Corporate Governance of Artificial Intelligence in the Public Interest

Corporations play a major role in artificial intelligence (AI) research, development, and deployment, with profound consequences for society. This paper surveys opportunities to improve how corporations govern their AI activities so as to better advance the public interest. The paper focuses on the roles of and opportunities for a wide range of actors inside the corporation—managers, workers, and investors—and outside the corporation—corporate partners and competitors, industry consortia, nonprofit organizations, the public, the media, and governments. Whereas prior work on multistakeholder AI governance has proposed dedicated institutions to bring together diverse actors and stakeholders, this paper explores the opportunities they have even in the absence of dedicated multistakeholder institutions. The paper illustrates these opportunities with many cases, including the participation of Google in the U.S. Department of Defense Project Maven; the publication of potentially harmful AI research by OpenAI, with input from the Partnership on AI; and the sale of facial recognition technology to law enforcement by corporations including Amazon, IBM, and Microsoft. These and other cases demonstrate the wide range of mechanisms to advance AI corporate governance in the public interest, especially when diverse actors work together.

[1]  Alec Radford,et al.  Release Strategies and the Social Impacts of Language Models , 2019, ArXiv.

[2]  Stephanie M. Tully,et al.  The Role of the Beneficiary in Willingness to Pay for Socially Responsible Products: A Meta-Analysis , 2014 .

[3]  Luciano Floridi,et al.  From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices , 2019, Science and Engineering Ethics.

[4]  C. Edquist,et al.  Public Procurement for Innovation as mission-oriented innovation policy , 2012 .

[5]  Inioluwa Deborah Raji,et al.  Model Cards for Model Reporting , 2018, FAT.

[6]  Jeffrey N. Gordon,et al.  The Oxford Handbook of Corporate Law and Governance , 2018 .

[7]  Elizabeth Gibney The battle for ethical AI at the world’s biggest machine-learning conference , 2020, Nature.

[8]  Ghislaine M. Lawrence The social construction of technological systems: new directions in the sociology and history of technology , 1989, Medical History.

[9]  Seth D. Baum,et al.  On the promotion of safe and socially beneficial artificial intelligence , 2017, AI & SOCIETY.

[10]  Mariarosaria Taddeo,et al.  Artificial Intelligence and the ‘Good Society’: the US, EU, and UK approach , 2016, Sci. Eng. Ethics.

[11]  Matthew U. Scherer Regulating Artificial Intelligence Systems: Risks, Challenges, Competencies, and Strategies , 2015 .

[12]  Ulrik Franke,et al.  The cyber insurance market in Sweden , 2017, Comput. Secur..

[13]  Pompeu Casanovas,et al.  The middle-out approach: assessing models of legal governance in data protection, artificial intelligence, and the Web of Data , 2019, The Theory and Practice of Legislation.

[14]  Luciano Floridi,et al.  Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation , 2017 .

[15]  Yavar Bathaee,et al.  The Artificial Intelligence Black Box and the Failure of Intent and Causation , 2018 .

[16]  Michael A. Osborne,et al.  The future of employment: How susceptible are jobs to computerisation? , 2017 .

[17]  Timnit Gebru,et al.  Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification , 2018, FAT.

[18]  Donald J. Trump,et al.  Executive Order 13859: Maintaining American Leadership in Artificial Intelligence , 2019 .

[19]  R. Gilson From Corporate Law to Corporate Governance , 2016 .

[20]  Ben Wagner,et al.  Regulating transparency?: Facebook, Twitter and the German Network Enforcement Act , 2020, FAT*.

[21]  Inioluwa Deborah Raji,et al.  Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing , 2020, FAT*.

[22]  C. Cauffman Robo-liability: The European Union in search of the best way to deal with liability for damage caused by artificial intelligence , 2018, Maastricht Journal of European and Comparative Law.

[23]  Anna Jobin,et al.  The global landscape of AI ethics guidelines , 2019, Nature Machine Intelligence.

[24]  J. Tschirhart,et al.  Alternatives to traditional regulation , 1989 .

[25]  Andrew McCallum,et al.  Energy and Policy Considerations for Deep Learning in NLP , 2019, ACL.

[26]  Kirsten E. Martin,et al.  Stakeholder Capitalism , 2009 .

[27]  R. Freeman Strategic Management: A Stakeholder Approach , 2010 .

[28]  Seth D. Baum,et al.  Medium-Term Artificial Intelligence and Society , 2020, Inf..

[29]  Charlotte Stix,et al.  A survey of the European Union's artificial intelligence ecosystem , 2020, SSRN Electronic Journal.

[30]  T. Luca,et al.  The Market for Virtue: The Potential and Limits of Corporate Social Responsibility , 2006, Perspectives on Politics.

[31]  J. Black,et al.  Making a success of Principles-based regulation , 2007 .

[32]  L. Georghiou,et al.  Public procurement and innovation?Resurrecting the demand side , 2007 .

[33]  Joseph R. Herkert,et al.  The growing gap between emerging technologies and legal-ethical oversight : the pacing problem , 2011 .

[34]  Gary E. Marchant,et al.  The Coming Collision Between Autonomous Vehicles and the Liability System , 2012 .

[35]  L. DeNardis,et al.  Multistakeholderism: anatomy of an inchoate global institution , 2015, International Theory.

[36]  Jonas Schuett A Legal Definition of AI , 2019, SSRN Electronic Journal.

[37]  N. Oreskes,et al.  Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues from Tobacco Smoke to Global Warming , 2010 .

[38]  Miles Brundage,et al.  The Role of Cooperation in Responsible AI Development , 2019, ArXiv.

[39]  A. Bradford The Brussels Effect: How the European Union Rules the World , 2020 .

[40]  G. Marchant “Soft Law” Governance of Artificial Intelligence , 2019 .

