Tag Archives: Richard Zemel

Age of AI and Big Data – Impact on Justice, Human Rights and Privacy Zoom event on September 28, 2022 at 12 – 1:30 pm EDT

The Canadian Science Policy Centre (CSPC) in a September 15, 2022 announcement (received via email) announced an event (Age of AI and Big Data – Impact on Justice, Human Rights and Privacy) centered on some of the latest government doings on artificial intelligence and privacy (Bill C-27),

In an increasingly connected world, we share a large amount of our data in our daily lives without our knowledge while browsing online, traveling, shopping, etc. More and more companies are collecting our data and using it to create algorithms or AI. The use of our data against us is becoming more and more common. The algorithms used may often be discriminatory against racial minorities and marginalized people.

As technology moves at a high pace, we have started to incorporate many of these technologies into our daily lives without understanding its consequences. These technologies have enormous impacts on our very own identity and collectively on civil society and democracy. 

Recently, the Canadian Government introduced the Artificial Intelligence and Data Act (AIDA) and Bill C-27 [which includes three acts in total] in parliament regulating the use of AI in our society. In this panel, we will discuss how our AI and Big data is affecting us and its impact on society, and how the new regulations affect us. 

Date: Sep 28 Time: 12:00 pm – 1:30 pm EDT Event Category: Virtual Session

Register Here

For some reason, there was no information about the moderator and panelists, other than their names, titles, and affiliations. Here’s a bit more:

Moderator: Yuan Stevens (from her eponymous website’s About page), Note: Links have been removed,

Yuan (“You-anne”) Stevens (she/they) is a legal and policy expert focused on sociotechnical security and human rights.

She works towards a world where powerful actors—and the systems they build—are held accountable to the public, especially when it comes to marginalized communities. 

She brings years of international experience to her role at the Leadership Lab at Toronto Metropolitan University [formerly Ryerson University], having examined the impacts of technology on vulnerable populations in Canada, the US and Germany. 

Committed to publicly accessible legal and technical knowledge, Yuan has written for popular media outlets such as the Toronto Star and Ottawa Citizen and has been quoted in news stories by the New York Times, the CBC and the Globe & Mail.

Yuan is a research fellow at the Centre for Law, Technology and Society at the University of Ottawa and a research affiliate at Data & Society Research Institute. She previously worked at Harvard University’s Berkman Klein Center for Internet & Society during her studies in law at McGill University.

She has been conducting research on artificial intelligence since 2017 and is currently exploring sociotechnical security as an LL.M candidate at University of Ottawa’s Faculty of Law working under Florian Martin-Bariteau.

Panelist: Brenda McPhail (from her Centre for International Governance Innovation profile page),

Brenda McPhail is the director of the Canadian Civil Liberties Association’s Privacy, Surveillance and Technology Project. Her recent work includes guiding the Canadian Civil Liberties Association’s interventions in key court cases that raise privacy issues, most recently at the Supreme Court of Canada in R v. Marakah and R v. Jones, which focused on privacy rights in sent text messages; research into surveillance of dissent, government information sharing, digital surveillance capabilities and privacy in relation to emergent technologies; and developing resources and presentations to drive public awareness about the importance of privacy as a social good.

Panelist: Nidhi Hegde (from her University of Alberta profile page),

My research has spanned many areas such as resource allocation in networking, smart grids, social information networks, machine learning. Broadly, my interest lies in gaining a fundamental understanding of a given system and the design of robust algorithms.

More recently my research focus has been in privacy in machine learning. I’m interested in understanding how robust machine learning methods are to perturbation, and privacy and fairness constraints, with the goal of designing practical algorithms that achieve privacy and fairness.

