Photo Credit: Prof Pina D'Agostino

Prof Giuseppina D’Agostino is the Founder & Director of IP Osgoode, the IP Intensive Program, and the IP Innovation Clinic, the Editor-in-Chief for the IPilogue and the Intellectual Property Journal, and an Associate Professor at Osgoode Hall Law School. She is also very proud of her new book!

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I am excited to share that I just published a collection on Artificial Intelligence (AI) and the law, Leading Legal Disruption: Artificial Intelligence and a Toolkit for Lawyers and the Law (Thomson Reuters 2021). Co-edited with Dr. Aviv Gaon and Carole Piovesan, the book provides a provocative analysis on the emerging terrain of AI and how it interrogates various areas of the law. The book, that features a foreword from the Hon. Marshall Rothstein (formerly of the Supreme Court of Canada), is an international collaboration of thought leaders in AI, with contributors from Canada, the USA, Europe and Israel. Issues discussed include intellectual property, privacy, contract law, regulation, governance, ethics, business and more. Importantly, such issues merit a toolkit of practical and international perspectives as they are increasingly complex and ajurisdictional. ����

In many ways this book is also a reflection of Osgoode’s strengths in AI. My co-editors, Dr. Aviv Gaon, Director at IDC Herzliya of Experiential Programs, is a PhD graduate (class of 2019) publishing several other books on AI and emerging technology, and Carole Piovesan (class of 2009) has co-founded her own firm, INQ Law. ��I am myself an LL. B graduate from Osgoode (class of 1999), eventually returned as faculty to found and run IP Osgoode and I am currently co-chairing the 91��ɫ AI & Society Task Force, among many other initiatives in this space.

I am particularly thankful to the Osgoode JD students who provided helpful research assistance: Elif Babaoglu, Daniel Joseph, Joseph Simile, Rachel Marcus, Christopher Tsuji, and Julianna Felendzer.

I am most grateful for the enthusiastic endorsements by Prof David Vaver (Professor of Intellectual Property Law, Osgoode; Emeritus Professor of Intellectual Property & Information Technology Law, University of Oxford), Prof Jane Ginsburg (Morton L. Janklow Professor of Literary and Artistic Property Law, Columbia University School of Law), Justice Michael Manson (Federal Court of Canada), and Dan Bereskin (Partner, Bereskin & Parr LLP) all which can be read on the back cover.

They say you can’t judge a book by its cover, but I particularly like this one, inspired by an AI and suggestive of our youth, our future ultimately grappling with AI and other emerging technology, that will iterate in every generation.

I look forward to hearing from you on your thoughts on the book (and the cover!). You may order your copy��here.

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Reposted here is the Abstract of an article by Aviv Gaon and Ian Stedman to be published in a forthcoming issue of the .�� A copy of the article is also available on .

is a��Lecturer at The Interdisciplinary Center Herzliya, Israel, and PhD Candidate at Osgoode Hall Law School.

is a Fellow in Artificial Intelligence Ethics and Law at SickKids’ Centre for Computational Medicine and PhD Candidate at Osgoode Law School.

The post A Call to Action: Moving Forward with the Governance of Artificial Intelligence in Canada appeared first on IPOsgoode.

Artificial intelligence (AI) can create inherent benefits for all sectors, but governance of the technology is lagging, forcing industry experts and academics to confront the legal and ethical issues that this technology raises.

At Bracing for Impact: The Artificial Intelligence Challenge, a one-day conference hosted by IP Osgoode on Feb. 2, international speakers gathered to encourage the creation of a road map for the legal treatment of AI issues. Touching on cybersecurity, intellectual property and privacy, the point of the day was clear: AI is here and society must catch up.

Ryan Calo, an associate professor at the University of Washington School of Law, joined the conference by teleconference from the United States and addressed policy issues that can arise when AI is used. He highlighted implications for justice and equity as AI may not benefit all levels of society.

“We’re experimenting with artificial intelligence on populations that are the most vulnerable and have the fewest resources to seek redress,” he said, explaining that in some instances AI may not work well for people based on their race.

“There’s anecdotal evidence that people of colour, their hands are not always recognized by automated dryers or automated faucets because those faucets have been calibrated to white hands. Similarly, there’s evidence that, for example, people of Taiwanese ancestry are having an issue where facial recognition software meant to optimize cameras are not taking pictures or are warning that the subject of the picture actually has their eyes closed or is squinting. Because, again, the database upon which the software’s been trained contained few Taiwanese faces,” he added.

