As artificial intelligence reshapes industries, economies, and societies, global leaders are grappling with the challenge of ensuring its ethical and responsible use.
The recent AI Summit, co-chaired by Indian Prime Minister Narendra Modi and French President Emmanuel Macron, underscores the urgency of establishing governance frameworks that balance innovation with safeguards against bias and inequality.
In this article, Anjana Susarla shares her expert insight exploring global potential of AI in shaping policymaking and international cooperation would be highly appreciated. Prof Susarla holds the Omura-Saxena Professorship in Responsible AI at the Broad College of Business. She earned an undergraduate degree in Mechanical Engineering from the Indian Institute of Technology, Chennai; a graduate degree in Business Administration from the Indian Institute of Management, Calcutta; and Ph.D. in Information Systems from the University of Texas at Austin.
Here's what she has to say-
With Prime Minister Modi co-chairing the AI Summit in Paris, how do you think India's role in AI development and policy will impact global discussions on AI governance?
India can play a great role in shaping international consensus around the values embodied in AI models. NITI Aayog, the public policy think tank of the government of India has taken a leadership role in unveiling principles of responsible AI that specify the values and boundaries of automated systems, including a governance model assigning responsibilities and accountabilities.
In your opinion, what are the key ethical considerations that policymakers must address as AI technologies continue to evolve? How can international cooperation help establish these ethical guidelines?
Key ethical considerations should be that AI is transparent, responsible, ensures safety and privacy. Policymakers need to ensure that use and design of AI that is fair, transparent, explainable, human-centric, and in a manner that safeguards privacy and security. International cooperation can ensure that use of algorithms must be accompanied by consumer protection guidelines including the guidance and choices to be provided by consumers. Businesses deploying these technologies and developers of AI must likewise consider the role played by explainability, risk management, managerial agency, and human control in the implementation of these technologies.
What do you think are the main obstacles to international cooperation on AI, and how can we overcome them to ensure AI's benefits are shared globally?
One of the challenges is that different countries and regions have adopted their own set of standards. In the past year, there have been a slew of proposals both in Europe and in the United States on regulation of AI. China is unveiling AI regulations as well. In the US, regulatory agencies such as the Federal Trade Commission (FTC) has indicated that they will be paying attention to the use of automated decision making enabled by AI. There are proposals being debated to regulate algorithmic harms and bills highlighting data privacy and protection across different US states. Given this patchwork of AI legislation, we need an overarching principle or set of guidelines that can be agreed upon.
What excites you most about the future of AI, and how do you believe the next decade will shape the relationship between technology and society?
Technological innovations enabled by AI could expand consumer welfare and well-being and could result in intangible investments such as new business models, new businesses and services that would not exist without AI. AI technologies offer great promise in improving healthcare, enabling new modes of drug discovery, streamlining the modes of production and distribution etc. However, in order for that vision to be realised, we also need to ensure that the development of AI takes place in an equitable manner and an understanding of how AI impacts consumer, markets and societal institutions. We need algorithmic accountability, algorithmic literacy, and algorithmic regulation to ensure equitable outcomes without sacrificing the productivity, profitability, and consumer welfare gains from AI.
