【正文】 about the implications of AI advances for defense and warfare, including potentially destabilizing developments and deployments. The report is designed to address four intended audiences. For the general public, it aims to provide an accessible, scientifically and technologically accurate portrayal of the current state of AI and its potential. For industry, the report describes relevant technologies and legal and ethical challenges, and may help guide resource allocation. The report is also directed to local, national, and international governments to help them better plan for AI in governance. Finally, the report can help AI researchers, as well as their institutions and funders, to set priorities and consider the ethical and legal issues raised by AI research and its applications. Given the unique nature of the One Hundred Year Study on AI, we expect that future generations of Standing Committees and Study Panels, as well as research scientists, policy experts, leaders in the private and public sectors, and the general public, will reflect on this assessment as they make new assessments of AI‘s future. We hope that this first effort in the series stretching out before us will be useful for both its failures and successes in accurately predicting the trajectory and influences of AI. The Standing Committee is grateful to the members of the Study Panel for investing their expertise, perspectives, and significant time to the creation of this inaugural report. We especially thank Professor Peter Stone for agreeing to serve as chair of the study and for his wise, skillful, and dedicated leadership of the panel, its discussions, and creation of the report. Standing Committee of the One Hundred Year Study of Artificial Intelligence Barbara J. Grosz, Chair Russ Altman Eric Horvitz Alan Mackwort h Tom Mitchell Deirdre Mulligan Yoav Shoham STUDY PANEL Peter Stone, University of Texas at Austin, Chair Rodney Brooks, Rethink Robotics Erik Brynjolfsson, Massachussets Institute of Technology Ryan Calo, University of Washington Oren Etzioni, Allen Institute for AI Greg Hager, Johns Hopkins University Julia Hirschberg, Columbia University Shivaram Kalyanakrishnan, Indian Institute of Technology Bombay Ece Kamar, Microsoft Research Sarit Kraus, Bar Ilan University Kevin LeytonBrown, University of British Columbia David Parkes, Harvard University William Press, University of Texas at Austin AnnaLee (Anno) Saxenian, University of California, Berkeley Julie Shah, Massachussets Institute of Technology Milind Tambe, University of Southern California Astro Teller, X Acknowledgments: The members of the Study Panel gratefully acknowledge the support of and valuable input from the Standing Committee, especially the chair, Barbara Grosz, who handled with supreme grace the unenviable role of mediating between two large, very passionate mittees. We also thank Kerry Tremain for his tireless and insightful input on the written product during the extensive editing and polishing process, which unquestionably strengthened the report considerably. 169。 20xx by Stanford University. Artificial Intelligence and Life in 2030 is made available under a Creative Commons AttributionNoDerivatives License (International): /licenses/bynd/3 Substantial increases in the future uses of AI applications, including more selfdriving cars, healthcare diagnostics and targeted treatment, and physical assistance for elder care can be expected. 4 EXECUTIVE SUMMARY Artificial Intelligence (AI) is a science and a set of putational technologies that are inspired by—but typically operate quite differently from—the ways people use their nervous systems and bodies to sense, learn, reason, and take action. While the rate of progress in AI has been patchy and unpredictable, there have been significant advances since the field‘s inception sixty years ago. Once a mostly academic area of study, twentyfirst century AI enables a constellation of mainstream technologies that are having a substantial impact on everyday lives. Computer vision and AI planning, for example, drive the video games that are now a bigger entertainment industry than Hollywood. Deep learning, a form of machine learning based on layered representations of variables referred to as neural works, has made speechunderstanding practical on our phones and in our kitchens, and its algorithms can be applied widely to an array of applications that rely on pattern recognition. Natural Language Processing (NLP) and knowledge representation and reasoning have enabled a machine to beat the Jeopardy champion and are bringing new power to Web searches. While impressive, these technologies are highly tailored to particular tasks. Each application typically requires years of specialized research and careful, unique construction. In similarly targeted applications, substantial increases in the future uses of AI technologies, including more selfdriving cars, healthcare diagnostics and targeted treatments, and physical assistance for elder care can be expected. AI and robotics will also be applied across the globe in industries struggling to attract younger workers, such as agriculture, food processing, fulfillment centers, and factories. They will facilitate delivery of online purchases through flying drones, selfdriving trucks, or robots that can get up the stairs to the front door. This report is the first in a series to be issued at regular intervals as a part of the One Hundred Year Study on Artificial Intelligence (AI100). Starting from a charge given by the AI100 Standing Committee to co