draw near, your cabin-room door unlocks without swiping. The room’s unique 43-inch TV, which doubles as a touch screen, offers a range of Carnival’s bespoke travel shows. Whatever you watch is fed into your excursion suggestions.

3. Food

When you order something, sensors detect where you are, allowing your server to find you. Your allergies and preferences are also tracked, and shape the choices you’re offered. In all, the back-end data has 45,000 allergens tagged and manages 250,000 drink combinations.

4. Activities

The right algorithms can go beyond suggesting wines based on previous orders. Carnival is creating a massive semantic database, so if you like pricey reds, you’re more apt to be guided to a violin concerto than a limbo competition. Your onboard choices—the casino, the gym, the pool—inform your excursion recommendations.

In Kuang’s Oct. 19, 2017 article he notes that the cruise ship line is putting a lot of effort into retraining their staff and emphasizing the ‘soft’ skills that aren’t going to be found in this iteration of the technology. No mention is made of whether or not there will be reductions in the number of staff members on this cruise ship nor is the possibility that ‘soft’ skills may in the future be incorporated into this technological marvel.

Personalization/customization is increasingly everywhere

How do you feel about customized news feeds? As it turns out, this is not a rhetorical question as Adrienne LaFrance notes in her Oct. 19, 2017 article for The Atlantic (Note: Links have been removed),

Today, a Google search for news runs through the same algorithmic filtration system as any other Google search: A person’s individual search history, geographic location, and other demographic information affects what Google shows you. Exactly how your search results differ from any other person’s is a mystery, however. Not even the computer scientists who developed the algorithm could precisely reverse engineer it, given the fact that the same result can be achieved through numerous paths, and that ranking factors—deciding which results show up first—are constantly changing, as are the algorithms themselves.

We now get our news in real time, on demand, tailored to our interests, across multiple platforms, without knowing just how much is actually personalized. It was technology companies like Google and Facebook, not traditional newsrooms, that made it so. But news organizations are increasingly betting that offering personalized content can help them draw audiences to their sites—and keep them coming back.

Personalization extends beyond how and where news organizations meet their readers. Already, smartphone users can subscribe to push notifications for the specific coverage areas that interest them. On Facebook, users can decide—to some extent—which organizations’ stories they would like to appear in their news feeds. At the same time, devices and platforms that use machine learning to get to know their users will increasingly play a role in shaping ultra-personalized news products. Meanwhile, voice-activated artificially intelligent devices, such as Google Home and Amazon Echo, are poised to redefine the relationship between news consumers and the news [emphasis mine].

While news personalization can help people manage information overload by making individuals’ news diets unique, it also threatens to incite filter bubbles and, in turn, bias [emphasis mine]. This “creates a bit of an echo chamber,” says Judith Donath, author of The Social Machine: Designs for Living Online and a researcher affiliated with Harvard University ’s Berkman Klein Center for Internet and Society. “You get news that is designed to be palatable to you. It feeds into people’s appetite of expecting the news to be entertaining … [and] the desire to have news that’s reinforcing your beliefs, as opposed to teaching you about what’s happening in the world and helping you predict the future better.”

Still, algorithms have a place in responsible journalism. “An algorithm actually is the modern editorial tool,” says Tamar Charney, the managing editor of NPR One, the organization’s customizable mobile-listening app. A handcrafted hub for audio content from both local and national programs as well as podcasts from sources other than NPR, NPR One employs an algorithm to help populate users’ streams with content that is likely to interest them. But Charney assures there’s still a human hand involved: “The whole editorial vision of NPR One was to take the best of what humans do and take the best of what algorithms do and marry them together.” [emphasis mine]

The skimming and diving Charney describes sounds almost exactly like how Apple and Google approach their distributed-content platforms. With Apple News, users can decide which outlets and topics they are most interested in seeing, with Siri offering suggestions as the algorithm gets better at understanding your preferences. Siri now has have help from Safari. The personal assistant can now detect browser history and suggest news items based on what someone’s been looking at—for example, if someone is searching Safari for Reykjavík-related travel information, they will then see Iceland-related news on Apple News. But the For You view of Apple News isn’t 100 percent customizable, as it still spotlights top stories of the day, and trending stories that are popular with other users, alongside those curated just for you.

Similarly, with Google’s latest update to Google News, readers can scan fixed headlines, customize sidebars on the page to their core interests and location—and, of course, search. The latest redesign of Google News makes it look newsier than ever, and adds to many of the personalization features Google first introduced in 2010. There’s also a place where you can preprogram your own interests into the algorithm.

Google says this isn’t an attempt to supplant news organizations, nor is it inspired by them. The design is rather an embodiment of Google’s original ethos, the product manager for Google News Anand Paka says: “Just due to the deluge of information, users do want ways to control information overload. In other words, why should I read the news that I don’t care about?” [emphasis mine]

Meanwhile, in May [2017?], Google briefly tested a personalized search filter that would dip into its trove of data about users with personal Google and Gmail accounts and include results exclusively from their emails, photos, calendar items, and other personal data related to their query. [emphasis mine] The “personal” tab was supposedly “just an experiment,” a Google spokesperson said, and the option was temporarily removed, but seems to have rolled back out for many users as of August [2017?].

Now, Google, in seeking to settle a class-action lawsuit alleging that scanning emails to offer targeted ads amounts to illegal wiretapping, is promising that for the next three years it won’t use the content of its users’ emails to serve up targeted ads in Gmail. The move, which will go into effect at an unspecified date, doesn’t mean users won’t see ads, however. Google will continue to collect data from users’ search histories, YouTube, and Chrome browsing habits, and other activity.

The fear that personalization will encourage filter bubbles by narrowing the selection of stories is a valid one, especially considering that the average internet user or news consumer might not even be aware of such efforts. Elia Powers, an assistant professor of journalism and news media at Towson University in Maryland, studied the awareness of news personalization among students after he noticed those in his own classes didn’t seem to realize the extent to which Facebook and Google customized users’ results. “My sense is that they didn’t really understand … the role that people that were curating the algorithms [had], how influential that was. And they also didn’t understand that they could play a pretty active role on Facebook in telling Facebook what kinds of news they want them to show and how to prioritize [content] on Google,” he says.

The results of Powers’s study, which was published in Digital Journalism in February [2017], showed that the majority of students had no idea that algorithms were filtering the news content they saw on Facebook and Google. When asked if Facebook shows every news item, posted by organizations or people, in a users’ newsfeed, only 24 percent of those surveyed were aware that Facebook prioritizes certain posts and hides others. Similarly, only a quarter of respondents said Google search results would be different for two different people entering the same search terms at the same time. [emphasis mine; Note: Respondents in this study were students.]

This, of course, has implications beyond the classroom, says Powers: “People as news consumers need to be aware of what decisions are being made [for them], before they even open their news sites, by algorithms and the people behind them, and also be able to understand how they can counter the effects or maybe even turn off personalization or make tweaks to their feeds or their news sites so they take a more active role in actually seeing what they want to see in their feeds.”

On Google and Facebook, the algorithm that determines what you see is invisible. With voice-activated assistants, the algorithm suddenly has a persona. “We are being trained to have a relationship with the AI,” says Amy Webb, founder of the Future Today Institute and an adjunct professor at New York University Stern School of Business. “This is so much more catastrophically horrible for news organizations than the internet. At least with the internet, I have options. The voice ecosystem is not built that way. It’s being built so I just get the information I need in a pleasing way.”

LaFrance’s article is thoughtful and well worth reading in its entirety. Now, onto some commentary.

Loss of personal agency

I have been concerned for some time about the increasingly dull results I get from a Google search and while I realize the company has been gathering information about me via my searches , supposedly in service of giving me better searches, I had no idea how deeply the company can mine for personal data. It makes me wonder what would happen if Google and Facebook attempted a merger.

More cogently, I rather resent the search engines and artificial intelligence agents (e.g. Facebook bots) which have usurped my role as the arbiter of what interests me, in short, my increasing loss of personal agency.

I’m also deeply suspicious of what these companies are going to do with my data. Will it be used to manipulate me in some way? Presumably, the data will be sold and used for some purpose. In the US, they have married electoral data with consumer data as Brent Bambury notes in an Oct. 13, 2017 article for his CBC (Canadian Broadcasting Corporation) Radio show,

How much of your personal information circulates in the free-market ether of metadata? It could be more than you imagine, and it might be enough to let others change the way you vote.

A data firm that specializes in creating psychological profiles of voters claims to have up to 5,000 data points on 220 million Americans. Cambridge Analytica has deep ties to the American right and was hired by the campaigns of Ben Carson, Ted Cruz and Donald Trump.