[41]  Michael Denga Deliktische Haftung für künstliche Intelligenz , 2018, Comput. und Recht.

[42]  The FTC as Internet Privacy Norm Entrepreneur , 2001 .

[43]  S. Baum,et al.  Liability Law for Present and Future Robotics Technology , 2017 .

[44]  Ryan Calo,et al.  Artificial Intelligence Policy: A Primer and Roadmap , 2017 .

[45]  Martina Gillen,et al.  Internet Co-Regulation: European Law, Regulatory Governance and Legitimacy in Cyberspace , 2012, Int. J. Law Inf. Technol..

[46]  Gillian K. Hadfield,et al.  Regulatory Markets for AI Safety , 2019, ArXiv.

[47]  Allan Dafoe,et al.  The Windfall Clause: Distributing the Benefits of AI for the Common Good , 2019, AIES.

[48]  J. Zeitlin Extending experimentalist governance? : the European Union and transnational regulation , 2015 .

[49]  Millicent Chang,et al.  Board Gender Diversity and Corporate Response to Sustainability Initiatives: Evidence from the Carbon Disclosure Project , 2015, Journal of Business Ethics.

[50]  Eva Thelisson,et al.  Regulatory Mechanisms and Algorithms towards Trust in AI / ML , 2017 .

[51]  Olivia Johanna Erdélyi,et al.  Regulating Artificial Intelligence: Proposal for a Global Solution , 2018, AIES.

[52]  Shane Legg,et al.  Universal Intelligence: A Definition of Machine Intelligence , 2007, Minds and Machines.

[53]  Flora Graham,et al.  Daily briefing: San Francisco bans facial-recognition technology , 2019, Nature.

[54]  S. Verba,et al.  Political culture and political development , 1965 .

[55]  K. Blind,et al.  The impact of standards and regulation on innovation in uncertain markets , 2017 .

[56]  Ryan Calo The Case for a Federal Robotics Commission , 2014 .

[57]  Francesca Rossi,et al.  AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations , 2018, Minds and Machines.

[58]  Chris Russell,et al.  Counterfactual Explanations Without Opening the Black Box: Automated Decisions and the GDPR , 2017, ArXiv.

[59]  Wendell Wallach,et al.  An Agile Ethical/Legal Model for the International and National Governance of AI and Robotics , 2017 .

[60]  Russell T. Vought Memorandum for the Heads of Executive Departments and Agencies: Federal Data Strategy - A Framework for Consistency , 2019 .

[61]  Kia Javanmardian,et al.  Confronting the risks of artificial intelligence , 2019 .

[62]  Seth D. Baum Superintelligence Skepticism as a Political Tool , 2018, Inf..

[63]  知秋 Microsoft:微软“变脸” , 2006 .

[64]  M. D. Cooper Towards a model of safety culture , 2000 .

[65]  Seth Flaxman,et al.  European Union Regulations on Algorithmic Decision-Making and a "Right to Explanation" , 2016, AI Mag..

[66]  Jonathan B. Wiener,et al.  Comparing precaution in the United States and Europe , 2002 .

[67]  A. Korolova,et al.  Discrimination through Optimization , 2019, Proc. ACM Hum. Comput. Interact..

[68]  S. Baum A Survey of Artificial General Intelligence Projects for Ethics, Risk, and Policy , 2017 .

[69]  Margot E. Kaminski,et al.  Binary Governance: Lessons from the GDPR's Approach to Algorithmic Accountability , 2019, SSRN Electronic Journal.

[70]  D. Vogel Trading Up: Consumer and Environmental Regulation in a Global Economy , 1997 .

[71]  Lav R. Varshney,et al.  CTRL: A Conditional Transformer Language Model for Controllable Generation , 2019, ArXiv.

[72]  Matthijs M. Maas,et al.  Should Artificial Intelligence Governance be Centralised?: Design Lessons from History , 2020, AIES.

[73]  Ram Shankar Siva Kumar,et al.  The Case for AI Insurance , 2020 .

[74]  Dylan LeValley Autonomous Vehicle Liability—Application of Common Carrier Liability , 2013 .

[75]  J. S. Legge,et al.  Public Opinion, Risk Assessment, and Biotechnology: Lessons from Attitudes toward Genetically Modified Foods in the European Union , 2010 .

[76]  Nathalie A. Smuha From a 'Race to AI' to a 'Race to AI Regulation' - Regulatory Competition for Artificial Intelligence , 2019, SSRN Electronic Journal.

[77]  W. Powell,et al.  THE IRON CAGE REVISITED: , 1983, The New Economic Sociology.

[78]  James Butcher,et al.  What is the State of Artificial Intelligence Governance Globally? , 2019, The RUSI Journal.

[79]  M. Porter,et al.  Strategy and society: the link between competitive advantage and corporate social responsibility. , 2006, Harvard business review.

[80]  Seth D. Baum,et al.  Countering Superintelligence Misinformation , 2018, Inf..

[81]  Cli McMahon,et al.  Machines Who Think : A Personal Inquiry into the History and Prospects of Artificial Intelligence , 2004 .

[82]  Emanuel Moss,et al.  Owning Ethics: Corporate Logics, Silicon Valley, and the Institutionalization of Ethics , 2019 .

[83]  Haydn Belfield,et al.  Activism by the AI Community: Analysing Recent Achievements and Future Prospects , 2020, AIES.

[84]  James Fox,et al.  Exploring AI Futures Through Role Play , 2019, AIES.

[85]  J. Wiener The Tragedy of the Uncommons: On the Politics of Apocalypse , 2016 .

[86]  Linda A.J. Senden,et al.  Soft Law, Self-Regulation and Co-Regulation in European Law: Where Do They Meet? , 2006 .