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A Century Long Commitment to Assessing Artificial Intelligence and Its Impact on Society1 Barbara J
A Century Long Commitment to Assessing Artificial Intelligence and Its Impact on Society1 Barbara J. Grosz, Harvard University, Inaugural Chair of the AI100 Standing Committee Peter Stone, University of Texas at Austin, Chair of the Inaugural AI100 Study Panel The Stanford One Hundred Year Study on Artificial Intelligence, a project that launched in December 2014, is designed to be a century-long periodic assessment of the field of Artificial Intelligence (AI) and its influences on people, their communities, and society. Colloquially referred to as "AI100", the project issued its first report in September 2016. A Standing Committee works with the Stanford Faculty Director of AI100 in overseeing the project and designing its activities. A little more than two years after the first report appeared, we reflect on the decisions made in shaping it, the process that produced it, its major conclusions, and reactions subsequent to its release. The inaugural AI100 report [4], which is titled “Artificial Intelligence and Life in 2030,” examines eight domains of human activity in which AI technologies are already starting to affect urban life. In scope, it encompasses domains with emerging products enabled by AI methods and ones raising concerns about technological impact generated by potential AI-enabled systems. The Study Panel members who authored the report and the AI100 Standing Committee, which is the body that directs the AI100 project, intend for it to act as a catalyst, spurring conversations on how we as a society might shape and share the potentially powerful technologies that AI could enable. In addition to influencing researchers and guiding decisions in industry and governments, the report aims to provide the general public with a scientifically and technologically accurate portrayal of the current state of AI and its potential. -
ARCHITECTS of INTELLIGENCE for Xiaoxiao, Elaine, Colin, and Tristan ARCHITECTS of INTELLIGENCE
MARTIN FORD ARCHITECTS OF INTELLIGENCE For Xiaoxiao, Elaine, Colin, and Tristan ARCHITECTS OF INTELLIGENCE THE TRUTH ABOUT AI FROM THE PEOPLE BUILDING IT MARTIN FORD ARCHITECTS OF INTELLIGENCE Copyright © 2018 Packt Publishing All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book. Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information. Acquisition Editors: Ben Renow-Clarke Project Editor: Radhika Atitkar Content Development Editor: Alex Sorrentino Proofreader: Safis Editing Presentation Designer: Sandip Tadge Cover Designer: Clare Bowyer Production Editor: Amit Ramadas Marketing Manager: Rajveer Samra Editorial Director: Dominic Shakeshaft First published: November 2018 Production reference: 2201118 Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK ISBN 978-1-78913-151-2 www.packt.com Contents Introduction ........................................................................ 1 A Brief Introduction to the Vocabulary of Artificial Intelligence .......10 How AI Systems Learn ........................................................11 Yoshua Bengio .....................................................................17 Stuart J. -
“Reflections on the Status and Future of Artificial Intelligence”
STATEMENT OF: ERIC HORVITZ TECHNICAL FELLOW AND DIRECTOR MICROSOFT RESEARCH—REDMOND LAB MICROSOFT CORPORATION BEFORE THE COMMITTEE ON COMMERCE SUBCOMMITTEE ON SPACE, SCIENCE, AND COMPETITIVENESS UNITED STATES SENATE HEARING ON THE DAWN OF ARTIFICIAL INTELLIGENCE NOVEMBER 30, 2016 “Reflections on the Status and Future of Artificial Intelligence” NOVEMBER 30, 2016 1 Chairman Cruz, Ranking Member Peters, and Members of the Subcommittee, my name is Eric Horvitz, and I am a Technical Fellow and Director of Microsoft’s Research Lab in Redmond, Washington. While I am also serving as Co-Chair of a new organization, the Partnership on Artificial Intelligence, I am speaking today in my role at