Interactions Between Artificial Intelligence and Digital Public Infrastructure: Concepts, Benefits, and Challenges
Sarosh Nagar, David Eaves

TL;DR
This paper explores how AI and digital public infrastructure can mutually enhance public value, discussing opportunities, challenges, empirical integration examples, and policy implications for their interaction.
Contribution
It provides a comprehensive analysis of the mutual benefits and challenges of AI and DPI, including empirical evidence and policy recommendations.
Findings
AI can enhance DPI functions like language translation and personalized services.
DPI can improve AI training data quality and quantity.
Challenges include high inference costs, interoperability, bias, and privacy concerns.
Abstract
Artificial intelligence (AI) and digital public infrastructure (DPI) are two technological developments that have taken center stage in global policy discourse. Yet, to date, there has been relatively little discussion about how AI and DPI can mutually enhance the public value provided by each other. Therefore, in this paper, we describe both the opportunities and challenges under which AI and DPI can interact for mutual benefit. First, we define both AI and DPI to provide clarity and help policymakers distinguish between these two technological developments. Second, we provide empirical evidence for how AI, a general-purpose technology, can integrate into many DPI systems, aiding DPI function in use cases like language localization via machine translation (MT), personalized service delivery via recommender systems, and more. Third, we catalog how DPI can act as a foundation for…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsLegal and Policy Issues · Smart Cities and Technologies