During the U.S. election, CNN called them “Donald Trump’s mind readers” and his secret weapon.

David Carroll is a Professor at the Parsons School of Design in New York City. He is one of the millions of Americans profiled by Cambridge Analytica and he’s taking legal action to find out where the company gets its masses of data and how they use it to create their vaunted psychographic profiles of voters.

On Day 6 [Banbury’s CBC radio programme], he explained why that’s important.

“They claim to have figured out how to project our voting behavior based on our consumer behavior. So it’s important for citizens to be able to understand this because it would affect our ability to understand how we’re being targeted by campaigns and how the messages that we’re seeing on Facebook and television are being directed at us to manipulate us.” [emphasis mine]

The parent company of Cambridge Analytica, SCL Group, is a U.K.-based data operation with global ties to military and political activities. David Carroll says the potential for sharing personal data internationally is a cause for concern.

“It’s the first time that this kind of data is being collected and transferred across geographic boundaries,” he says.

But that also gives Carroll an opening for legal action. An individual has more rights to access their personal information in the U.K., so that’s where he’s launching his lawsuit.

Reports link Michael Flynn, briefly Trump’s National Security Adviser, to SCL Group and indicate that former White House strategist Steve Bannon is a board member of Cambridge Analytica. Billionaire Robert Mercer, who has underwritten Bannon’s Breitbart operations and is a major Trump donor, also has a significant stake in Cambridge Analytica.

In the world of data, Mercer’s credentials are impeccable.

“He is an important contributor to the field of artificial intelligence,” says David Carroll.

“His work at IBM is seminal and really important in terms of the foundational ideas that go into big data analytics, so the relationship between AI and big data analytics. …

Banbury’s piece offers a lot more, including embedded videos, than I’ve not included in that excerpt but I also wanted to include some material from Carole Cadwalladr’s Oct. 1, 2017 Guardian article about Carroll and his legal fight in the UK,

“There are so many disturbing aspects to this. One of the things that really troubles me is how the company can buy anonymous data completely legally from all these different sources, but as soon as it attaches it to voter files, you are re-identified. It means that every privacy policy we have ignored in our use of technology is a broken promise. It would be one thing if this information stayed in the US, if it was an American company and it only did voter data stuff.”

But, he [Carroll] argues, “it’s not just a US company and it’s not just a civilian company”. Instead, he says, it has ties with the military through SCL – “and it doesn’t just do voter targeting”. Carroll has provided information to the Senate intelligence committee and believes that the disclosures mandated by a British court could provide evidence helpful to investigators.

Frank Pasquale, a law professor at the University of Maryland, author of The Black Box Society and a leading expert on big data and the law, called the case a “watershed moment”.

“It really is a David and Goliath fight and I think it will be the model for other citizens’ actions against other big corporations. I think we will look back and see it as a really significant case in terms of the future of algorithmic accountability and data protection. …

Nobody is discussing personal agency directly but if you’re only being exposed to certain kinds of messages then your personal agency has been taken from you. Admittedly we don’t have complete personal agency in our lives but AI along with the data gathering done online and increasingly with wearable and smart technology means that another layer of control has been added to your life and it is largely invisible. After all, the students in Elia Powers’ study didn’t realize their news feeds were being pre-curated.

Limitless energy and the International Thermonuclear Experimental Reactor (ITER)

Over 30 years in the dreaming, the International Thermonuclear Experimental Reactor (ITER) is now said to be 1/2 way to completing construction. A December 6, 2017 ITER press release (received via email) makes the joyful announcement,

WORLD’S MOST COMPLEX MACHINE IS 50 PERCENT COMPLETED
ITER is proving that fusion is the future source of clean, abundant, safe and economic energy_

The International Thermonuclear Experimental Reactor (ITER), a project to prove that fusion power can be produced on a commercial scale and is sustainable, is now 50 percent built to initial operation. Fusion is the same energy source from the Sun that gives the Earth its light and warmth.

ITER will use hydrogen fusion, controlled by superconducting magnets, to produce massive heat energy. In the commercial machines that will follow, this heat will drive turbines to produce electricity with these positive benefits:

* Fusion energy is carbon-free and environmentally sustainable, yet much more powerful than fossil fuels. A pineapple-sized amount of hydrogen offers as much fusion energy as 10,000 tons of coal.

* ITER uses two forms of hydrogen fuel: deuterium, which is easily extracted from seawater; and tritium, which is bred from lithium inside the fusion reactor. The supply of fusion fuel for industry and megacities is abundant, enough for millions of years.

* When the fusion reaction is disrupted, the reactor simply shuts down-safely and without external assistance. Tiny amounts of fuel are used, about 2-3 grams at a time; so there is no physical possibility of a meltdown accident.

* Building and operating a fusion power plant is targeted to be comparable to the cost of a fossil fuel or nuclear fission plant. But unlike today’s nuclear plants, a fusion plant will not have the costs of high-level radioactive waste disposal. And unlike fossil fuel plants,
fusion will not have the environmental cost of releasing CO2 and other pollutants.

ITER is the most complex science project in human history. The hydrogen plasma will be heated to 150 million degrees Celsius, ten times hotter than the core of the Sun, to enable the fusion reaction. The process happens in a donut-shaped reactor, called a tokamak(*), which is surrounded by giant magnets that confine and circulate the superheated, ionized plasma, away from the metal walls. The superconducting magnets must be cooled to minus 269°C, as cold as interstellar space.

The ITER facility is being built in Southern France by a scientific partnership of 35 countries. ITER’s specialized components, roughly 10 million parts in total, are being manufactured in industrial facilities all over the world. They are subsequently shipped to the ITER worksite, where they must be assembled, piece-by-piece, into the final machine.

Each of the seven ITER members-the European Union, China, India, Japan, Korea, Russia, and the United States-is fabricating a significant portion of the machine. This adds to ITER’s complexity.

In a message dispatched on December 1 [2017] to top-level officials in ITER member governments, the ITER project reported that it had completed 50 percent of the “total construction work scope through First Plasma” (**). First Plasma, scheduled for December 2025, will be the first stage of operation for ITER as a functional machine.

“The stakes are very high for ITER,” writes Bernard Bigot, Ph.D., Director-General of ITER. “When we prove that fusion is a viable energy source, it will eventually replace burning fossil fuels, which are non-renewable and non-sustainable. Fusion will be complementary with wind, solar, and other renewable energies.

“ITER’s success has demanded extraordinary project management, systems engineering, and almost perfect integration of our work.

“Our design has taken advantage of the best expertise of every member’s scientific and industrial base. No country could do this alone. We are all learning from each other, for the world’s mutual benefit.”

The ITER 50 percent milestone is getting significant attention.

“We are fortunate that ITER and fusion has had the support of world leaders, historically and currently,” says Director-General Bigot. “The concept of the ITER project was conceived at the 1985 Geneva Summit between Ronald Reagan and Mikhail Gorbachev. When the ITER Agreement was signed in 2006, it was strongly supported by leaders such as French President Jacques Chirac, U.S. President George W. Bush, and Indian Prime Minister Manmohan Singh.

“More recently, President Macron and U.S. President Donald Trump exchanged letters about ITER after their meeting this past July. One month earlier, President Xi Jinping of China hosted Russian President Vladimir Putin and other world leaders in a showcase featuring ITER and fusion power at the World EXPO in Astana, Kazakhstan.

“We know that other leaders have been similarly involved behind the scenes. It is clear that each ITER member understands the value and importance of this project.”

Why use this complex manufacturing arrangement?

More than 80 percent of the cost of ITER, about $22 billion or EUR18 billion, is contributed in the form of components manufactured by the partners. Many of these massive components of the ITER machine must be precisely fitted-for example, 17-meter-high magnets with less than a millimeter of tolerance. Each component must be ready on time to fit into the Master Schedule for machine assembly.

Members asked for this deal for three reasons. First, it means that most of the ITER costs paid by any member are actually paid to that member’s companies; the funding stays in-country. Second, the companies working on ITER build new industrial expertise in major fields-such as electromagnetics, cryogenics, robotics, and materials science. Third, this new expertise leads to innovation and spin-offs in other fields.

For example, expertise gained working on ITER’s superconducting magnets is now being used to map the human brain more precisely than ever before.

The European Union is paying 45 percent of the cost; China, India, Japan, Korea, Russia, and the United States each contribute 9 percent equally. All members share in ITER’s technology; they receive equal access to the intellectual property and innovation that comes from building ITER.

When will commercial fusion plants be ready?