Bio

Before joining the University of Alberta, I spent many years in industry research labs. Most recently, I was a Research team lead at Borealis AI (a research institute at Royal Bank of Canada), where my team worked on privacy-preserving methods for machine learning models and other applied problems for RBC. Prior to that, I spent many years in research labs in Europe working on a variety of interesting and impactful problems. I was a researcher at Bell Labs, Nokia, in France from January 2015 to March 2018, where I led a new team focussed on Maths and Algorithms for Machine Learning in Networks and Systems, in the Maths and Algorithms group of Bell Labs. I also spent a few years at the Technicolor Paris Research Lab working on social network analysis, smart grids, and privacy in recommendations.

Panelist: Benjamin Faveri (from his LinkedIn page),

About

Benjamin Faveri is a Research and Policy Analyst at the Responsible AI Institute (RAII) [headquarted in Austin, Texas]. Currently, he is developing their Responsible AI Certification Program and leading it through Canada’s national accreditation process. Over the last several years, he has worked on numerous certification program-related research projects such as fishery economics and certification programs, police body-worn camera policy certification, and emerging AI certifications and assurance systems. Before his work at RAII, Benjamin completed a Master of Public Policy and Administration at Carleton University, where he was a Canada Graduate Scholar, Ontario Graduate Scholar, Social Innovation Fellow, and Visiting Scholar at UC Davis School of Law. He holds undergraduate degrees in criminology and psychology, finishing both with first class standing. Outside of work, Benjamin reads about how and why certification and private governance have been applied across various industries.

Panelist: Ori Freiman (from his eponymous website’s About page)

I research at the forefront of technological innovation. This website documents some of my academic activities.

My formal background is in Analytic Philosophy, Library and Information Science, and Science & Technology Studies. Until September 22′ [September 2022], I was a Post-Doctoral Fellow at the Ethics of AI Lab, at the University of Toronto’s Centre for Ethics. Before joining the Centre, I submitted my dissertation, about trust in technology, to The Graduate Program in Science, Technology and Society at Bar-Ilan University.

I have also found a number of overviews and bits of commentary about the Canadian federal government’s proposed Bill C-27, which I think of as an omnibus bill as it includes three proposed Acts.

The lawyers are excited but I’m starting with the Responsible AI Institute’s (RAII) response first as one of the panelists (Benjamin Faveri) works for them and it’s a view from a closely neighbouring country, from a June 22, 2022 RAII news release, Note: Links have been removed,

Business Implications of Canada’s Draft AI and Data Act

On June 16 [2022], the Government of Canada introduced the Artificial Intelligence and Data Act (AIDA), as part of the broader Digital Charter Implementation Act 2022 (Bill C-27). Shortly thereafter, it also launched the second phase of the Pan-Canadian Artificial Intelligence Strategy.

Both RAII’s Certification Program, which is currently under review by the Standards Council of Canada, and the proposed AIDA legislation adopt the same approach of gauging an AI system’s risk level in context; identifying, assessing, and mitigating risks both pre-deployment and on an ongoing basis; and pursuing objectives such as safety, fairness, consumer protection, and plain-language notification and explanation.

Businesses should monitor the progress of Bill C-27 and align their AI governance processes, policies, and controls to its requirements. Businesses participating in RAII’s Certification Program will already be aware of requirements, such as internal Algorithmic Impact Assessments to gauge risk level and Responsible AI Management Plans for each AI system, which include system documentation, mitigation measures, monitoring requirements, and internal approvals.

The AIDA draft is focused on the impact of any “high-impact system”. Companies would need to assess whether their AI systems are high-impact; identify, assess, and mitigate potential harms and biases flowing from high-impact systems; and “publish on a publicly available website a plain-language description of the system” if making a high-impact system available for use. The government elaborated in a press briefing that it will describe in future regulations the classes of AI systems that may have high impact.

The AIDA draft also outlines clear criminal penalties for entities which, in their AI efforts, possess or use unlawfully obtained personal information or knowingly make available for use an AI system that causes serious harm or defrauds the public and causes substantial economic loss to an individual.

If enacted, AIDA would establish the Office of the AI and Data Commissioner, to support Canada’s Minister of Innovation, Science and Economic Development, with powers to monitor company compliance with the AIDA, to order independent audits of companies’ AI activities, and to register compliance orders with courts. The Commissioner would also help the Minister ensure that standards for AI systems are aligned with international standards.