Microsoft. We appreciate being asked to testify about AI and are committed to working collaboratively with you and other policymakers so that the potential of AI to benefit our country, and to people and society more broadly can be fully realized. With my testimony, I will first offer a historical perspective of AI, a definition of AI and discuss the inflection point the discipline is currently facing. Second, I will highlight key opportunities using examples in the healthcare and transportation industries. Third, I will identify the important research direction many are taking with AI. Next, I will attempt to identify some of the challenges related to AI and offer my thoughts on how best to address them. Finally, I will offer several recommendations. What is Artificial Intelligence? Artificial intelligence (AI) refers to a set of computer science disciplines aimed at the scientific understanding of the mechanisms underlying thought and intelligent behavior and the embodiment of these principles in machines that can deliver value to people and society. -
Keeping AI Legal
Vanderbilt Journal of Entertainment & Technology Law Volume 19 Issue 1 Issue 1 - Fall 2016 Article 5 2016 Keeping AI Legal Amitai Etzioni Oren Etzioni Follow this and additional works at: https://scholarship.law.vanderbilt.edu/jetlaw Part of the Computer Law Commons, and the Science and Technology Law Commons Recommended Citation Amitai Etzioni and Oren Etzioni, Keeping AI Legal, 19 Vanderbilt Journal of Entertainment and Technology Law 133 (2020) Available at: https://scholarship.law.vanderbilt.edu/jetlaw/vol19/iss1/5 This Article is brought to you for free and open access by Scholarship@Vanderbilt Law. It has been accepted for inclusion in Vanderbilt Journal of Entertainment & Technology Law by an authorized editor of Scholarship@Vanderbilt Law. For more information, please contact [email protected]. Keeping Al Legal Amitai Etzioni* and Oren Etzioni** ABSTRACT AI programs make numerous decisions on their own, lack transparency, and may change frequently. Hence, unassisted human agents, such as auditors, accountants, inspectors, and police, cannot ensure that Al-guided instruments will abide by the law. This Article suggests that human agents need the assistance of AI oversight programs that analyze and oversee operational AI programs. This Article asks whether operationalAIprograms should be programmed to enable human users to override them; without that, such a move would undermine the legal order. This Article also points out that Al operational programs provide high surveillance capacities and, therefore, are essential for protecting individual rights in the cyber age. This Article closes by discussing the argument that Al-guided instruments, like robots, lead to endangering much more than the legal order-that they may turn on their makers, or even destroy humanity. -
AI Ignition Ignite Your AI Curiosity with Oren Etzioni AI for the Common Good
AI Ignition Ignite your AI curiosity with Oren Etzioni AI for the common good From Deloitte’s AI Institute, this is AI Ignition—a monthly chat about the human side of artificial intelligence with your host, Beena Ammanath. We will take a deep dive into the past, present, and future of AI, machine learning, neural networks, and other cutting-edge technologies. Here is your host, Beena. Beena Ammanath (Beena): Hello, my name is Beena Ammanath. I am the executive director of the Deloitte AI Institute, and today on AI Ignition we have Oren Etzioni, a professor, an entrepreneur, and the CEO of Allen Institute for AI. Oren has helped pioneer meta search, online comparison shopping, machine reading, and open information extraction. He was also named Seattle’s Geek of the Year in 2013. Welcome to the show, Oren. I am so excited to have you on our AI Ignition show today. How are you doing? Oren Etzioni (Oren): I am doing as well as anyone can be doing in these times of COVID and counting down the days till I get a vaccine. Beena: Yeah, and how have you been keeping yourself busy during the pandemic? Oren: Well, we are fortunate that AI is basically software with a little sideline into robotics, and so despite working from home, we have been able to stay productive and engaged. It’s just a little bit less fun because one of the things I like to say about AI is that it’s still 99% human intelligence, and so obviously the human interactions are stilted. -
