The challenges of industry self-regulation of AI in emerging economies: Implications of the case of Russia for public policy and institutional development

The widespread utilization of AI technologies urges governments worldwide to design governance structures for it. Industry self-regulation is one of the approaches most often suggested for this task, as it allows flexibility in balancing innovation and safety. This book chapter discusses how self-regulatory approaches popular for the governance of AI can potentially be problematic for emerging economies. The findings are derived from the fieldwork conducted in Russia in 2021-2022. The key challenges include the need for more technical expertise within the government, the lack of civil liberties, the interwovenness between the public and the private sector, the lack of motivation for ethical development, and protectionism over the local IT industry. Some initial remedies for the shortcomings of the industry self-regulation for AI in emerging economies can be found in how governments mitigate the negative effects of regulatory capture. These include promoting greater balance and diversity in the competition among different stakeholders, reforming the institutional context within which regulators operate, and opening up the regulatory process to various external checks and balances.