Apart from being aligned with the approach and requirements of Canada’s proposed AIDA legislation, RAII is also playing a key role in the Standards Council of Canada’s AI  accreditation pilot. The second phase of the Pan-Canadian includes funding for the Standards Council of Canada to “advance the development and adoption of standards and a conformity assessment program related to AI/”

The AIDA’s introduction shows that while Canada is serious about governing AI systems, its approach to AI governance is flexible and designed to evolve as the landscape changes.

Charles Mandel’s June 16, 2022 article for Betakit (Canadian Startup News and Tech Innovation) provides an overview of the government’s overall approach to data privacy, AI, and more,

The federal Liberal government has taken another crack at legislating privacy with the introduction of Bill C-27 in the House of Commons.

Among the bill’s highlights are new protections for minors as well as Canada’s first law regulating the development and deployment of high-impact AI systems.

“It [Bill C-27] will address broader concerns that have been expressed since the tabling of a previous proposal, which did not become law,” a government official told a media technical briefing on the proposed legislation.

François-Philippe Champagne, the Minister of Innovation, Science and Industry, together with David Lametti, the Minister of Justice and Attorney General of Canada, introduced the Digital Charter Implementation Act, 2022. The ministers said Bill C-27 will significantly strengthen Canada’s private sector privacy law, create new rules for the responsible development and use of artificial intelligence (AI), and continue to put in place Canada’s Digital Charter.

The Digital Charter Implementation Act includes three proposed acts: the Consumer Privacy Protection Act, the Personal Information and Data Protection Tribunal Act, and the Artificial Intelligence and Data Act (AIDA)- all of which have implications for Canadian businesses.

Bill C-27 follows an attempt by the Liberals to introduce Bill C-11 in 2020. The latter was the federal government’s attempt to reform privacy laws in Canada, but it failed to gain passage in Parliament after the then-federal privacy commissioner criticized the bill.

The proposed Artificial Intelligence and Data Act is meant to protect Canadians by ensuring high-impact AI systems are developed and deployed in a way that identifies, assesses and mitigates the risks of harm and bias.

For businesses developing or implementing AI this means that the act will outline criminal prohibitions and penalties regarding the use of data obtained unlawfully for AI development or where the reckless deployment of AI poses serious harm and where there is fraudulent intent to cause substantial economic loss through its deployment.

..

An AI and data commissioner will support the minister of innovation, science, and industry in ensuring companies comply with the act. The commissioner will be responsible for monitoring company compliance, ordering third-party audits, and sharing information with other regulators and enforcers as appropriate.

The commissioner would also be expected to outline clear criminal prohibitions and penalties regarding the use of data obtained unlawfully for AI development or where the reckless deployment of AI poses serious harm and where there is fraudulent intent to cause substantial economic loss through its deployment.

Canada already collaborates on AI standards to some extent with a number of countries. Canada, France, and 13 other countries launched an international AI partnership to guide policy development and “responsible adoption” in 2020.

The federal government also has the Pan-Canadian Artificial Intelligence Strategy for which it committed an additional $443.8 million over 10 years in Budget 2021. Ahead of the 2022 budget, Trudeau [Canadian Prime Minister Justin Trudeau] had laid out an extensive list of priorities for the innovation sector, including tasking Champagne with launching or expanding national strategy on AI, among other things.

Within the AI community, companies and groups have been looking at AI ethics for some time. Scotiabank donated $750,000 in funding to the University of Ottawa in 2020 to launch a new initiative to identify solutions to issues related to ethical AI and technology development. And Richard Zemel, co-founder of the Vector Institute [formed as part of the Pan-Canadian Artificial Intelligence Strategy], joined Integrate.AI as an advisor in 2018 to help the startup explore privacy and fairness in AI.