Oren Etzioni, Phd: CEO of Allen Institute for AI
Behind the Tech Kevin Scott Podcast EP-26: Oren Etzioni, PhD: CEO of Allen Institute for AI [MUSIC] OREN ETZIONI: Whose responsibility is it? The responsibility and liability has to ultimately rest with a person. You can’t say, “Hey, you know, look, my car ran you over, it’s an AI car, I don’t know what it did, it’s not my fault, right?” You as the driver or maybe it’s the manufacturer if there’s some malfunction, but people have to be responsible for the behavior of the machines. [MUSIC] KEVIN SCOTT: Hi, everyone. Welcome to Behind the Tech. I'm your host, Kevin Scott, Chief Technology Officer for Microsoft. In this podcast, we're going to get behind the tech. We'll talk with some of the people who have made our modern tech world possible and understand what motivated them to create what they did. So, join me to maybe learn a little bit about the history of computing and get a few behind- the-scenes insights into what's happening today. Stick around. [MUSIC] CHRISTINA WARREN: Hello, and welcome to Behind the Tech. I’m Christina Warren, senior cloud advocate at Microsoft. KEVIN SCOTT: And I’m Kevin Scott. CHRISTINA WARREN: Today on the show, our guest is Oren Etzioni. Oren is a professor, entrepreneur, and is the chief executive officer for the Allen Institute for AI. So, Kevin, I’m guessing that you guys have already crossed paths in your professional pursuits. KEVIN SCOTT: Yeah, I’ve been lucky enough to know Oren for the past several years. -
Curriculum Vitae
6/14/21 CURRICULUM VITAE Edward Hance Shortliffe, MD, PhD, MACP, FACMI, FIAHSI [work] Chair Emeritus and Adjunct Professor, Department of Biomedical Informatics Vagelos College of Physicians and Surgeons, Columbia University in the City of New York [email protected] – https://www.dbmi.columbia.edu/people/edward-shortliffe/ Adjunct Professor of Biomedical Informatics College of Health Solutions Arizona State University, Phoenix, AZ [email protected] – https://isearch.asu.edu/profile/1098580 Adjunct Professor, Department of Healthcare Policy and Research (Health Informatics) Weill Cornell Medical College, New York, NY http://hpr.weill.cornell.edu/divisions/health_informatics/ [home] 272 W 107th St #5B, New York, NY 10025-7833 Phone: 212-666-8440 — Mobile: 917-640-0933 [email protected] – http://www.shortliffe.net Born: Edmonton, Alberta, Canada Date of birth: 28 August 1947 Citizenship: U.S.A. (naturalized - 1962) Spouse: Vimla L. Patel, PhD Education From To School/Institution Major Subject, Degree, and Date 9/62 6/65 The Loomis School, Windsor, CT. High School 9/65 7/66 Gresham's School, Holt, Norfolk, U.K. Foreign Exchange Student 9/66 6/70 Harvard College, Cambridge, MA. Applied Math and Computer Science, A.B., June 1970 9/70 1/75 Stanford University, Stanford, CA PhD, Medical Information Sciences, January 1975 9/70 6/76 Stanford University School of Medicine MD, June 1976. 7/76 6/77 Massachusetts General Hospital, Boston, MA Internship in Internal Medicine 7/77 6/79 Stanford University Hospital, Stanford, CA Residency in Internal Medicine Honors Graduation Magna Cum Laude, Harvard College, June 1970 Medical Scientist Training Program (MSTP), NIH-funded Stanford Traineeship, September 1971 - June 1976 Grace Murray Hopper Award (Distinguished computer scientist under age 30), Association for Computing Machinery, October 1976 Research Career Development Award, National Library of Medicine, July 1979—June 1984 Henry J. -
The Elephant in the Room: Getting Value from Big Data Serge Abiteboul, Luna Dong, Oren Etzioni, Divesh Srivastava, Gerhard Weikum, Julia Stoyanovich, Fabian Suchanek
