The Governance of AI
Tackling Four Magnitudes of Complexity
After An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations, i.e. the document we released on November 2018 the next step of the AI4’s Scientific Committee will concern the “Governance of AI”.
The Recommendations of our previous document and its 20 Action Points (AP) are the starting point of the work. Most of the issues on how to assess, to develop, to incentivise and to support a Good AI Society entail complex matters of governance, such as auditing mechanisms for AI systems (AP # 6), a new EU oversight agency responsible for the protection of public welfare (AP # 9), a process or mechanism of redress to remedy or compensate for wrongs, or grievances (AP # 6), etc.
1. AI4People Forum. At the heart of the second year will be the activity of the AI4People Forum, open to representatives of governments around the world, European institutions, civil society organisations, relevant media and leading businesses. Members will be invited to attend three meetings in Brussels:
►April 2019: Presentation of the 2019 Program.
►July 2019: Presentation of initial paper and contributions from Forum members.
►November 2019: AI4People Final Event: Presentation of the final results at the European Parliament.
2. Scientific Activity on: Governance of AI. The Governance of AI sets the level of abstraction, in order to properly tackle four magnitudes of complexity on (i) regulation; (ii) know-how; (iii) possible solutions; and, (iv) evaluation, that is, who, how, what, and why. More particularly, the intricacy regards:
(i) The interaction between different regulatory systems. In addition to the rules of national and international lawmakers, consider the role that the forces of the market, or of social norms, play in this context, e.g. trust. These regulatory systems can compete, and even clash with each other. Several approaches capture part of this complex interaction, for example, through models of risk regulation, and of risk governance. Next year (2019), before Election Day in May, the EU Commission’s documents on a new legal framework for AI and its ethical principles should be available. Also, but not only, in light of these documents, the aim is to flesh out what kind of governance is emerging, and we should opt for in the field of AI, before the new EU Parliament and Commission;
(ii) The interaction between different kinds of expertise. Matters of institutional design regard the ways in which economics and the law, technology and social norms interact. As shown by today’s debate on the weight that AI evidence should have in legal trials, problems concern different heuristics, and how we should govern them. As our previous recommendations on auditing mechanisms, or an oversight agency, illustrate, focus is not on ‘who’ takes decisions (previous magnitude of complexity), but rather on ‘how.’ The sets of challenges that are unique to AI renew this kind of problem in terms of governance;
(iii) Solutions. The ethical framework provided in our previous document insisted on the context-dependent issues brought about by AI. It is clear for example that the complex set of provisions regulating the production and use of AI for autonomous vehicles scarcely overlaps with that of AI appliances for smart houses, for finance, etc. The same holds true in terms of governance. The latter may require the adoption of ‘central authorities,’ such as a new EU oversight agency responsible for the protection of public welfare, but governance solutions will often depend on the specificity of the issues and AI domains we’re dealing with. Here, matters revolve around ‘what,’ rather than ‘who’ or ‘how';
(iv) Evaluations. The final magnitude of complexity regards the setting of standards. This stance partially overlaps with our first stance on how different regulatory systems interact, for we have legal standards, social standards, technical standards, etc. Attention is drawn here, however, to how such standards evolve, and new standards are required today. The question concerns ‘why,’ rather than ‘who,’ ‘how, ‘ or ‘what.’ The ethical framework for a good AI society has to be implemented through a good AI governance. Standards will play a major role in this accomplishment.