ETHICS & INNOVATION

With AI developing at an extraordinary rate, the need to strike the right balance between ethics and innovation - and to adhere to it consistently - has become impossible to ignore

- JP Singh

The biggest governance dilemma in AI is setting guidelines for the technology’s ethical use without unduly weakening the incentive to innovate.

So far, countries and regions have largely failed to strike any kind of balance, instead tipping the scales one way or the other while loftily proclaiming reverence for both.

The concept of responsible AI (RAI) exemplifies this idealistic rhetoric. The principles it espouses — from ensuring that algorithms are not based on faulty datasets to preventing privacy and human-rights violations — are undoubtedly worthy. Where RAI falls short is in showing how these ideals should be incorporated into AI governance, and how to balance regulation with incentives for continued innovation. Nonetheless, RAI has been embraced by many governments, which have incorporated relevant language into national AI policies. International organizations have also championed RAI-UNESCO’s Global AI Ethics and Governance Observatory is a leading example — with the goal of shaping international norms and national policy. But such top-down approaches contrast sharply with the deliberative, bottom-up decision-making that has proven most effective in addressing problems requiring collective action and coordination.

Meanwhile, corporations are touting their supposed commitment to RAI, often while resisting the regulations that would force them to implement its principles. Even universities have jumped on the RAI bandwagon, offering AI ethics courses in computer science departments. AI governance courses, however, are usually offered in other departments, so computer science students may not take them.