When it comes to the Consumer Privacy Protection Act, the Liberals said the proposed act responds to feedback received on the proposed legislation, and is meant to ensure that the privacy of Canadians will be protected, and that businesses can benefit from clear rules as technology continues to evolve.

“A reformed privacy law will establish special status for the information of minors so that they receive heightened protection under the new law,” a federal government spokesperson told the technical briefing.

..

The act is meant to provide greater controls over Canadians’ personal information, including how it is handled by organizations as well as giving Canadians the freedom to move their information from one organization to another in a secure manner.

The act puts the onus on organizations to develop and maintain a privacy management program that includes the policies, practices and procedures put in place to fulfill obligations under the act. That includes the protection of personal information, how requests for information and complaints are received and dealt with, and the development of materials to explain an organization’s policies and procedures.

The bill also ensures that Canadians can request that their information be deleted from organizations.

The bill provides the privacy commissioner of Canada with broad powers, including the ability to order a company to stop collecting data or using personal information. The commissioner will be able to levy significant fines for non-compliant organizations—with fines of up to five percent of global revenue or $25 million, whichever is greater, for the most serious offences.

The proposed Personal Information and Data Protection Tribunal Act will create a new tribunal to enforce the Consumer Privacy Protection Act.

Although the Liberal government said it engaged with stakeholders for Bill C-27, the Council of Canadian Innovators (CCI) expressed reservations about the process. Nick Schiavo, CCI’s director of federal affairs, said it had concerns over the last version of privacy legislation, and had hoped to present those concerns when the bill was studied at committee, but the previous bill died before that could happen.

Now the lawyers. Simon Hodgett, Kuljit Bhogal, and Sam Ip have written a June 27, 2022 overview, which highlights the key features from the perspective of Osler, a leading business law firm practising internationally from offices across Canada and in New York.

Maya Medeiros and Jesse Beatson authored a June 23, 2022 article for Norton Rose Fulbright, a global law firm, which notes a few ‘weak’ spots in the proposed legislation,

… While the AIDA is directed to “high-impact” systems and prohibits “material harm,” these and other key terms are not yet defined. Further, the quantum of administrative penalties will be fixed only upon the issuance of regulations. 

Moreover, the AIDA sets out publication requirements but it is unclear if there will be a public register of high-impact AI systems and what level of technical detail about the AI systems will be available to the public. More clarity should come through Bill C-27’s second and third readings in the House of Commons, and subsequent regulations if the bill passes.

The AIDA may have extraterritorial application if components of global AI systems are used, developed, designed or managed in Canada. The European Union recently introduced its Artificial Intelligence Act, which also has some extraterritorial application. Other countries will likely follow. Multi-national companies should develop a coordinated global compliance program.

I have two podcasts from Michael Geist, a lawyer and Canada Research Chair in Internet and E-Commerce Law at the University of Ottawa.

  • June 26, 2022: The Law Bytes Podcast, Episode 132: Ryan Black on the Government’s Latest Attempt at Privacy Law Reform “The privacy reform bill that is really three bills in one: a reform of PIPEDA, a bill to create a new privacy tribunal, and an artificial intelligence regulation bill. What’s in the bill from a privacy perspective and what’s changed? Is this bill any likelier to become law than an earlier bill that failed to even advance to committee hearings? To help sort through the privacy aspects of Bill C-27, Ryan Black, a Vancouver-based partner with the law firm DLA Piper (Canada) …” (about 45 mins.)
  • August 15, 2022: The Law Bytes Podcast, Episode 139: Florian Martin-Bariteau on the Artificial Intelligence and Data Act “Critics argue that regulations are long overdue, but have expressed concern about how much of the substance is left for regulations that are still to be developed. Florian Martin-Bariteau is a friend and colleague at the University of Ottawa, where he holds the University Research Chair in Technology and Society and serves as director of the Centre for Law, Technology and Society. He is currently a fellow at the Harvard’s Berkman Klein Center for Internet and Society …” (about 38 mins.)

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.