The elephant in the room: getting value from Big Data Serge Abiteboul, Luna Dong, Oren Etzioni, Divesh Srivastava, Gerhard Weikum, Julia Stoyanovich, Fabian Suchanek To cite this version: Serge Abiteboul, Luna Dong, Oren Etzioni, Divesh Srivastava, Gerhard Weikum, et al.. The elephant in the room: getting value from Big Data. Workshop on Web and Databases (WebDB), May 2015, Melbourne, France. 10.1145/2767109.2770014. hal-01699868 HAL Id: hal-01699868 https://hal-imt.archives-ouvertes.fr/hal-01699868 Submitted on 2 Feb 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. The elephant in the room: getting value from Big Data Serge Abiteboul (INRIA Saclay & ENS Cachan, France), Luna Dong (Google Inc., USA), Oren Etzioni (Allen Institute for Artificial Intelligence, USA), Divesh Srivastava (AT&T Labs-Research, USA), Gerhard Weikum (Max Planck Institute for Informatics, Germany), Julia Stoyanovich (Drexel University, USA) and Fabian M. Suchanek (Télécom ParisTech, France) 1. INTRODUCTION SIGMOD Innovation Award in 1998, the EADS Award from Big Data, and its 4 Vs { volume, velocity, variety, and the French Academy of sciences in 2007; the Milner Award veracity { have been at the forefront of societal, scientific from the Royal Society in 2013; and a European Research and engineering discourse. -
Machine Learning, Reasoning, and Intelligence in Daily Life: Directions and Challenges
Machine Learning, Reasoning, and Intelligence in Daily Life: Directions and Challenges Eric Horvitz Microsoft Research Redmond, Washington USA 98052 [email protected] Abstract An example of an implicit integration of ambient learning Technical developments and trends are providing a and reasoning is the effort by our team to create a probabil- fertile substrate for creating and integrating ma- istic action prediction and prefetching subsystem that is em- chine learning and reasoning into multiple applica- bedded deeply in the kernel of Microsoft’s Windows Vista tions and services. I will review several illustrative operating system. The predictive component, operating research efforts on our team, and focus on chal- within a component in the Vista operating system called lenges, opportunities, and directions with the Superfetch, learns by watching sequences of application streaming of machine intelligence into daily life. launches over time to predict a computer user’s application launches. These predictions, coupled with a utility model 1 Reflections on Trends and Directions that captures preferences about the cost of waiting, are used Over the last decade, technical and infrastructural develop- in an ongoing optimization to prefetch unlaunched applica- ments have come together to create a nurturing environment tions into memory ahead of their manual launching. The for developing and fielding applications of machine learning implicit service seeks to minimize the average wait for ap- and reasoning—and for harnessing automated intelligence -
The Dawn of Artificial Intelligence Hearing
S. HRG. 114–562 THE DAWN OF ARTIFICIAL INTELLIGENCE HEARING BEFORE THE SUBCOMMITTEE ON SPACE, SCIENCE, AND COMPETITIVENESS OF THE COMMITTEE ON COMMERCE, SCIENCE, AND TRANSPORTATION UNITED STATES SENATE ONE HUNDRED FOURTEENTH CONGRESS SECOND SESSION NOVEMBER 30, 2016 Printed for the use of the Committee on Commerce, Science, and Transportation ( U.S. GOVERNMENT PUBLISHING OFFICE 24–175 PDF WASHINGTON : 2017 For sale by the Superintendent of Documents, U.S. Government Publishing Office Internet: bookstore.gpo.gov Phone: toll free (866) 512–1800; DC area (202) 512–1800 Fax: (202) 512–2104 Mail: Stop IDCC, Washington, DC 20402–0001 VerDate Nov 24 2008 13:07 Feb 15, 2017 Jkt 075679 PO 00000 Frm 00001 Fmt 5011 Sfmt 5011 S:\GPO\DOCS\24175.TXT JACKIE SENATE COMMITTEE ON COMMERCE, SCIENCE, AND TRANSPORTATION ONE HUNDRED FOURTEENTH CONGRESS SECOND SESSION JOHN THUNE, South Dakota, Chairman ROGER F. WICKER, Mississippi BILL NELSON, Florida, Ranking ROY BLUNT, Missouri MARIA CANTWELL, Washington MARCO RUBIO, Florida CLAIRE MCCASKILL, Missouri KELLY AYOTTE, New Hampshire AMY KLOBUCHAR, Minnesota TED CRUZ, Texas RICHARD BLUMENTHAL, Connecticut DEB FISCHER, Nebraska BRIAN SCHATZ, Hawaii JERRY MORAN, Kansas EDWARD MARKEY, Massachusetts DAN SULLIVAN, Alaska CORY BOOKER, New Jersey RON JOHNSON, Wisconsin TOM UDALL, New Mexico DEAN HELLER, Nevada JOE MANCHIN III, West Virginia CORY GARDNER, Colorado GARY PETERS, Michigan STEVE DAINES, Montana NICK ROSSI, Staff Director ADRIAN ARNAKIS, Deputy Staff Director JASON VAN BEEK, General Counsel KIM LIPSKY, Democratic -