Calo noted that algorithms can reinforce bias, which can be particularly concerning if an AI is being used to determine the length of a prison sentence or being used by police in enforcement. He said this also leads to challenging questions about when AI is safe and can be certified.

“For example, if you’re going to be operated on by a surgeon, she’s got to go to medical school and she’s got to pass her board. But under development today in a number of labs are autonomous surgical units, which are amazing on one level because they allow for standardized and presumably, one day, safer surgery, or even surgery in places where a surgeon isn’t available to do the surgery. But at the same time, how do you go about establishing that the surgeon is adequate given that they’re not going to go to medical school and they’re not going to pass a board?” he said, asking what tests and standards are going to be used to vet AI when they replace a human in their work.

With AI being able to replace an increasing amount of human roles in the workforce, Calo noted that governments need to be alive to the issue of taxation and displacement of labour. He noted that the impact on income tax could be huge if in a short period of time a large amount of jobs are given to robots.

Calo said governments need to accrue expertise in technology in order to understand the impacts AI is having and create policy that will keep people safe.

“It’s very unlikely that we will come up with the wisest laws possible for infrastructure of AI in the absence of lawmakers and regulators and judges that have an inadequate mental model of the technology,” he said, adding that investing in research is key.

Society must make sure “to invest in basic, interdisciplinary research,” he said, “to not only further the state of AI, but also the state of social impact research about AI is critical. Thoughtful procurement — one of the issues we’re having today is people are buying AI enabled systems for use in places, like courts, without really understanding what they’re buying or understanding the consequences,” he explained.

Calo noted that regulation can go a long way in mediating issues surrounding AI, but an unusual paradox of wanting change, but insisting society remains the same is acting as a barrier.

“Artificial intelligence is going to remake every aspect of society, but there shouldn’t be any change somehow to law and legal institutions. That strikes me as deeply implausible. Either artificial intelligence is all hype or we’re going to need laws to address it. I think regulation at some level is inevitable. I think it’s premature today to top down regulate everything, but I think we should be watching for opportunities where there’s a gap between what the law assumes and what is happening on the ground in practice,” he said.

Maura Grossman, a research professor at the David R. Cheriton School of Computer Science at the University of Waterloo, like Calo, noted in her address to the conference that society needs to examine who benefits from the results of AI.

“I think we have to move away from the zero sum game and find ways to make this a win-win proposition for everybody,” she said.

Grossman was working at a large law firm in New 91��ɫ when she was faced with the challenge of going through millions of documents with only five lawyers to do document review.

“It occurred to me that technology is the problem. Technology needs to be the answer, so I started to go to computer science programs and started to learn about machine learning,” she said.

Grossman was at one of these conferences when she met Gordon Cormack, a researcher in information retrieval, and together they began a research study pitting lawyers against algorithms.

“Gordon and I took 896,000 documents that were part of the Enron dataset that was released during the course of that litigation and we took third year law students who had volunteered their time pro bono, and we took contract attorneys who volunteered their time, and then we took some of these supervised machine learning algorithms and we put them back to back on five requests for production. We said ‘find all of the documents that relate to these topics.’ And then we looked at who did better,” she explained.

The results fell staggeringly in favour of the algorithm side with the AI making fewer mistakes and being highly efficient. Grossman thought these results would lead the legal profession to use algorithms across the board, but she didn’t take into account the large amount of people who make money doing document review.

“We don’t forgive errors in algorithms and we don’t believe they can learn for some reason, even though we talked today about one of the scarier things about algorithms is that they can learn,” she said, noting that the legal profession is slow to adopt to technology that it doesn’t trust.

“Obviously we don’t want people to overuse algorithms and over-trust them when they shouldn’t, but they should use them when it’s logical,” she added.

Grossman used the example of air travel as a time when people rely on AI even when they doubt its safety.

“When people say to me ‘I could never use one of these algorithms to do document review. It’s too risky.’ And then I’ll say ‘do you get on an airplane?’ And they say ‘of course I do.’ Are you aware that there are four minutes of that flight that is flown by a human. The rest is flown by an algorithm. And almost all the accidents that occur, occur in those four minutes or in transition from the algorithm to the human,” she explained.