ITER scientists predict that fusion plants will start to come on line as soon as 2040. The exact timing, according to fusion experts, will depend on the level of public urgency and political will that translates to financial investment.

How much power will they provide?

The ITER tokamak will produce 500 megawatts of thermal power. This size is suitable for studying a “burning” or largely self-heating plasma, a state of matter that has never been produced in a controlled environment on Earth. In a burning plasma, most of the plasma heating comes from the fusion reaction itself. Studying the fusion science and technology at ITER’s scale will enable optimization of the plants that follow.

A commercial fusion plant will be designed with a slightly larger plasma chamber, for 10-15 times more electrical power. A 2,000-megawatt fusion electricity plant, for example, would supply 2 million homes.

How much would a fusion plant cost and how many will be needed?

The initial capital cost of a 2,000-megawatt fusion plant will be in the range of $10 billion. These capital costs will be offset by extremely low operating costs, negligible fuel costs, and infrequent component replacement costs over the 60-year-plus life of the plant. Capital costs will decrease with large-scale deployment of fusion plants.

At current electricity usage rates, one fusion plant would be more than enough to power a city the size of Washington, D.C. The entire D.C. metropolitan area could be powered with four fusion plants, with zero carbon emissions.

“If fusion power becomes universal, the use of electricity could be expanded greatly, to reduce the greenhouse gas emissions from transportation, buildings and industry,” predicts Dr. Bigot. “Providing clean, abundant, safe, economic energy will be a miracle for our planet.”

*     *     *

FOOTNOTES:

* “Tokamak” is a word of Russian origin meaning a toroidal or donut-shaped magnetic chamber. Tokamaks have been built and operated for the past six decades. They are today’s most advanced fusion device design.

** “Total construction work scope,” as used in ITER’s project performance metrics, includes design, component manufacturing, building construction, shipping and delivery, assembly, and installation.

It is an extraordinary project on many levels as Henry Fountain notes in a March 27, 2017 article for the New York Times (Note: Links have been removed),

At a dusty construction site here amid the limestone ridges of Provence, workers scurry around immense slabs of concrete arranged in a ring like a modern-day Stonehenge.

It looks like the beginnings of a large commercial power plant, but it is not. The project, called ITER, is an enormous, and enormously complex and costly, physics experiment. But if it succeeds, it could determine the power plants of the future and make an invaluable contribution to reducing planet-warming emissions.

ITER, short for International Thermonuclear Experimental Reactor (and pronounced EAT-er), is being built to test a long-held dream: that nuclear fusion, the atomic reaction that takes place in the sun and in hydrogen bombs, can be controlled to generate power.

ITER will produce heat, not electricity. But if it works — if it produces more energy than it consumes, which smaller fusion experiments so far have not been able to do — it could lead to plants that generate electricity without the climate-affecting carbon emissions of fossil-fuel plants or most of the hazards of existing nuclear reactors that split atoms rather than join them.

Success, however, has always seemed just a few decades away for ITER. The project has progressed in fits and starts for years, plagued by design and management problems that have led to long delays and ballooning costs.

ITER is moving ahead now, with a director-general, Bernard Bigot, who took over two years ago after an independent analysis that was highly critical of the project. Dr. Bigot, who previously ran France’s atomic energy agency, has earned high marks for resolving management problems and developing a realistic schedule based more on physics and engineering and less on politics.

The site here is now studded with tower cranes as crews work on the concrete structures that will support and surround the heart of the experiment, a doughnut-shaped chamber called a tokamak. This is where the fusion reactions will take place, within a plasma, a roiling cloud of ionized atoms so hot that it can be contained only by extremely strong magnetic fields.

Here’s a rendering of the proposed reactor,

Source: ITER Organization

It seems the folks at the New York Times decided to remove the notes which help make sense of this image. However, it does get the idea across.

If I read the article rightly, the official cost in March 2017 was around 22 B Euros and more will likely be needed. You can read Fountain’s article for more information about fusion and ITER or go to the ITER website.

I could have sworn a local (Vancouver area) company called General Fusion was involved in the ITER project but I can’t track down any sources for confirmation. The sole connection I could find is in a documentary about fusion technology,

Here’s a little context for the film from a July 4, 2017 General Fusion news release (Note: A link has been removed),

A new documentary featuring General Fusion has captured the exciting progress in fusion across the public and private sectors.

Let There Be Light made its international premiere at the South By Southwest (SXSW) music and film festival in March [2017] to critical acclaim. The film was quickly purchased by Amazon Video, where it will be available for more than 70 million users to stream.

Let There Be Light follows scientists at General Fusion, ITER and Lawrenceville Plasma Physics in their pursuit of a clean, safe and abundant source of energy to power the world.

The feature length documentary has screened internationally across Europe and North America. Most recently it was shown at the Hot Docs film festival in Toronto, where General Fusion founder and Chief Scientist Dr. Michel Laberge joined fellow fusion physicist Dr. Mark Henderson from ITER at a series of Q&A panels with the filmmakers.

Laberge and Henderson were also interviewed by the popular CBC radio science show Quirks and Quarks, discussing different approaches to fusion, its potential benefits, and the challenges it faces.

It is yet to be confirmed when the film will be release for streaming, check Amazon Video for details.

You can find out more about General Fusion here.

Brief final comment

ITER is a breathtaking effort but if you’ve read about other large scale projects such as building a railway across the Canadian Rocky Mountains, establishing telecommunications in an  astonishing number of countries around the world, getting someone to the moon, eliminating small pox, building the pyramids, etc., it seems standard operating procedure both for the successes I’ve described and for the failures we’ve forgotten. Where ITER will finally rest on the continuum between success and failure is yet to be determined but the problems experienced so far are not necessarily a predictor.

I wish the engineers, scientists, visionaries, and others great success with finding better ways to produce energy.

Canadian science policy news and doings (also: some US science envoy news)

I have a couple of notices from the Canadian Science Policy Centre (CSPC), a twitter feed, and an article in online magazine to thank for this bumper crop of news.

 Canadian Science Policy Centre: the conference

The 2017 Canadian Science Policy Conference to be held Nov. 1 – 3, 2017 in Ottawa, Ontario for the third year in a row has a super saver rate available until Sept. 3, 2017 according to an August 14, 2017 announcement (received via email).

Time is running out, you have until September 3rd until prices go up from the SuperSaver rate.

Savings off the regular price with the SuperSaver rate:
Up to 26% for General admission
Up to 29% for Academic/Non-Profit Organizations
Up to 40% for Students and Post-Docs

Before giving you the link to the registration page and assuming that you might want to check out what is on offer at the conference, here’s a link to the programme. They don’t seem to have any events celebrating Canada’s 150th anniversary although they do have a session titled, ‘The Next 150 years of Science in Canada: Embedding Equity, Delivering Diversity/Les 150 prochaine années de sciences au Canada:  Intégrer l’équité, promouvoir la diversité‘,

Enhancing equity, diversity, and inclusivity (EDI) in science, technology, engineering and math (STEM) has been described as being a human rights issue and an economic development issue by various individuals and organizations (e.g. OECD). Recent federal policy initiatives in Canada have focused on increasing participation of women (a designated under-represented group) in science through increased reporting, program changes, and institutional accountability. However, the Employment Equity Act requires employers to act to ensure the full representation of the three other designated groups: Aboriginal peoples, persons with disabilities and members of visible minorities. Significant structural and systemic barriers to full participation and employment in STEM for members of these groups still exist in Canadian institutions. Since data support the positive role of diversity in promoting innovation and economic development, failure to capture the full intellectual capacity of a diverse population limits provincial and national potential and progress in many areas. A diverse international panel of experts from designated groups will speak to the issue of accessibility and inclusion in STEM. In addition, the discussion will focus on evidence-based recommendations for policy initiatives that will promote full EDI in science in Canada to ensure local and national prosperity and progress for Canada over the next 150 years.

There’s also this list of speakers . Curiously, I don’t see Kirsty Duncan, Canada’s Minister of Science on the list, nor do I see any other politicians in the banner for their conference website  This divergence from the CSPC’s usual approach to promoting the conference is interesting.

Moving onto the conference, the organizers have added two panels to the programme (from the announcement received via email),

Friday, November 3, 2017
10:30AM-12:00PM
Open Science and Innovation
Organizer: Tiberius Brastaviceanu
Organization: ACES-CAKE

10:30AM- 12:00PM
The Scientific and Economic Benefits of Open Science
Organizer: Arij Al Chawaf
Organization: Structural Genomics

I think this is the first time there’s been a ‘Tiberius’ on this blog and teamed with the organization’s name, well, I just had to include it.

