United States–Japan Research Exchange on Artificial Intelligence

Proceedings from a Pair of Conferences on the Impact of Artificial Intelligence on Work, Health, and Data Privacy and on Disaster Prediction, Resilience, and Recovery

by Scott W. Harold, Greg Brunelle, Ritika Chaturvedi, Jeffrey W. Hornung, Shunichi Koshimura, Osonde A. Osoba, Chizuru Suga

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Artificial intelligence (AI) and machine learning (ML — hereafter AI/ML) are being applied widely across the globe, affecting how individuals work, pursue health, and protect their communities. These changes have implications for society, the economy, and data science. The experiences of the United States and Japan, two of the world's wealthiest and most technologically advanced liberal democracies, represent important leading indicators of how AI/ML affect human society now and will continue to do so. At least as important, U.S. and Japanese experiences also carry lessons for each other about how the two sides of the Pacific might think about the policy impacts that AI/ML technologies can have and what policies might be necessary to effectively and safely employ learning algorithms.

Given the importance of understanding the implications of AI/ML, the RAND Corporation convened a pair of public conferences that brought together leading U.S. and Japanese experts on work, health, and data security (Conference I), and on international affairs, disaster response, and disaster modeling (Conference II) to exchange views on some of the most important questions in the application of AI/ML technologies to contemporary policy issues. This report captures insights from the two conferences, recounts some of the exchanges among the participants at those sessions, and is built around the papers that the conference presenters submitted after the conferences concluded. The views articulated and expressed, including those about any technology or commercial product, are those of the participants and should not be construed as an endorsement by RAND or its research sponsors.

Table of Contents

  • Chapter One

    Introduction

  • Chapter Two

    AI and Labor Automation: A Cross-Cultural Assessment

  • Chapter Three

    Artificial Intelligence, Big Data, and Precision Medicine

  • Chapter Four

    Artificial Intelligence and the Problem of Data Governance: Building Trust in Data Flows for the Benefit of Society

  • Chapter Five

    Building Resilience: AI/ML Technologies and Natural Disaster Risk Assessment

  • Chapter Six

    Natural Disasters in the United States and Japan: Where Could AI Be Most Helpful?

  • Chapter Seven

    How AI-Enabled Modeling and Simulation Can Improve Coastal Communities' Preparation, Defense, and Recovery from Disaster: Real-Time Tsunami Inundation Forecasting

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This effort was sponsored by the Government of Japan and conducted in the Community Health and Environmental Policy Program within RAND Social and Economic Well-Being.

This report is part of the RAND Corporation conference proceeding series. RAND conference proceedings present a collection of papers delivered at a conference or a summary of the conference.

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