future, an ongoing blog to augment the periodic AI100 studies to be produced by future study panels. The AI Index follows various facets of AI, including those related to volume of activity, technological progress, and societal impact, as determined by a broad advisory panel with advice from the AI100 standing committee. As with the study panel reports, the AI Index aims to provide information on the status of AI that is useful for those both outside the field and those engaged in developing AI technologies, as well as those actively involved in AI research and applications, policymakers and business executives, and the general public. This nascent effort issued its first report in December 2017.

The AI100 project (https://ai100. stanford.edu/) welcomes advice as it plans its next report, as does the AI Index ( http://aiindex.org/). We look forward to following, and continuing to help shape, the AI100 trajectory over the coming years.

 

References

1. Angwin, J. et al. Machine bias: There’s software used across the country to predict future criminals. And it’s biased against blacks. ProPublica (May 23, 2016); https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing

2. Association for the Advancement of Artificial Intelligence. AAAI Workshop on AI and OR [Operations Research] for Social Good (San Francisco, CA, Feb. 2017); https://www.aaai.org/Library/ Workshops/ ws17-01.php

3. Computing Community Consortium Workshop on AI and Social Good (Washington, D. C., June 7, 2016); https://cra.org/ccc/events/ai-social-good/

4. Felten, E. and Lyons, T. The Administration’s Report on the Future of Artificial Intelligence. The White House, Oct. 12, 2016; https://obamawhitehouse.archives. gov/blog/2016/10/12/administrations-report-future- artificial-intelligence

5. Moor, J.H. What is computer ethics? Metaphilosophy

16, 4 (Mar. 1985), 266–275.

6. Stone, P., Brooks, R., Brynjolfsson, E., Calo, R., Etzioni, O., Hager, G., Hirschberg, J., Kalyanakrishnan, S., Kamar, E., Kraus, S., Leyton-Brown, K., Parkes, D., Press, W., Saxenian, A., Shah, J., Tambe, M., and Teller, A. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence (A100): Report of the 2015-2016 Study Panel. Stanford University, Stanford, CA, Sept. 2016; http://ai100.stanford. edu/2016-report

 

Barbara J. Grosz ( [e-mail]) is Higgins Professor of Natural Sciences on the Computer Science faculty of the John A. Paulson School of Engineering and Applied Sciences at Harvard University, Cambridge, MA, USA, and a member of the External Faculty of Santa Fe Institute, Santa Fe, NM, USA. She was Inaugural Chair of the standing committee for the One Hundred Year Study on Artificial Intelligence.

Peter Stone ( [e-mail]) is the David Bruton, Jr. Centennial Professor in the Department of Computer Science at The University of Texas at Austin, Austin, TX, USA, and President and COO of Cogitai, Inc. He was Chair of the inaugural study panel of the One Hundred Year Study on Artificial Intelligence.

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rather than jobs in the near term and also create new kinds of jobs. But imagining what new jobs will emerge is more difficult in advance than is identifying the existing jobs that will likely be lost. As AI applications engage in behavior that, if done by a human, would constitute a crime, courts and other legal actors will have to puzzle through whom to hold accountable and on what theory.

Reactions and Uses

Even more than when the AI100 project was first planned in 2014, we are at a crucial juncture in determining how to deploy AI-based technologies in ways that support societal needs and promote rather than hinder democratic values of freedom, equality, and transparency. The philosopher J.H. Moor wrote5 that in ethical arguments, most often people agree on values but not on the facts of the matter. This first AI100 report aims to bring AI expertise to the forefront so the challenges, as well as the promise, of technologies that incorporate AI methods can be understood and assessed properly.

Although the report’s impact over
time remains to be seen, we hope it will
establish a strong precedent for future
AI100 study panels. We are gratified to
have seen that since the report first ap-
peared, it seems to have succeeded in
this aim, along with the larger AI 100
goals, in several ways. For instance,
shortly after it was released, Septem-
ber 1, 2016, it was covered widely in the
press, including in the New York Times,
Christian Science Monitor, NPR, BBC,
and CBC radio. It helped shape a series
of workshops sponsored by the White
House Office of Science and Technology
Policy and the reports that emanated
from them. 4 Requests for permission
to translate the report into several lan-
guages demonstrate worldwide inter-
est. Various members of the AI 100
standing committee and the inaugural
study panel have been asked to organize
workshops for various governmental
and scientific organizations and give
talks in many settings. The study panel
chair (and co-author of this article) was
invited to speak by the Prime Minister
of Finland, Juha Sipilä, on the occa-
sion of his announcement of a new “AI
strategy” for Finland, in February 2017;
http://valtioneuvosto.fi/live?v=/vnk/
events-seminars/professori-peter-
stonen-puhe-tekoalyseminaarissa. The
report is also being used in AI classes in
various ways.

Looking Forward

AI technologies are becoming ever more prevalent, and opinions on their impact on individuals and societies vary widely, from those the (inaugural) study panel considered overly optimistic to others it considered overly pessimistic. The need for the general public, government, and industry to have reliable information is of increasing importance. The AI100 project aims to fill that need. This first report is an important initial step, launching a long-term project. It crucially illuminates the enormous technical differences between AI technologies that are developed and targeted toward specific application domains and a “general-purpose AI” capability that can be incorporated into any device to make it more intelligent. The former is the focus of much research and business development, while the latter remains science fiction. It is quite tempting to think that if AI technologies can help drive our cars, they ought to also be able to fold our laundry, but these two activities make very different types of demands on reasoning. They require very different algorithms and capabilities. People do both, along with a full range of equally distinct activities requiring intelligence of various sorts. However, current AI applications are based on specialized do-main-specific methods, and the normal human inclination to generalize from one intelligent behavior to seemingly related ones leads some people astray when assessing machine capabilities. This first AI100 report aims to provide insights to its readers, enabling them to better assess the implications of any AI success for other open challenges, as well as alert them to the societal and ethical issues that must be addressed as AI pervades ever more areas of daily life.

Since publishing the inaugural study panel’s report, the AI100 project has begun a complementary effort, the Artificial Intelligence Index (AI Index), an ongoing tracking activity led by a steering committee of Yoav Shoham, Ray Perrault, Erik Brynjolfsson, Jack Clark, John Etchemendy, Terah Lyons, and James Maniyka. It complements the major studies originally envisioned for AI100 by providing annual reports and, in the