McDonough School of Business
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Office Hours: Exploring the Intersection of AI and Public Policy

In the ever-evolving landscape of the digital age, the intersection of artificial intelligence (AI) and policy has been a focal point for researchers, policymakers, and industry leaders. At the Center for Business and Public Policy (CBPP) at Georgetown University’s McDonough School of Business, Timothy DeStefano, Associate Research Professor, leverages his expertise in digital technology, AI, industrial robotics, and firm productivity to shape policies conducive to AI-driven innovation while addressing emerging challenges, such as data privacy. 

Before joining Georgetown, DeStefano spent three years at Harvard University’s Laboratory for Innovation Science, where he led a team in pioneering research on data science and AI. DeStefano now uses his expertise with the CBPP to unravel the complexities of AI’s impact on firm performance and policy. 

Here, he shares insights into the center’s AI in Action Series and the impact of AI usage across industries.

What are the key takeaways from the AI and Policy conference earlier this year?

The primary objective of CBPP’s AI and policy conferences is to foster dialogue among key stakeholders shaping the future of AI. These stakeholders include academic experts, policy makers from intergovernmental and governmental organizations, and businesses at the frontier of AI development. We aim to bridge the gap between these groups by facilitating knowledge sharing and collaboration. The first conference focused on gauging our understanding of AI policy and measurement, which revealed  significant gaps in our knowledge. Additionally, we examined how AI is actually being utilized, bringing together researchers and industry professionals active in developing AI technologies.

Timothy DeStefano is an Associate Professor of Research at the Georgetown University McDonough School of Business

Timothy DeStefano, Associate Research Professor at Georgetown McDonough

Stay tuned for our next AI in Action Conference, which will take place in September 2024.

How does your research within the AI space relate to these key stakeholders?

My research journey began with an exploration of the digital economy paradigm during my tenure at the Organization for Economic Cooperation and Development. I discovered a significant shift towards  cloud computing services, which revolutionized access to new digital technology. Cloud computing drastically reduced the cost of data storage and processing, laying the foundation for AI advancements. However, existing policy frameworks predominantly incentivize physical investments, hindering cloud computing, big data and AI adoption. My research underscores the need for updated policies aligned with the evolving digital landscape.

How might your research impact further studies and conversations in the AI and policy realm?

My research aims to spark conversations about the adequacy of current policies in fostering technology adoption. Traditional policies designed for brick-and-mortar businesses may hinder the adoption of AI-driven technologies. By initiating discussions and reevaluating existing policies, we can pave the way for more effective strategies conducive to AI adoption and innovation.

Where do you envision these conversations headed in the future, particularly in terms of the stakeholders involved?

Moving forward, we aspire to expand our engagement with policymakers through events such as Georgetown on the Hill. By convening experts across academia, industry, and policy spheres, we aim to influence policy discussions and facilitate the development of informed, forward-thinking policies.

What are some areas of opportunity within the AI and policy space that warrant further exploration?

One notable opportunity lies in enhancing the understanding of AI’s true prevalence and impact. Contrary to common perceptions, only a small fraction of businesses extensively utilize AI technologies. Also, there’s a misconception that AI represents a radical departure from existing technologies. In reality, much of AI’s functionality involves predictive analytics, replacing rather than revolutionizing existing tools. Addressing these misconceptions and focusing on better measurement and privacy policies are key areas to explore.

Is data privacy a prominent topic of discussion in AI conferences?

While data privacy garners more attention in regions like Europe, it’s less prominent in the United States. However, given AI’s reliance on vast amounts of data, privacy concerns are integral to the conversation. Policy discussions should prioritize safeguarding privacy while facilitating AI innovation and adoption.

Center for Business and Public Policy