Finally, here’s the link to the registration page and a page that details travel deals.

Canadian Science Policy Conference: a compendium of documents and articles on Canada’s Chief Science Advisor and Ontario’s Chief Scientist and the pre-2018 budget submissions

The deadline for applications for the Chief Science Advisor position was extended to Feb. 2017 and so far, there’s no word as to whom it might be. Perhaps Minister of Science Kirsty Duncan wants to make a splash with a surprise announcement at the CSPC’s 2017 conference? As for Ontario’s Chief Scientist, this move will make province the third (?) to have a chief scientist, after Québec and Alberta. There is apparently one in Alberta but there doesn’t seem to be a government webpage and his LinkedIn profile doesn’t include this title. In any event, Dr. Fred Wrona is mentioned as the Alberta’s Chief Scientist in a May 31, 2017 Alberta government announcement. *ETA Aug. 25, 2017: I missed the Yukon, which has a Senior Science Advisor. The position is currently held by Dr. Aynslie Ogden.*

Getting back to the compendium, here’s the CSPC’s A Comprehensive Collection of Publications Regarding Canada’s Federal Chief Science Advisor and Ontario’s Chief Scientist webpage. Here’s a little background provided on the page,

On June 2nd, 2017, the House of Commons Standing Committee on Finance commenced the pre-budget consultation process for the 2018 Canadian Budget. These consultations provide Canadians the opportunity to communicate their priorities with a focus on Canadian productivity in the workplace and community in addition to entrepreneurial competitiveness. Organizations from across the country submitted their priorities on August 4th, 2017 to be selected as witness for the pre-budget hearings before the Committee in September 2017. The process will result in a report to be presented to the House of Commons in December 2017 and considered by the Minister of Finance in the 2018 Federal Budget.

NEWS & ANNOUNCEMENT

House of Commons- PRE-BUDGET CONSULTATIONS IN ADVANCE OF THE 2018 BUDGET

https://www.ourcommons.ca/Committees/en/FINA/StudyActivity?studyActivityId=9571255

CANADIANS ARE INVITED TO SHARE THEIR PRIORITIES FOR THE 2018 FEDERAL BUDGET

https://www.ourcommons.ca/DocumentViewer/en/42-1/FINA/news-release/9002784

The deadline for pre-2018 budget submissions was Aug. 4, 2017 and they haven’t yet scheduled any meetings although they are to be held in September. (People can meet with the Standing Committee on Finance in various locations across Canada to discuss their submissions.) I’m not sure where the CSPC got their list of ‘science’ submissions but it’s definitely worth checking as there are some odd omissions such as TRIUMF (Canada’s National Laboratory for Particle and Nuclear Physics)), Genome Canada, the Pan-Canadian Artificial Intelligence Strategy, CIFAR (Canadian Institute for Advanced Research), the Perimeter Institute, Canadian Light Source, etc.

Twitter and the Naylor Report under a microscope

This news came from University of British Columbia President Santa Ono’s twitter feed,

 I will join Jon [sic] Borrows and Janet Rossant on Sept 19 in Ottawa at a Mindshare event to discuss the importance of the Naylor Report

The Mindshare event Ono is referring to is being organized by Universities Canada (formerly the Association of Universities and Colleges of Canada) and the Institute for Research on Public Policy. It is titled, ‘The Naylor report under the microscope’. Here’s more from the event webpage,

Join Universities Canada and Policy Options for a lively discussion moderated by editor-in-chief Jennifer Ditchburn on the report from the Fundamental Science Review Panel and why research matters to Canadians.

Moderator

Jennifer Ditchburn, editor, Policy Options.

Jennifer Ditchburn

Editor-in-chief, Policy Options

Jennifer Ditchburn is the editor-in-chief of Policy Options, the online policy forum of the Institute for Research on Public Policy.  An award-winning parliamentary correspondent, Jennifer began her journalism career at the Canadian Press in Montreal as a reporter-editor during the lead-up to the 1995 referendum.  From 2001 and 2006 she was a national reporter with CBC TV on Parliament Hill, and in 2006 she returned to the Canadian Press.  She is a three-time winner of a National Newspaper Award:  twice in the politics category, and once in the breaking news category. In 2015 she was awarded the prestigious Charles Lynch Award for outstanding coverage of national issues. Jennifer has been a frequent contributor to television and radio public affairs programs, including CBC’s Power and Politics, the “At Issue” panel, and The Current. She holds a bachelor of arts from Concordia University, and a master of journalism from Carleton University.

@jenditchburn

Tuesday, September 19, 2017

 12-2 pm

Fairmont Château Laurier,  Laurier  Room
 1 Rideau Street, Ottawa

 rsvp@univcan.ca

I can’t tell if they’re offering lunch or if there is a cost associated with this event so you may want to contact the organizers.

As for the Naylor report, I posted a three-part series on June 8, 2017, which features my comments and the other comments I was able to find on the report:

INVESTING IN CANADA’S FUTURE; Strengthening the Foundations of Canadian Research (Review of fundamental research final report): 1 of 3

INVESTING IN CANADA’S FUTURE; Strengthening the Foundations of Canadian Research (Review of fundamental research final report): 2 of 3

INVESTING IN CANADA’S FUTURE; Strengthening the Foundations of Canadian Research (Review of fundamental research final report): 3 of 3

One piece not mentioned in my three-part series is Paul Wells’ provocatively titled June 29, 2017 article for MacLean’s magazine, Why Canadian scientists aren’t happy (Note: Links have been removed),

Much hubbub this morning over two interviews Kirsty Duncan, the science minister, has given the papers. The subject is Canada’s Fundamental Science Review, commonly called the Naylor Report after David Naylor, the former University of Toronto president who was its main author.

Other authors include BlackBerry founder Mike Lazaridis, who has bankrolled much of the Waterloo renaissance, and Canadian Nobel physicist Arthur McDonald. It’s as blue-chip as a blue-chip panel could be.

Duncan appointed the panel a year ago. It’s her panel, delivered by her experts. Why does it not seem to be… getting anywhere? Why does it seem to have no champion in government? Therein lies a tale.

Note, first, that Duncan’s interviews—her first substantive comment on the report’s recommendations!—come nearly three months after its April release, which in turn came four months after Duncan asked Naylor to deliver his report, last December. (By March I had started to make fun of the Trudeau government in print for dragging its heels on the report’s release. That column was not widely appreciated in the government, I’m told.)

Anyway, the report was released, at an event attended by no representative of the Canadian government. Here’s the gist of what I wrote at the time:

 

Naylor’s “single most important recommendation” is a “rapid increase” in federal spending on “independent investigator-led research” instead of the “priority-driven targeted research” that two successive federal governments, Trudeau’s and Stephen Harper’s, have preferred in the last 8 or 10 federal budgets.

In English: Trudeau has imitated Harper in favouring high-profile, highly targeted research projects, on areas of study selected by political staffers in Ottawa, that are designed to attract star researchers from outside Canada so they can bolster the image of Canada as a research destination.

That’d be great if it wasn’t achieved by pruning budgets for the less spectacular research that most scientists do.

Naylor has numbers. “Between 2007-08 and 2015-16, the inflation-adjusted budgetary envelope for investigator-led research fell by 3 per cent while that for priority-driven research rose by 35 per cent,” he and his colleagues write. “As the number of researchers grew during this period, the real resources available per active researcher to do investigator-led research declined by about 35 per cent.”

And that’s not even taking into account the way two new programs—the $10-million-per-recipient Canada Excellence Research Chairs and the $1.5 billion Canada First Research Excellence Fund—are “further concentrating resources in the hands of smaller numbers of individuals and institutions.”

That’s the context for Duncan’s remarks. In the Globe, she says she agrees with Naylor on “the need for a research system that promotes equity and diversity, provides a better entry for early career researchers and is nimble in response to new scientific opportunities.” But she also “disagreed” with the call for a national advisory council that would give expert advice on the government’s entire science, research and innovation policy.

This is an asinine statement. When taking three months to read a report, it’s a good idea to read it. There is not a single line in Naylor’s overlong report that calls for the new body to make funding decisions. Its proposed name is NACRI, for National Advisory Council on Research and Innovation. A for Advisory. Its responsibilities, listed on Page 19 if you’re reading along at home, are restricted to “advice… evaluation… public reporting… advice… advice.”

Duncan also didn’t promise to meet Naylor’s requested funding levels: $386 million for research in the first year, growing to $1.3 billion in new money in the fourth year. That’s a big concern for researchers, who have been warning for a decade that two successive government’s—Harper’s and Trudeau’s—have been more interested in building new labs than in ensuring there’s money to do research in them.