Report on the Future of AI Workshop
Report on The Future of AI Workshop Date: December 13 - 15, 2002 Venue: Amagi Homestead, IBM Japan Edited by the Future of AI Workshop Steering Committee Edward A. Feigenbaum Setsuo Ohsuga Hiroshi Motoda Koji Sasaki Compiled by AdIn Research, Inc. August 31, 2003 Please direct general inquiries to AdIn Research, Inc. 3-6 Kioicho, Chiyoda-ku, Tokyo 102-0094, Japan phone: +81-3-3288-7311 fax: +81-3-3288-7568 url: http://www.adin.co.jp/ Table of Contents Prospectus ………………………………………………………………………………………………… 4 Outline …………………………………………………………………………………………………… 5 Co-sponsors and Supporting Organizations ………………………………………………………………… 6 Schedule ……………………………………………………………………………………………………. 9 List of Panelists …………………………………………………………………………………………….. 10 Contact Information …………………………………….…………………………………………………... 12 Keynote Speech Edward A. Feigenbaum ………………………………………………………………... 17 Sessions 1. FOUNDATIONS OF AI 1. Hiroki Arimura ………………………………………………………………………… 27 2. Stuart Russell …………………………………………………………………………... 30 3. Naonori Ueda …………………………………………………………………………... 34 4. Akito Sakurai …………………………………………………………………………... 38 2. DISCOVERY 1. Einoshin Suzuki ……………………………………………………………………...… 45 2. Satoru Miyano …………………………………………………………………...…….. 49 3. Thomas Dietterich …………………………………………………………...………… 55 4. Hiroshi Motoda ………………………………………………………...……………… 62 3. HCL 1. Yasuyuki Sumi …………………………………………………...……………………. 68 2. Kumiyo Nakakoji ………………………………………………...……………………. 72 3. Toru Ishida ………………………………………………………..…………………… 77 4. Eric Horvitz ………………………………………………………..…………………... 83 4. AI SYSTEMS 1. Ron -
TR10: Modeling Surprise Technologyreview.Com NSORS
NSORS Modeling Surprise WHO Eric Horvitz, Microsoft Research Combining massive quantities of data, insights into human psychology, and machine learning can help humans manage DEFINITION surprising events, says Eric Horvitz. Surprise modeling combines data mining and machine learning to By M. Mitchell Waldrop help people do a better job of anticipating and coping with Much of modern life depends on forecasts: where the next unusual events. hurricane will make landfall, how the stock market will react IMPACT to falling home prices, who will win the next primary. While Although research in the field is existing computer models predict many things fairly preliminary, surprise modeling accurately, surprises still crop up, and we probably can’t could aid decision makers in a wide eliminate them. But Eric Horvitz, head of the Adaptive range of domains, such as traffic management, preventive medicine, Systems and Interaction group at Microsoft Research, thinks military planning, politics, business, we can at least minimize them, using a technique he calls and finance. “surprise modeling.” CONTEXT A prototype that alerts users to Horvitz stresses that surprise modeling is not about building a surprises in Seattle traffic patterns technological crystal ball to predict what the stock market will has proved effective in field tests do tomorrow, or what al-Qaeda might do next month. But, he involving thousands of Microsoft says, “We think we can apply these methodologies to look at employees. Studies investigating broader applications are now under the kinds of things that have surprised us in the past and then way. model the kinds of things that may surprise us in the future.” The result could be enormously useful for decision makers in fields that range from health care to military strategy, politics to financial markets.