A common approach to AI ethics alone is unlikely to provide sufficient glue for robust cooperation on AI. Rather than a zero-sum game, many such efforts can be additive, benefiting global welfare. CIFAR is fuelling AI research and innovation. The multilateral and multistakeholder forums for AI governance and cooperation discussed above offer advantages and disadvantages. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. G-7 Science and Technology Minister’s Declaration on COVID-19, May 28, 2020;  https://www.state.gov/G-7-science-and-technology-ministers-declaration-on-covid-19/, Saudi Arabia G-20, G-20 Digital Economy Ministers Meeting, Ministerial Declaration, July 22, 2020. At the same time, China combines a restricted domestic market with an international approach to AI that includes aggressive acquisition of intellectual property (IP) and innovation from rivals, government subsidies that tilt the playing field towards Chinese companies, and strategic engagement in international forums for standards and norms that support China’s applications of AI. Stay up to date on news & ideas from CIFAR. first propose an efficient untargeted attack, called the FGSM, to generate adversarial samples in the L ∞ neighbor of the benign samples, as shown in Fig. The recommendations that follow are based on three interrelated goals that should be a focus for the new administration and its international engagement on technology and AI: (1) developing avenues of cooperation for global development of AI, (2) effective alignment with the EU on AI, and (3) addressing the China challenge. In addition, there is funding for AI R&D as well as AI research institutes.20 In 2020 alone, the federal government has spent almost $1 billion in nondefense artificial intelligence research and development21 and announced $140 million in awards over five years to seven NSF-led AI Research Institutes. Salakhutdinov and Hinton, AI-Stats 2007: 6-layer NN 784-2500-2000-1500-1000-500-10 (on GPU) [elastic distortions] none: 0.35: Ciresan et al. Indeed, China has developed its own AI ethical principles that align with western ethical principles in material ways.53 China’s participation in the G-20 and engagement in international standards bodies provide opportunities to influence Chinese policies and practices. The latter produced some high-level agreement on principles while the former spawned GPAI, which has the potential to help put principles into practice. The economic and strategic importance of AI has led to a proliferation of AI policies and strategies globally. It also requires a more strategic approach to how Chinese researchers engage, one that avoids shutting the door entirely to collaboration but is clear-eyed about the risks and takes appropriate measures to mitigate these. He also applies machine learning to various problems in artificial intelligence, notably the automated design and analysis of algorithms for solving hard computational problems. Joshua P. Ongoing U.S. efforts to foster international cooperation in AI include bilateral cooperation agreements such as the U.S.-U.K. Cooperation in Artificial Intelligence Research and Development,23 hosting and engaging in international and multistakeholder initiatives such as the G-7 Science and Technology Ministerial Meeting that launched the Global Partnership on AI, and participation in common and formalized AI principles for the innovative and trustworthy development and application of AI such as the OECD Principles on AI discussed below. The Canadian Institute for Advanced Research (CIFAR) is leading the Government of Canada's CAD$125M Pan-Canadian Artificial Intelligence Strategy, which promotes collaboration, talent building and research on AI among Canada's already well-developed centres of AI expertise. This dramatic expansion in funding and interest reflects advances in what AI can do. As outlined above, this subject has been a common thread in government policies as well as a frequent focus of frameworks developed in civil society, academia, and industry. Both SDOs and multistakeholder forums are important vehicles for integrating nongovernmental bodies into AI policymaking. As technology increasingly becomes an object of concern to governments around the world, a broad range of issues from economic development, competitiveness, and digital trade to competition and content on platforms and social media, data flows, privacy, cybersecurity, and other issues have emerged as mainstream concerns alongside AI. In academia, the share of conference papers that focus on AI tripled from 3 percent in the late 1990s to 9 percent in 2018; private funding has likewise ballooned, with global private AI investment exceeding $70 billion in 2019. CIFAR's annual round-up of advances and impact from the CIFAR Pan-Canadian AI Strategy. The notion that there might be ways to engage with China on AI might be controversial, but it is the case that not all uses of AI by China are unethical or create economic risks. As reflected in the foregoing discussion, there are numerous avenues of engagement on international AI cooperation that the Biden-Harris administration should continue to engage with and support. Advance national AI initiatives by supporting a national research community on AI through training programs, workshops, and other collaborative opportunities. The sheer size of China, its access to population-scaled datasets, and its willingness to use state power to boost domestic AI at the expense of AI developed elsewhere, also presents unique challenges to a model for successful AI development driven by markets and open flows of technology and information.41 These challenges arise from government-sponsored cyber theft of commercial technology, state-directed strategic acquisition of western technology, forced data localization requirements, and restrictions on data flows and access to the Chinese market for American and other technology companies. Rather than bet on one horse for international engagement on AI (and related issues), the U.S. should play the field, seeking out like-minded partners and the best pathways for specific issues and building outward where it can. In 2017, the Government of Canada appointed CIFAR to develop and lead a $125 million Pan-Canadian Artificial Intelligence Strategy, the world’s first national AI strategy. Meltzer., Cameron Kerry and Alex Engler, “Submission to the EC White Paper on Artificial Intelligence, the importance and opportunities of transatlantic cooperation on AI”, June 2020. Such policies could distort the development and benefits of AI for humanity, make the world less secure for the U.S. and allies, and markets less receptive to U.S. products and services. This values-based rationale for AI cooperation has been given content with the development by the AI High Level Expert Group (HLEG) of international ethical standards, where this forms a basis for EU goals of “upward regulatory convergence,” with the aim of creating a level playing field on AI.24. 