Grossman said in order for people to trust in AI they have to feel some sense of control and more peer-reviewed research is needed to keep the technology moving forward.

“We really need people to take the time to do the careful research. We need the funding of the research. I think that convinces people in the long run,” she said.

Amanda Jerome is a Digital Reporter for The Lawyer’s Daily

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, a conference organized by IP Osgoode earlier this year, included a panel entitled “AI & Industries” that covered a wide range of current issues as a result of AI technologies and anticipated other looming issues. The panelists shed light on what may be sensible to expect from AI governance in the near future and hinted at what may constitute the cornerstones for effective AI regulation.

Competent practice management

As I boiled down the main threads called forth by the panel, I realized they provided scope for an interesting case for AI regulation in light of a lawyer’s duty of , as per the Law Society of Ontario’s Rules of Professional Responsibility (“Rules”). Practice management by way of available systems, technologies, and other methods is one of the areas of competence where lawyers must meet minimum standards to ensure they serve clients well, timely, and at a reasonable cost (see, , and commentary ). These three mandates of competent practice management provide an initial framework for addressing the concerns raised by the panelists and gauging whether the deployment of AI meets minimum ethical standards in different circumstances.

Well-served society

To gauge the appropriateness of AI, one may need to make an initial assessment of how well the deployment of a specific technology serves society. Generally, the in favour of the machines, for the high efficiency and low likelihood of errors technology offers. Dr.��, Chief Pediatrician at the Hospital for Sick Children, discussed the benign effects that flow from the synergy��between artificial and human intelligence, while Prof. , Professor at the UC Berkeley School of Information, made a counterpoint by touching on problems related to inappropriate uses of AI.

Dr. Cohn noted that AI is a tool that allows professionals —in his particular case, physicians — to make better informed decisions. AI-enabled tools do not eliminate (medical) school training nor the need for a skill set based on first principles for their use (see, though, concerns with deskilling and ). AI has been crucial, Dr. Cohn added, for the development of medicine’s three main scopes: prediction, prevention, and precision. He remarked that AI-assisted clinical trials are cheaper, faster and more informative; yet, the doctor still bears the decision-making responsibility and��the human element that allows for effective communication with patients. As to preventive medicine, Dr. Cohn remarked that AI data analytics tools permit physicians to quickly identify environmental risk factors and promptly propose actions in response. Finally, Dr. Cohn noted that the third scope of medicine — precision — has improved substantially with AI technologies, which are able to identify pattern deviations and that could take even the most experienced, senior professional .

Prof. Mulligan presented a counterpoint related to the inappropriate use of AI, such as when this unduly interferes with professional judgement. Two examples arise in the context of the and the healthcare industry. In both fields, on algorithms that are not always free of and may trigger . Prof. Mulligan argued, “error avoidance is an ethical imperative, both to maximize positive, short-term consequences and to ensure that, in the long run, informatics is not associated with error or carelessness, or the kind of cavalier stance sometimes associated with high-tech boosterism.” She added, citing K. W. Goodman, that the expansion of the field should be encouraged “”. Transparency and proper justification of decision-making by professionals that rely heavily on AI may provide a solution to address undue bias built into the algorithms.

Time is of the essence

, Professor at the University of Washington School of Law, raised the question of whether it is premature to think about regulation. Prof. Calo , while it may be premature to top-down regulate every aspect of life that AI touches upon, a sensible approach towards governance involves “watching for opportunities where there is a gap between what law assumes and what is happening on the ground in practice”.

In addition to confronting the legal and ethical social issues that may arise from the ever-broader use of AI, Prof. Calo noted that we should also be attentive to the issues of justice and equity that lurk in AI governance. There are concerns in our community respecting the inappropriate use of AI and, at a macro level, there is still some degree of uncertainty as to whether AI’s benefits and costs will be within reach of everyone equally.

Reasonable cost

Prof. , the Canada Research Chair in Ethics Law and Technology at the University of Ottawa, tackled the problem of costs associated with AI use. In his presentation, he warned “to accept that things will be more expensive because we will have things that we never had before is to support a neo-liberal fantasy”. As AI tends to outperform humans in virtually every field, and as we increasingly seek ultimate efficiency in service provision, Prof. Kerr noted that this ongoing search for ever-enhancing efficiency may result in elevated costs whenever AI is engaged.