The minister has talking points. She gave the same answer to both reporters about whether Naylor’s recommendations will be implemented in time for the next federal budget. “It takes time to turn the Queen Mary around,” she said. Twice. I’ll say it does: She’s reacting three days before Canada Day to a report that was written before Christmas. Which makes me worry when she says elected officials should be in charge of being nimble.

Here’s what’s going on.

The Naylor report represents Canadian research scientists’ side of a power struggle. The struggle has been continuing since Jean Chrétien left office. After early cuts, he presided for years over very large increases to the budgets of the main science granting councils. But since 2003, governments have preferred to put new funding dollars to targeted projects in applied sciences. …

Naylor wants that trend reversed, quickly. He is supported in that call by a frankly astonishingly broad coalition of university administrators and working researchers, who until his report were more often at odds. So you have the group representing Canada’s 15 largest research universities and the group representing all universities and a new group representing early-career researchers and, as far as I can tell, every Canadian scientist on Twitter. All backing Naylor. All fundamentally concerned that new money for research is of no particular interest if it does not back the best science as chosen by scientists, through peer review.

The competing model, the one preferred by governments of all stripes, might best be called superclusters. Very large investments into very large projects with loosely defined scientific objectives, whose real goal is to retain decorated veteran scientists and to improve the Canadian high-tech industry. Vast and sprawling labs and tech incubators, cabinet ministers nodding gravely as world leaders in sexy trendy fields sketch the golden path to Jobs of Tomorrow.

You see the imbalance. On one side, ribbons to cut. On the other, nerds experimenting on tapeworms. Kirsty Duncan, a shaky political performer, transparently a junior minister to the supercluster guy, with no deputy minister or department reporting to her, is in a structurally weak position: her title suggests she’s science’s emissary to the government, but she is not equipped to be anything more than government’s emissary to science.

A government that consistently buys into the market for intellectual capital at the very top of the price curve is a factory for producing white elephants. But don’t take my word for it. Ask Geoffrey Hinton [University of Toronto’s Geoffrey Hinton, a Canadian leader in machine learning].

“There is a lot of pressure to make things more applied; I think it’s a big mistake,” he said in 2015. “In the long run, curiosity-driven research just works better… Real breakthroughs come from people focusing on what they’re excited about.”

I keep saying this, like a broken record. If you want the science that changes the world, ask the scientists who’ve changed it how it gets made. This government claims to be interested in what scientists think. We’ll see.

Incisive and acerbic,  you may want to make time to read this article in its entirety.

Getting back to the ‘The Naylor report under the microscope’ event, I wonder if anyone will be as tough and direct as Wells. Going back even further, I wonder if this is why there’s no mention of Duncan as a speaker at the conference. It could go either way: surprise announcement of a Chief Science Advisor, as I first suggested, or avoidance of a potentially angry audience.

For anyone curious about Geoffrey Hinton, there’s more here in my March 31, 2017 post (scroll down about 20% of the way) and for more about the 2017 budget and allocations for targeted science projects there’s my March 24, 2017 post.

US science envoy quits

An Aug. 23, 2017article by Matthew Rosza for salon.com notes the resignation of one of the US science envoys,

President Donald Trump’s infamous response to the Charlottesville riots — namely, saying that both sides were to blame and that there were “very fine people” marching as white supremacists — has prompted yet another high profile resignation from his administration.

Daniel M. Kammen, who served as a science envoy for the State Department and focused on renewable energy development in the Middle East and Northern Africa, submitted a letter of resignation on Wednesday. Notably, he began the first letter of each paragraph with letters that spelled out I-M-P-E-A-C-H. That followed a letter earlier this month by writer Jhumpa Lahiri and actor Kal Penn to similarly spell R-E-S-I-S-T in their joint letter of resignation from the President’s Committee on Arts and Humanities.

Jeremy Berke’s Aug. 23, 2017 article for BusinessInsider.com provides a little more detail (Note: Links have been removed),

A State Department climate science envoy resigned Wednesday in a public letter posted on Twitter over what he says is President Donald Trump’s “attacks on the core values” of the United States with his response to violence in Charlottesville, Virginia.

“My decision to resign is in response to your attacks on the core values of the United States,” wrote Daniel Kammen, a professor of energy at the University of California, Berkeley, who was appointed as one five science envoys in 2016. “Your failure to condemn white supremacists and neo-Nazis has domestic and international ramifications.”

“Your actions to date have, sadly, harmed the quality of life in the United States, our standing abroad, and the sustainability of the planet,” Kammen writes.

Science envoys work with the State Department to establish and develop energy programs in countries around the world. Kammen specifically focused on renewable energy development in the Middle East and North Africa.

That’s it.

The US White House and its Office of Science and Technology Policy (OSTP)

It’s been a while since I first wrote this but I believe this situation has not changed.

There’s some consternation regarding the US Office of Science and Technology Policy’s (OSTP) diminishing size and lack of leadership. From a July 3, 2017 article by Bob Grant for The Scientist (Note: Links have been removed),

Three OSTP staffers did leave last week, but it was because their prearranged tenures at the office had expired, according to an administration official familiar with the situation. “I saw that there were some tweets and what-not saying that it’s zero,” the official tells The Scientist. “That is not true. We have plenty of PhDs that are still on staff that are working on science. All of the work that was being done by the three who left on Friday had been transitioned to other staffers.”

At least one of the tweets that the official is referring to came from Eleanor Celeste, who announced leaving OSTP, where she was the assistant director for biomedical and forensic sciences. “science division out. mic drop,” she tweeted on Friday afternoon.

The administration official concedes that the OSTP is currently in a state of “constant flux” and at a “weird transition period” at the moment, and expects change to continue. “I’m sure that the office will look even more different in three months than it does today, than it did six months ago,” the official says.

Jeffrey Mervis in two articles for Science Magazine is able to provide more detail. From his July 11, 2017 article,

OSTP now has 35 staffers, says an administration official who declined to be named because they weren’t authorized to speak to the media. Holdren [John Holdren], who in January [2017] returned to Harvard University, says the plunge in staff levels is normal during a presidential transition. “But what’s shocking is that, this far into the new administration, the numbers haven’t gone back up.”

The office’s only political appointee is Michael Kratsios, a former aide to Trump confidant and Silicon Valley billionaire Peter Thiel. Kratsios is serving as OSTP’s deputy chief technology officer and de facto OSTP head. Eight new detailees have arrived from other agencies since the inauguration.

Although there has been no formal reorganization of OSTP, a “smaller, more collaborative staff” is now grouped around three areas—science, technology, and national security—according to the Trump aide. Three holdovers from Obama’s OSTP are leading teams focused on specific themes—Lloyd Whitman in technology, Chris Fall in national security, and Deerin Babb-Brott in environment and energy. They report to Kratsios and Ted Wackler, a career civil servant who was Holdren’s deputy chief of staff and who joined OSTP under former President George W. Bush.

“It’s a very flat structure,” says the Trump official, consistent with the administration’s view that “government should be looking for ways to do more with less.” Ultimately, the official adds, “the goal is [for OSTP] to have “probably closer to 50 [people].”

A briefing book prepared by Obama’s outgoing OSTP staff may be a small but telling indication of the office’s current status. The thick, three-ring binder, covering 100 issues, was modeled on one that Holdren received from John “Jack” Marburger, Bush’s OSTP director. “Jack did a fabulous job of laying out what OSTP does, including what reports it owes Congress, so we decided to do likewise,” Holdren says. “But nobody came [from Trump’s transition team] to collect it until a week before the inauguration.”

That person was Reed Cordish, the 43-year-old scion of billionaire real estate developer David Cordish. An English major in college, Reed Cordish was briefly a professional tennis player before joining the family business. He “spent an hour with us and took the book away,” Holdren says. “He told us, ‘This is an important operation and I’ll do my best to see that it flourishes.’ But we don’t know … whether he has the clout to make that happen.”

Cordish is now assistant to the president for intragovernmental and technology initiatives. He works in the new Office of American Innovation led by presidential son-in-law Jared Kushner. That office arranged a recent meeting with high-tech executives, and is also leading yet another White House attempt to “reinvent” government.

Trump has renewed the charter of the National Science and Technology Council, a multiagency group that carries out much of the day-to-day work of advancing the president’s science initiatives. … Still pending is the status of the President’s Council of Advisors on Science and Technology [emphasis mine], a body of eminent scientists and high-tech industry leaders that went out of business at the end of the Obama administration.

