Introduction to the AI Policy Forum
The AI Policy Forum (AIPF) is an initiative of the MIT Schwarzman College of Computing that aims to move the global conversation about the impact of artificial intelligence from principles to practical policy implementation. Formed in late 2020, AIPF brings together leaders in government, business, and academia to develop approaches to address the societal challenges posed by the rapid advances and increasing applicability of AI.
The Co-Chairs of the AI Policy Forum
The co-chairs of the AI Policy Forum are Aleksander Madry, the Cadence Design Systems Professor; Asu Ozdaglar, deputy dean of academics for the MIT Schwarzman College of Computing and head of the Department of Electrical Engineering and Computer Science; and Luis Videgaray, senior lecturer at MIT Sloan School of Management and director of MIT AI Policy for the World Project. They discuss some of the key issues facing the AI policy landscape today and the challenges surrounding the deployment of AI.
Ongoing Work of the AI Policy Forum
There is no shortage of discussion about AI at different venues, but conversations are often high-level, focused on questions of ethics and principles, or on policy problems alone. The approach the AIPF takes to its work is to target specific questions with actionable policy solutions and engage with the stakeholders working directly in these areas. They work “behind the scenes” with smaller focus groups to tackle these challenges and aim to bring visibility to some potential solutions alongside the players working directly on them through larger gatherings.
Trustworthy AI Development and Deployment
AI impacts many sectors, which makes us naturally worry about its trustworthiness. The most important thing to understand regarding deploying trustworthy AI is that AI technology isn’t some natural, preordained phenomenon. It is something built by people. People who are making certain design decisions. We thus need to advance research that can guide these decisions as well as provide more desirable solutions. But we also need to be deliberate and think carefully about the incentives that drive these decisions.
AI in the Financial Sector
The financial sector is seeing a number of trends that present policy challenges at the intersection of AI systems. For one, there is the issue of explainability. By law (in the U.S. and in many other countries), lenders need to provide explanations to customers when they take actions deleterious in whatever way, like denial of a loan, to a customer’s interest. However, as financial services increasingly rely on automated systems and machine learning models, the capacity of banks to unpack the “black box” of machine learning to provide that level of mandated explanation becomes tenuous.
Social Media and Public Good
Social media is one of the most controversial sectors of the economy, resulting in many societal shifts and disruptions around the world. The role of social media in society is of growing concern to many, but the nature of these concerns can vary quite a bit — with some seeing social media as not doing enough to prevent, for example, misinformation and extremism, and others seeing it as unduly silencing certain viewpoints. This lack of unified view on what the problem is impacts the capacity to enact any change.
Conclusion
In conclusion, the AI Policy Forum is working to address the societal challenges posed by the rapid advances and increasing applicability of AI. The co-chairs of the AI Policy Forum, Aleksander Madry, Asu Ozdaglar, and Luis Videgaray, are working together to develop approaches to ensure that AI is developed and deployed in a trustworthy and responsible manner. They are focusing on specific questions with actionable policy solutions and engaging with stakeholders to tackle the challenges surrounding AI deployment. By working together, we can ensure that AI is a force for public good and not public harm.