Indeed, it may be hasty to assume that AI, and technology in general, will always but with no delay will become largely democratized. Although tech goods have become in the past decades, and the ’ are what have increased the availability of these goods in the market. What must not be underrated as a associated with AI is the to build, maintain, and monitor . Companies and other service providers across industries are likely to make poor financial decisions if they cut expenses in this area and disregard this risk factor in their business as they might eventually feel the backlash from the .

The monetary costs associated with and the are hardly overemphasized. As a result, cost regulation of AI may warrant increased security to stakeholders on a more regular basis, while also preventing AI from leveraging vulnerabilities in sensitive fields such as the healthcare industry.

Good governance and competent management of AI, as with the provision of legal services, may be tied to serving society well, timely, and at a reasonable cost. Hence, because time is of the essence, it flows logically that society will be underserved if the efforts to bring the rule of law into the technological world become deferred.

Bruna D. Kalinoski is a contributing editor for the IPilogue and holds an LLM from the Osgoode Professional Development Program at 91��ɫ.

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First Off, what really is AI?

Traditionally, computers were thought to be creatures of instructions. However, over six decades ago, the umbrella term, Artificial Intelligence, was coined to refer to a computer’s ability to make decisions without direct human intervention. According to Arthur Samuels, it is “a field of study that gives computers the ability to learn without being explicitly programmed.” that allow for human-like responses to problems by identifying patterns from enormous pools of data. From , , , to , AI is literally in our faces and has the potential to infiltrate nearly every aspect of our lives.

AI Poses Both a Risk and Opportunity

Cyberspace, despite its many advantages, continues to be exploited. Since 2013, . AI provides a unique opportunity to bolster cybersecurity solutions by utilizing predictive analysis capabilities. Almost and it appears cybercriminals are always a step ahead because .

AI is a game changer, which can allow for a more proactive and dynamic approach to cybersecurity. For example, deep learning technologies can , run numerous simulations, and predict potential attacks and respond accordingly.

However, AI comes with a number of risks, such as threat agents using AI to develop automated attacks that learn and adapt to vulnerable systems in real time. AI models also thrive on data, so bias or false positives could adversely affect decisions or actions taken by the algorithm. Issues of accountability and even tort liability may arise if the AI model goes rogue and does what it was not programmed to do.

Managing Director and CEO of ABCLive Corporation, , expressed that the capacity of AI to learn and evolve will undoubtedly exceed human capacity. For example, in 2016, where its sutures were found to be superior and done with more precision. As astounding as this may be, there are still risks to consider. If this AI bot was somehow compromised and succumbed to a cybercriminal’s ransomware attack, human lives could potentially be at risk.

Privacy vs. Security – Do We Tradeoff or Can We Have Both?��

So, how can these risks be mitigated? It appears that efforts to do so could impact privacy rights or even the fabric of a nation’s security.

According to Benjamin Franklin, Jurisdictions around the world continue to struggle with this concept, especially in light of autonomous AI weapons and other national security concerns. , special counsel, Yigal Armon & Co. and former Israeli legal advisor for the National Security Council, argued that an invasion of privacy might be a necessary trade off in some instances, . Keidar posited that while an individual’s privacy rights should be protected, the concept of freedom also extends to border security issues and other national security concerns. Clearly, this topic is a mammoth task for governments, so a natural corollary is that in order to preserve the security architecture of a nation, tools need to be developed to allow for a certain level of security. Consequently, in an attempt to keep citizens safe, this invariably might encroach on individuals’ privacy rights. Conversely, privacy expert maintains that it is quite possible to have both privacy and security. Cavoukian argues that over one’s data and this should be reflected in free and democratic societies. Her proposed approach seeks to change the paradigm from flawed ‘zero-sum’ models to ‘positive-sum’ models. Privacy and security would no longer be competing interests because measures safeguarding privacy would be proactively embedded into technological operations and security considerations. Cavoukian predicts that the implementation of the (GDPR) in May 2018 will replace current privacy laws in all European Union member countries, making privacy the default. As such, the use of data will be ‘user-centric’ and only used for the purposes it was collected for. Entities who do not abide by the GDPR could face fines of up to 4% of their global revenue. Cavoukian’s proposed would allow for transparency and oversight of algorithms with high levels of accountability, which could help to facilitate ethical algorithmic designs and data symmetry.