Mervis’ July 12, 2017 article is in the form of a Q&A (question and answer) session with the previously mentioned John Holdren, director of the OSTP in Barack Obama’s administration,

Q: Why did you have such a large staff?

A: One reason was to cover the bases. We knew from the start that the Obama administration thought cybersecurity would be an important issue and we needed to be capable in that space. We also knew we needed people who were capable in climate change, in science and technology for economic recovery and job creation and sustained economic growth, and people who knew about advanced manufacturing and nanotechnology and biotechnology.

We also recruited to carry out specific initiatives, like in precision medicine, or combating antibiotic resistance, or the BRAIN [Brain Research through Advancing Innovative Neurotechnologies] initiative. Most of the work will go on in the departments and agencies, but you need someone to oversee it.

The reason we ended up with 135 people at our peak, which was twice the number during its previous peak in the Clinton administration’s second term, was that this president was so interested in knowing what science could do to advance his agenda, on economic recovery, or energy and climate change, or national intelligence. He got it. He didn’t need to be tutored on why science and technology matters.

I feel I’ve been given undue credit for [Obama] being a science geek. It wasn’t me. He came that way. He was constantly asking what we could do to move the needle. When the first flu epidemic, H1N1, came along, the president immediately turned to me and said, “OK, I want [the President’s Council of Advisors on Science and Technology] to look in depth on this, and OSTP, and NIH [National Institutes of Health], and [the Centers for Disease Control and Prevention].” And he told us to coordinate my effort on this stuff—inform me on what can be done and assemble the relevant experts. It was the same with Ebola, with the Macondo oil spill in the Gulf, with Fukushima, where the United States stepped up to work with the Japanese.

It’s not that we had all the expertise. But our job was to reach out to those who did have the relevant expertise.

Q: OSTP now has 35 people. What does that level of staffing say to you?

A: I have to laugh.

Q: Why?

A: When I left, on 19 January [2017], we were down to 30 people. And a substantial fraction of the 30 were people who, in a sense, keep the lights on. They were the OSTP general counsel and deputy counsel, the security officer and deputy, the budget folks, the accounting folks, the executive director of NSTC [National Science and Technology Council].

There are some scientists left, and there are some scientists there still. But on 30 June the last scientist in the science division left.

Somebody said OSTP has shut down. But that’s not quite it. There was no formal decision to shut anything down. But they did not renew the contract of the last remaining science folks in the science division.

I saw somebody say, “Well, we still have some Ph.D.s left.” And that’s undoubtedly true. There are still some science Ph.D.s left in the national security and international affairs division. But because [OSTP] is headless, they have no direct connection to the president and his top advisers.

I don’t want to disparage the top people there. The top people there now are Michael Kratsios, who they named the deputy chief technology officer, and Ted Wackler, who was my deputy chief of staff and who was [former OSTP Director] Jack Marberger’s deputy, and who I kept because he’s a fabulously effective manager. And I believe that they are doing everything they can to make sure that OSTP, at the very least, does the things it has to do. … But right now I think OSTP is just hanging on.

Q: Why did some people choose to stay on?

A: A large portion of OSTP staff are borrowed from other agencies, and because the White House is the White House, we get the people we need. These are dedicated folks who want to get the job done. They want to see science and technology applied to advance the public interest. And they were willing to stay and do their best despite the considerable uncertainty about their future.

But again, most of the detailees, and the reason we went from 135 to 30 almost overnight, is that it’s pretty standard for the detailees to go back to their home agencies and wait for the next administration to decide what set of detailees it wants to advance their objects.

So there’s nothing shocking that most of the detailees went back to their home agencies. The people who stayed are mostly employed directly by OSTP. What’s shocking is that, this far into the new administration, that number hasn’t gone back up. That is, they have only five more people than they had on January 20 [2017].

As I had been wondering about the OSTP and about the President’s Council of Advisors on Science and Technology (PCAST), it was good to get an update.

On a more parochial note, we in Canada are still waiting for an announcement about who our Chief Science Advisor might be.

Health technology and the Canadian Broadcasting Corporation’s (CBC) two-tier health system ‘Viewpoint’

There’s a lot of talk and handwringing about Canada’s health care system, which ebbs and flows in almost predictable cycles. Jesse Hirsh in a May 16, 2017 ‘Viewpoints’ segment (an occasional series run as part the of the CBC’s [Canadian Broadcasting Corporation] flagship, daily news programme, The National) dared to reframe the discussion as one about technology and ‘those who get it’  [the technologically literate] and ‘those who don’t’,  a state Hirsh described as being illiterate as you can see and hear in the following video.

I don’t know about you but I’m getting tired of being called illiterate when I don’t know something. To be illiterate means you can’t read and write and as it turns out I do both of those things on a daily basis (sometimes even in two languages). Despite my efforts, I’m ignorant about any number of things and those numbers keep increasing day by day. BTW, Is there anyone who isn’t having trouble keeping up?

Moving on from my rhetorical question, Hirsh has a point about the tech divide and about the need for discussion. It’s a point that hadn’t occurred to me (although I think he’s taking it in the wrong direction). In fact, this business of a tech divide already exists if you consider that people who live in rural environments and need the latest lifesaving techniques or complex procedures or access to highly specialized experts have to travel to urban centres. I gather that Hirsh feels that this divide isn’t necessarily going to be an urban/rural split so much as an issue of how technically literate you and your doctor are.  That’s intriguing but then his argumentation gets muddled. Confusingly, he seems to be suggesting that the key to the split is your access (not your technical literacy) to artificial intelligence (AI) and algorithms (presumably he’s referring to big data and data analytics). I expect access will come down more to money than technological literacy.

For example, money is likely to be a key issue when you consider his big pitch is for access to IBM’s Watson computer. (My Feb. 28, 2011 posting titled: Engineering, entertainment, IBM’s Watson, and product placement focuses largely on Watson, its winning appearances on the US television game show, Jeopardy, and its subsequent adoption into the University of Maryland’s School of Medicine in a project to bring Watson into the examining room with patients.)

Hirsh’s choice of IBM’s Watson is particularly interesting for a number of reasons. (1) Presumably there are companies other than IBM in this sector. Why do they not rate a mention?  (2) Given the current situation with IBM and the Canadian federal government’s introduction of the Phoenix payroll system (a PeopleSoft product customized by IBM), which is  a failure of monumental proportions (a Feb. 23, 2017 article by David Reevely for the Ottawa Citizen and a May 25, 2017 article by Jordan Press for the National Post), there may be a little hesitation, if not downright resistance, to a large scale implementation of any IBM product or service, regardless of where the blame lies. (3) Hirsh notes on the home page for his eponymous website,

I’m presently spending time at the IBM Innovation Space in Toronto Canada, investigating the impact of artificial intelligence and cognitive computing on all sectors and industries.

Yes, it would seem he has some sort of relationship with IBM not referenced in his Viewpoints segment on The National. Also, his description of the relationship isn’t especially illuminating but perhaps it.s this? (from the IBM Innovation Space  – Toronto Incubator Application webpage),

Our incubator

The IBM Innovation Space is a Toronto-based incubator that provides startups with a collaborative space to innovate and disrupt the market. Our goal is to provide you with the tools needed to take your idea to the next level, introduce you to the right networks and help you acquire new clients. Our unique approach, specifically around client engagement, positions your company for optimal growth and revenue at an accelerated pace.

OUR SERVICES

IBM Bluemix
IBM Global Entrepreneur
Softlayer – an IBM Company
Watson

Startups partnered with the IBM Innovation Space can receive up to $120,000 in IBM credits at no charge for up to 12 months through the Global Entrepreneurship Program (GEP). These credits can be used in our products such our IBM Bluemix developer platform, Softlayer cloud services, and our world-renowned IBM Watson ‘cognitive thinking’ APIs. We provide you with enterprise grade technology to meet your clients’ needs, large or small.

Collaborative workspace in the heart of Downtown Toronto
Mentorship opportunities available with leading experts
Access to large clients to scale your startup quickly and effectively
Weekly programming ranging from guest speakers to collaborative activities
Help with funding and access to local VCs and investors​

Final comments

While I have some issues with Hirsh’s presentation, I agree that we should be discussing the issues around increased automation of our health care system. A friend of mine’s husband is a doctor and according to him those prescriptions and orders you get when leaving the hospital? They are not made up by a doctor so much as they are spit up by a computer based on the data that the doctors and nurses have supplied.

