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 ( grosz@eecs.harvard.edu) 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 ( pstone@cs.utexas.edu) 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.
Copyright held by authors.
Publication rights licensed to ACM. $15.00
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