5430, entitled “New Jersey Algorithmic Accountability Act” and would introduce mandatory impact assessments on “high-risk” automated decision-making systems. In 2017, Canada became the first country to adopt a national AI strategy. As the Biden administration re-engages with the world and rebuilds alliances, it needs to develop a strategy for international engagement that articulates a comprehensive and balanced vision of how to harness the benefits and address the challenges of technology across this range of issues. Commonalities in governments’ AI policies, • Establish national AI research centers, • Remuneration incentives and visa policies to attract international talent, • Increase AI programs or components in master’s and doctoral programs, • Increase reskilling/training programs for workers, • Incorporate more STEM (including AI) in primary to undergrad curriculum, • Establish digital innovation hubs to connect companies to AI expertise, • Use state investment funds to support startups and leverage, • Make public datasets available for AI development, • Develop regulation to address AI specific opportunities and risks, • Develop cybersecurity policies for infrastructure and data, including supply chains, • Pilot AI-based solutions in public service, • Engaging in international organizations, working with international partners, • Establishing international public-private partnerships, • Promote use of AI to solve common challenges (SDGs) and advance debate on issues arising from AI (robot alienation/citizenship, global safety). The EU white paper states that “The EU will continue to cooperate with like-minded countries, but also with global players” (which presumably include China), with the proviso that such cooperation “promotes the respect of fundamental rights, including human dignity, pluralism, inclusion, non-discrimination and protection of privacy and personal data. China’s AI strategy also needs to be assessed alongside its efforts to internationalize its technology and standards, including along the “Digital Silk Road” as a component of the Chinese Belt and Road Initiative, and by proactive and strategic engagement in international standards organizations.33, China’s AI policies also include some elements of international cooperation on AI. But not all AI involves brute force analysis of vast arrays of data. Post was not sent - check your email addresses! Marc G Bellemare is a research scientist at Google Brain in Montreal, Canada; CIFAR Learning in Machines & Brain Fellow; adjunct professor at McGill University; and was recently awarded a Canada CIFAR AI chair, held at the Montreal Institute for Learning Algorithms (Mila). As these AI regulatory efforts take shape, international cooperation can minimize unnecessary divergence and find areas where alignment is possible. All Rights Reserved. New rules affecting AI are being developed in trade agreements such as U.S.-Mexico-Canada Agreement and Comprehensive and Progressive Agreement for Trans-Pacific Partnership, including commitments to sustain cross-border data flows and to exclude data localization requirements (subject to appropriate exceptions), as well as commitments to protecting privacy and the interoperability of such regimes.50 There are also AI-specific provisions in the Digital Economy Partnership Agreement among Singapore, New Zealand, and Chile and in the Australia-Singapore Digital Economy Agreement.51 In addition, Asia Pacific Economic Cooperation (APEC) has an increasingly robust work program on digital trade issues, including on developing interoperability mechanisms to facilitate data flow among APEC economies. Memorandum for the Heads of Executive Departments and Agencies, “Guidance for Regulation of Artificial Intelligence Applications”. 2557). Indeed, how the rest of the world develops and uses AI presents the U.S. a key opportunity for global leadership on AI development and norms and in support of broader development needs. 2020-1, John P. Holdren, 2016., Preparing for the Future of Artificial Intelligence”, Executive Office of the President, National Science and Technology Council, Committee on Technology, October 2016. This led to publication of the Commission’s White Paper on Artificial Intelligence in February 2020, envisioning a “European ecosystem of excellence and trust.” Proposals in the white paper include measures to streamline research and foster collaboration on AI among member states, and increasing investment into AI development and deployment by 70 percent. Goodfellow et al. Media Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. He is a recipient of the CIFAR AI Research Chair. Supporters A former member of Google Brain, Alex’s graduate work in machine learning has been among the most influential in the field. On Wednesday December 23 I had the honor of participating in “AI Debate 2”, a symposium organized by Montreal AI, which brought together an impressive group of scholars to discuss the future of AI. The development of principles for ethical use of AI has been a major focus for governments as well as international organizations, industry, academia, and civil society.3 The U.S. government has also been a key player in developing AI ethical principles. 2231) were introduced in Congress in 2020, and New Jersey has introduced a similar bill, A.B.

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