GIGO, bias, and de-skilling

Leaving aside the wonders that Hirsh describes, there’s an oldish saying in the computer business, garbage in/garbage out (gigo). At its simplest, who’s going to catch a mistake? (There are lots of mistakes made in hospitals and other health care settings.)

There are also issues around the quality of research. Are all the research papers included in the data used by the algorithms going to be considered equal? There’s more than one case where a piece of problematic research has been accepted uncritically, even if it get through peer review, and subsequently cited many times over. One of the ways to measure impact, i.e., importance, is to track the number of citations. There’s also the matter of where the research is published. A ‘high impact’ journal, such as Nature, Science, or Cell, automatically gives a piece of research a boost.

There are other kinds of bias as well. Increasingly, there’s discussion about algorithms being biased and about how machine learning (AI) can become biased. (See my May 24, 2017 posting: Machine learning programs learn bias, which highlights the issues and cites other FrogHeart posts on that and other related topics.)

These problems are to a large extent already present. Doctors have biases and research can be wrong and it can take a long time before there are corrections. However, the advent of an automated health diagnosis and treatment system is likely to exacerbate the problems. For example, if you don’t agree with your doctor’s diagnosis or treatment, you can search other opinions. What happens when your diagnosis and treatment have become data? Will the system give you another opinion? Who will you talk to? The doctor who got an answer from ‘Watson”? Is she or he going to debate Watson? Are you?

This leads to another issue and that’s automated systems getting more credit than they deserve. Futurists such as Hirsh tend to underestimate people and overestimate the positive impact that automation will have. A computer, data analystics, or an AI system are tools not gods. You’ll have as much luck petitioning one of those tools as you would Zeus.

The unasked question is how will your doctor or other health professional gain experience and skills if they never have to practice the basic, boring aspects of health care (asking questions for a history, reading medical journals to keep up with the research, etc.) and leave them to the computers? There had to be  a reason for calling it a medical ‘practice’.

There are definitely going to be advantages to these technological innovations but thoughtful adoption of these practices (pun intended) should be our goal.

Who owns your data?

Another issue which is increasingly making itself felt is ownership of data. Jacob Brogan has written a provocative May 23, 2017 piece for slate.com asking that question about the data Ancestry.com gathers for DNA testing (Note: Links have been removed),

AncestryDNA’s pitch to consumers is simple enough. For $99 (US), the company will analyze a sample of your saliva and then send back information about your “ethnic mix.” While that promise may be scientifically dubious, it’s a relatively clear-cut proposal. Some, however, worry that the service might raise significant privacy concerns.

After surveying AncestryDNA’s terms and conditions, consumer protection attorney Joel Winston found a few issues that troubled him. As he noted in a Medium post last week, the agreement asserts that it grants the company “a perpetual, royalty-free, world-wide, transferable license to use your DNA.” (The actual clause is considerably longer.) According to Winston, “With this single contractual provision, customers are granting Ancestry.com the broadest possible rights to own and exploit their genetic information.”

Winston also noted a handful of other issues that further complicate the question of ownership. Since we share much of our DNA with our relatives, he warned, “Even if you’ve never used Ancestry.com, but one of your genetic relatives has, the company may already own identifiable portions of your DNA.” [emphasis mine] Theoretically, that means information about your genetic makeup could make its way into the hands of insurers or other interested parties, whether or not you’ve sent the company your spit. (Maryam Zaringhalam explored some related risks in a recent Slate article.) Further, Winston notes that Ancestry’s customers waive their legal rights, meaning that they cannot sue the company if their information gets used against them in some way.

Over the weekend, Eric Heath, Ancestry’s chief privacy officer, responded to these concerns on the company’s own site. He claims that the transferable license is necessary for the company to provide its customers with the service that they’re paying for: “We need that license in order to move your data through our systems, render it around the globe, and to provide you with the results of our analysis work.” In other words, it allows them to send genetic samples to labs (Ancestry uses outside vendors), store the resulting data on servers, and furnish the company’s customers with the results of the study they’ve requested.

Speaking to me over the phone, Heath suggested that this license was akin to the ones that companies such as YouTube employ when users upload original content. It grants them the right to shift that data around and manipulate it in various ways, but isn’t an assertion of ownership. “We have committed to our users that their DNA data is theirs. They own their DNA,” he said.

I’m glad to see the company’s representatives are open to discussion and, later in the article, you’ll see there’ve already been some changes made. Still, there is no guarantee that the situation won’t again change, for ill this time.

What data do they have and what can they do with it?

It’s not everybody who thinks data collection and data analytics constitute problems. While some people might balk at the thought of their genetic data being traded around and possibly used against them, e.g., while hunting for a job, or turned into a source of revenue, there tends to be a more laissez-faire attitude to other types of data. Andrew MacLeod’s May 24, 2017 article for thetyee.ca highlights political implications and privacy issues (Note: Links have been removed),

After a small Victoria [British Columbia, Canada] company played an outsized role in the Brexit vote, government information and privacy watchdogs in British Columbia and Britain have been consulting each other about the use of social media to target voters based on their personal data.

The U.K.’s information commissioner, Elizabeth Denham [Note: Denham was formerly B.C.’s Office of the Information and Privacy Commissioner], announced last week [May 17, 2017] that she is launching an investigation into “the use of data analytics for political purposes.”

The investigation will look at whether political parties or advocacy groups are gathering personal information from Facebook and other social media and using it to target individuals with messages, Denham said.

B.C.’s Office of the Information and Privacy Commissioner confirmed it has been contacted by Denham.

Macleod’s March 6, 2017 article for thetyee.ca provides more details about the company’s role (note: Links have been removed),

The “tiny” and “secretive” British Columbia technology company [AggregateIQ; AIQ] that played a key role in the Brexit referendum was until recently listed as the Canadian office of a much larger firm that has 25 years of experience using behavioural research to shape public opinion around the world.

The larger firm, SCL Group, says it has worked to influence election outcomes in 19 countries. Its associated company in the U.S., Cambridge Analytica, has worked on a wide range of campaigns, including Donald Trump’s presidential bid.

In late February [2017], the Telegraph reported that campaign disclosures showed that Vote Leave campaigners had spent £3.5 million — about C$5.75 million [emphasis mine] — with a company called AggregateIQ, run by CEO Zack Massingham in downtown Victoria.

That was more than the Leave side paid any other company or individual during the campaign and about 40 per cent of its spending ahead of the June referendum that saw Britons narrowly vote to exit the European Union.

According to media reports, Aggregate develops advertising to be used on sites including Facebook, Twitter and YouTube, then targets messages to audiences who are likely to be receptive.

The Telegraph story described Victoria as “provincial” and “picturesque” and AggregateIQ as “secretive” and “low-profile.”

Canadian media also expressed surprise at AggregateIQ’s outsized role in the Brexit vote.

The Globe and Mail’s Paul Waldie wrote “It’s quite a coup for Mr. Massingham, who has only been involved in politics for six years and started AggregateIQ in 2013.”

Victoria Times Colonist columnist Jack Knox wrote “If you have never heard of AIQ, join the club.”

The Victoria company, however, appears to be connected to the much larger SCL Group, which describes itself on its website as “the global leader in data-driven communications.”

In the United States it works through related company Cambridge Analytica and has been involved in elections since 2012. Politico reported in 2015 that the firm was working on Ted Cruz’s presidential primary campaign.

And NBC and other media outlets reported that the Trump campaign paid Cambridge Analytica millions to crunch data on 230 million U.S. adults, using information from loyalty cards, club and gym memberships and charity donations [emphasis mine] to predict how an individual might vote and to shape targeted political messages.

That’s quite a chunk of change and I don’t believe that gym memberships, charity donations, etc. were the only sources of information (in the US, there’s voter registration, credit card information, and more) but the list did raise my eyebrows. It would seem we are under surveillance at all times, even in the gym.

In any event, I hope that Hirsh’s call for discussion is successful and that the discussion includes more critical thinking about the implications of Hirsh’s ‘Brave New World’.

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.

China, US, and the race for artificial intelligence research domination

John Markoff and Matthew Rosenberg have written a fascinating analysis of the competition between US and China regarding technological advances, specifically in the field of artificial intelligence. While the focus of the Feb. 3, 2017 NY Times article is military, the authors make it easy to extrapolate and apply the concepts to other sectors,

Robert O. Work, the veteran defense official retained as deputy secretary by President Trump, calls them his “A.I. dudes.” The breezy moniker belies their serious task: The dudes have been a kitchen cabinet of sorts, and have advised Mr. Work as he has sought to reshape warfare by bringing artificial intelligence to the battlefield.

Last spring, he asked, “O.K., you guys are the smartest guys in A.I., right?”