Is Legislation the Answer?

Technology enthusiasts around the world, including Stephen Hawking and Elon Musk, argue that AI is an existential threat to humanity and are calling for nations to . Indeed, there are concerns about AI’s impact on weapons and privacy rights, but whether legislation can restrain this ‘monstrous beast’ is moot. Not only are there jurisdictional issues as it relates to regulating AI in a borderless Cyberworld, but AI is evolving and do not have a good of .

Even if policy makers manage to develop a legislative framework for AI, that is only one aspect of this labyrinthine technology. Other issues to grapple with include potential job losses in those roles at risk of automation. For example, a revealed that due to AI bots taking over assembly line work traditionally done by humans. ��due to automation as well. Even the legal fraternity is not immune, especially with talks of possibly replacing lower-level legal assignments carried out by articling students or junior lawyers. Governments would also need to consider wider economic implications such as the decline in tax dollars received from those jobs.

AI could boost by 2035, so policy makers should be cautious in over regulating this invaluable resource that could drive innovation. Over regulation could possibly stifle growth in AI by making it a less attractive field for investors. For example, a potential backlash could be Google and other tech giants such as no longer investing in Canada.

Perhaps more work needs to be done in developing ethical oversight of AI; particularly teaching AI the unique aspects of human values like privacy and freedom. who have been for over 30 years, so their expertise in determining the extent to which these principles can be reflected in AI technologies could then inform legislation. Canada would then need to focus its policy lens on training and research, thus building and sustaining Canada’s AI ecosystem.

Andrae Campbell is an IPilogue Editor and an LLM Candidate at Osgoode Hall Law School.

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Bracing for Impact – The Artificial Intelligence Challenge (A Road Map for AI Governance in Canada)

Date: February 2, 2018

Location: Osgoode Hall, 130 Queen St. W., Toronto, Canada

Time: Conference (9:00 AM to 4:30 PM); Cocktail Reception (4:30 PM to 6:00 PM)

TO REGISTER CLICK

Registration rates are as follows:
Students: $25+HST
General Admission: $75+HST
Live WebCast: $10+HST

Speakers and Panel Chairs will be registered on a complimentary basis. Please do not register if you are a speaker or panel chair.

Recent developments in artificial intelligence, and especially machine learning technology, automated vehicles, and genetic enhancement pose a challenge to governments in Canada and abroad. At the current stage, government policy regarding the possible technological changes must be studied.

The conference will focus on the following panel topics:

Panel I – AI – IP & Commercialization Issues

Future developments in the field of AI pose a challenge to intellectual property. The current legal regime does not offer protection for AI creations. Thus, registering AI patents and allocate copyright protection for AI inventions and works is not yet possible. Subsequently, AI creations might fall under the public domain. We wish to address these concerns and to offer new insights and suggestions for the upcoming era.

Panel II – AI & Industry

The Path of Law, as Justice Holmes articulated in his seminal paper, is in constant development – like the development of a planet – each generation taking the necessary step forward. Advancements in AI promise to change our society in the years to come and will drastically affect every aspect of our legal norms. It is therefore crucial for us to confront the legal issues that these advancements will doubtless give rise to and to aspire to create guidelines to help us navigate the inevitable changes to our society. In this regard, we hope that Canada can provide a road map for the legal treatment of AI issues in several key areas.

Panel III – Cybersecurity in the AI Era

Cybersecurity is quickly emerging as a crucial component of every nation's security efforts. Recent events around the world have proven the importance of developing the tools needed to face this challenge. AI poses both a risk and opportunity. This Panel will explore the possible changes in modern cybersecurity warfare in the AI era. In doing so, it will bring to the table several experts in the field in an effort to shape a better government cybersecurity policy for the next generation.

Panel IV – AI For Social Good

keeps widening as inequality grows markedly. Artificial Intelligence holds great potential for helping us to lessen these inequalities. While AI is often viewed as a threat to social justice, the opposite may in fact be true. Machine learning in language translation technology can collapse the barriers between third world countries and the West. Algorithmic decision-making can lessen the bias effects toward minority groups. From transportation, healthcare, agriculture to sustainably and governance - the positive applications of AI are unlimited in scope.

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