No, the dudes told him, “the smartest guys are at Facebook and Google,” Mr. Work recalled in an interview.

Now, increasingly, they’re also in China. The United States no longer has a strategic monopoly on the technology, which is widely seen as the key factor in the next generation of warfare.

The Pentagon’s plan to bring A.I. to the military is taking shape as Chinese researchers assert themselves in the nascent technology field. And that shift is reflected in surprising commercial advances in artificial intelligence among Chinese companies. [emphasis mine]

Having read Marshal McLuhan (de rigeur for any Canadian pursuing a degree in communications [sociology-based] anytime from the 1960s into the late 1980s [at least]), I took the movement of technology from military research to consumer applications as a standard. Television is a classic example but there are many others including modern plastic surgery. The first time, I encountered the reverse (consumer-based technology being adopted by the military) was in a 2004 exhibition “Massive Change: The Future of Global Design” produced by Bruce Mau for the Vancouver (Canada) Art Gallery.

Markoff and Rosenberg develop their thesis further (Note: Links have been removed),

Last year, for example, Microsoft researchers proclaimed that the company had created software capable of matching human skills in understanding speech.

Although they boasted that they had outperformed their United States competitors, a well-known A.I. researcher who leads a Silicon Valley laboratory for the Chinese web services company Baidu gently taunted Microsoft, noting that Baidu had achieved similar accuracy with the Chinese language two years earlier.

That, in a nutshell, is the challenge the United States faces as it embarks on a new military strategy founded on the assumption of its continued superiority in technologies such as robotics and artificial intelligence.

First announced last year by Ashton B. Carter, President Barack Obama’s defense secretary, the “Third Offset” strategy provides a formula for maintaining a military advantage in the face of a renewed rivalry with China and Russia.

As consumer electronics manufacturing has moved to Asia, both Chinese companies and the nation’s government laboratories are making major investments in artificial intelligence.

The advance of the Chinese was underscored last month when Qi Lu, a veteran Microsoft artificial intelligence specialist, left the company to become chief operating officer at Baidu, where he will oversee the company’s ambitious plan to become a global leader in A.I.

The authors note some recent military moves (Note: Links have been removed),

In August [2016], the state-run China Daily reported that the country had embarked on the development of a cruise missile system with a “high level” of artificial intelligence. The new system appears to be a response to a missile the United States Navy is expected to deploy in 2018 to counter growing Chinese military influence in the Pacific.

Known as the Long Range Anti-Ship Missile, or L.R.A.S.M., it is described as a “semiautonomous” weapon. According to the Pentagon, this means that though targets are chosen by human soldiers, the missile uses artificial intelligence technology to avoid defenses and make final targeting decisions.

The new Chinese weapon typifies a strategy known as “remote warfare,” said John Arquilla, a military strategist at the Naval Post Graduate School in Monterey, Calif. The idea is to build large fleets of small ships that deploy missiles, to attack an enemy with larger ships, like aircraft carriers.

“They are making their machines more creative,” he said. “A little bit of automation gives the machines a tremendous boost.”

Whether or not the Chinese will quickly catch the United States in artificial intelligence and robotics technologies is a matter of intense discussion and disagreement in the United States.

Markoff and Rosenberg return to the world of consumer electronics as they finish their article on AI and the military (Note: Links have been removed),

Moreover, while there appear to be relatively cozy relationships between the Chinese government and commercial technology efforts, the same cannot be said about the United States. The Pentagon recently restarted its beachhead in Silicon Valley, known as the Defense Innovation Unit Experimental facility, or DIUx. It is an attempt to rethink bureaucratic United States government contracting practices in terms of the faster and more fluid style of Silicon Valley.

The government has not yet undone the damage to its relationship with the Valley brought about by Edward J. Snowden’s revelations about the National Security Agency’s surveillance practices. Many Silicon Valley firms remain hesitant to be seen as working too closely with the Pentagon out of fear of losing access to China’s market.

“There are smaller companies, the companies who sort of decided that they’re going to be in the defense business, like a Palantir,” said Peter W. Singer, an expert in the future of war at New America, a think tank in Washington, referring to the Palo Alto, Calif., start-up founded in part by the venture capitalist Peter Thiel. “But if you’re thinking about the big, iconic tech companies, they can’t become defense contractors and still expect to get access to the Chinese market.”

Those concerns are real for Silicon Valley.

If you have the time, I recommend reading the article in its entirety.

Impact of the US regime on thinking about AI?

A March 24, 2017 article by Daniel Gross for Slate.com hints that at least one high level offician in the Trump administration may be a little naïve in his understanding of AI and its impending impact on US society (Note: Links have been removed),

Treasury Secretary Steven Mnuchin is a sharp guy. He’s a (legacy) alumnus of Yale and Goldman Sachs, did well on Wall Street, and was a successful movie producer and bank investor. He’s good at, and willing to, put other people’s money at risk alongside some of his own. While he isn’t the least qualified person to hold the post of treasury secretary in 2017, he’s far from the best qualified. For in his 54 years on this planet, he hasn’t expressed or displayed much interest in economic policy, or in grappling with the big picture macroeconomic issues that are affecting our world. It’s not that he is intellectually incapable of grasping them; they just haven’t been in his orbit.

Which accounts for the inanity he uttered at an Axios breakfast Friday morning about the impact of artificial intelligence on jobs.

“it’s not even on our radar screen…. 50-100 more years” away, he said. “I’m not worried at all” about robots displacing humans in the near future, he said, adding: “In fact I’m optimistic.”

A.I. is already affecting the way people work, and the work they do. (In fact, I’ve long suspected that Mike Allen, Mnuchin’s Axios interlocutor, is powered by A.I.) I doubt Mnuchin has spent much time in factories, for example. But if he did, he’d see that machines and software are increasingly doing the work that people used to do. They’re not just moving goods through an assembly line, they’re soldering, coating, packaging, and checking for quality. Whether you’re visiting a GE turbine plant in South Carolina, or a cable-modem factory in Shanghai, the thing you’ll notice is just how few people there actually are. It’s why, in the U.S., manufacturing output rises every year while manufacturing employment is essentially stagnant. It’s why it is becoming conventional wisdom that automation is destroying more manufacturing jobs than trade. And now we are seeing the prospect of dark factories, which can run without lights because there are no people in them, are starting to become a reality. The integration of A.I. into factories is one of the reasons Trump’s promise to bring back manufacturing employment is absurd. You’d think his treasury secretary would know something about that.

It goes far beyond manufacturing, of course. Programmatic advertising buying, Spotify’s recommendation engines, chatbots on customer service websites, Uber’s dispatching system—all of these are examples of A.I. doing the work that people used to do. …

Adding to Mnuchin’s lack of credibility on the topic of jobs and robots/AI, Matthew Rozsa’s March 28, 2017 article for Salon.com features a study from the US National Bureau of Economic Research (Note: Links have been removed),

A new study by the National Bureau of Economic Research shows that every fully autonomous robot added to an American factory has reduced employment by an average of 6.2 workers, according to a report by BuzzFeed. The study also found that for every fully autonomous robot per thousand workers, the employment rate dropped by 0.18 to 0.34 percentage points and wages fell by 0.25 to 0.5 percentage points.

I can’t help wondering if the US Secretary of the Treasury is so oblivious to what is going on in the workplace whether that’s representative of other top-tier officials such as the Secretary of Defense, Secretary of Labor, etc. What is going to happen to US research in fields such as robotics and AI?

I have two more questions, in future what happens to research which contradicts or makes a top tier Trump government official look foolish? Will it be suppressed?

You can find the report “Robots and Jobs: Evidence from US Labor Markets” by Daron Acemoglu and Pascual Restrepo. NBER (US National Bureau of Economic Research) WORKING PAPER SERIES (Working Paper 23285) released March 2017 here. The introduction featured some new information for me; the term ‘technological unemployment’ was introduced in 1930 by John Maynard Keynes.

Moving from a wholly US-centric view of AI

Naturally in a discussion about AI, it’s all US and the country considered its chief sceince rival, China, with a mention of its old rival, Russia. Europe did rate a mention, albeit as a totality. Having recently found out that Canadians were pioneers in a very important aspect of AI, machine-learning, I feel obliged to mention it. You can find more about Canadian AI efforts in my March 24, 2017 posting (scroll down about 40% of the way) where you’ll find a very brief history and mention of the funding for a newly launching, Pan-Canadian Artificial Intelligence Strategy.

If any of my readers have information about AI research efforts in other parts of the world, please feel free to write them up in the comments.