ACM Special Interest Group on Artificial Intelligence

We promote and support the growth and application of AI principles and techniques throughout computing

AI Matters: our blog

Autonomous Vehicles: Policy and Technology

In 2018, we discussed language that aims at safety and degrees of autonomy rather than having, possibly unattainable, goals of completely autonomous things. A better approach, at least for the next 5-10 years, is to seek the correct balance between technology and humans in hybrid devices and systems. See for example, the Unmanned Integrated Systems Roadmap, 2017-2042 and Ethically Aligned Design. We also need to consider the limits and possibilities for research on the technologies and their impacts on time frames and the proper focus of policymaking.

In a recent interview, Dr. Harold Szu, a co-founder and former governor of the International Neural Network Society, discusses research ideas that better mimic human thinking and that could dramatically reduce the time to develop autonomous technology. He discusses a possible new level of brain-style computing that incorporates fuzzy membership functions into autonomous control systems. Autonomous technology incorporating human characteristics, along with safe policies and earlier arrival of brain-style technologies, could usher in the next big economic boom. For more details, view the Harold Szu interview.

Discussion Issues for 2019

FaceBook, Face Recognition, Autonomous Things, and the Future of Work

Four focus areas of discussions at the end of 2018 are the initial topics for the SIGAI Policy Blog as we start 2019.  The following, with links to resources, are important ongoing subjects for our Policy blogsite in the new year:

FaceBook continues to draw attention to the general issue of data privacy and the role of personal data in business models. Here are some good resources to check:
NY Times on FaceBook Privacy
FaceBook Partners
Spotify
Netflix

Facial recognition software is known to be flawed, having side effects of bias, unwanted surveillance, and other problems. The Safe Face Pledge, developed by the Algorithmic Justice League and Georgetown University Law Center of Privacy & Technology, is an example of emerging efforts to make organizations aware of problems with facial recognition products, for example in autonomous weapons systems and law enforcement agencies. The Safe Face Pledge asks that companies commit to safety in business practices and promote public policy for broad regulation and government oversight on facial recognition applications.

“Autonomous” Things: Degrees of Separation: The R&D for “autonomous” vehicles and other devices that dominate our daily lives pose challenges for technologies as well as for ethics and policy considerations. In 2018, we discussed language that aims at safety and degrees of autonomy rather than having, possibly unattainable, goals of completely autonomous things. A better approach may be to seek the correct balance between technology and humans in hybrid devices and systems. See for example, the Unmanned Integrated Systems Roadmap, 2017-2042 and Ethically Aligned Design.

The Future of Work and Education is a topic that not only tries to predict the workforce of the future, but also how society needs to prepare for it. Many experts believe that our current school systems are not up to the challenge and that industry and government programs are needed for the challenges emerging in just a few years. See, for example, writing by the Ford Foundation and the World Economic Forum.

We welcome your feedback and discussions as we enter the 2019 world of AI and policy!

ACM SIGAI Industry Award for Excellence in Artificial Intelligence

The ACM SIGAI Industry Award for Excellence in Artificial Intelligence (AI) will be given annually to individuals or teams who created AI applications in recent years in ways that demonstrate the power of AI techniques via a combination of the following features: novelty of application area, novelty and technical excellence of the approach, importance of AI techniques for the approach, and actual and predicted societal impact of the application. The award plaque is accompanied by a prize of $5,000 and will be awarded at the International Joint Conference on Artificial Intelligence through an agreement with the IJCAI Board of Trustees.

After decades of progress in the theory of AI, research and development, AI applications are now increasingly moving into the commercial sector. A great deal of pioneering application-level work is being done—from startups to large corporations—and this is influencing commerce and the broad public in a wide variety of ways. This award complements the numerous academic, best paper and related awards, in that it focuses on innovators of fielded AI applications, honoring those who are playing key roles in AI commercialization. The award honors these innovators and highlights their achievements (and thus also the benefit of AI techniques) to computing professionals and the public at large. The award committee will consider applications that are open source or proprietary and that may or may not involve hardware.

Evaluation criteria:
The criteria include the following, but there is no fixed weighting of them:

  • Novelty of application area
  • Novelty and technical excellence of the approach
  • Importance of AI techniques for the approach
  • Actual and predicted societal benefits of the fielded application

Eligibility criteria:
Any individual or team, worldwide, is eligible for the award.

Nomination procedure:
One nomination and three endorsements must be submitted. The nomination must identify the individual or team members, describe their fielded AI system, and explain how it addresses the award criteria. The nomination must be written by a member of ACM SIGAI. Two of the endorsements must be from members of ACM or ACM SIGAI. Anyone can join ACM SIGAI at any time for just US$11 (students) and US$25 (other) annual membership fee, even if they are not an ACM member.

Please submit the nomination and endorsements as a single PDF file in an email to SIGAIIndustryAward@ACM.org. We will acknowledge receipt of the nomination.

Timeline:

  • Nominations Due: March 1, 2019
  • Award Announcement: April 25, 2019
  • Award Presentation: August 10-16, 2019 at IJCAI in Macao (China)

Call for Proposals: Artificial Intelligence Activities Fund

ACM SIGAI invites funding proposals for artificial intelligence (AI) activities with a strong outreach component to either students, researchers, or practitioners not working on AI technologies or to the public in general.

The purpose of this call is to promote a better understanding of current AI technologies, including their strengths and limitations, as well as their promise for the future. Examples of fundable activities include (but are not limited to) AI technology exhibits or exhibitions, holding meetings with panels on AI technology (including on AI ethics) with expert speakers, creating podcasts or short films on AI technologies that are accessible to the public, and holding AI programming competitions. ACM SIGAI will look for evidence that the information presented by the activity will be of high quality, accurate, unbiased (for example, not influenced by company interests), and at the right level for the intended audience.

ACM SIGAI has set aside $10,000 to provide grants of up to $2,000 each, with priority given to a) proposals from ACM affiliated organizations other than conferences (such as ACM SIGAI chapter or ACM chapters), b) out-of-the-box ideas, c) new activities (rather than existing and recurring activities), d) activities with long-term impact, e) activities that reach many people, and f) activities co-funded by others. We prefer not to fund activities for which sufficient funding is already available from elsewhere or that result in profit for the organizers. Note that expert talks on AI technology can typically be arranged with financial support of the ACM Distinguished Speaker program (https://speakers.acm.org/) and then are not appropriate for funding via this call.

A proposal should contain the following information on at most 3 pages:

  • a description of the activity (including when and where it will be held);
  • a budget for the activity and the amount of funding requested, and whether other organizations have been or will be approached for funding (and, if so, for how much);
  • an explanation of how the activity fits this call (including whether it is new or recurring, which audience it will benefit, and how large the audience is);
  • a description of the organizers and other participants (such as speakers) involved in the activity (including their expertise and their affiliation with ACM SIGAI or ACM);
  • a description of what will happen to the surplus in case there is, unexpectedly, one; and
  • the name, affiliation, and contact details (including postal and email address, phone number, and URL) of the corresponding organizer.

Grantees are required to submit reports to ACM SIGAI following completion of their activities with details on how they utilized the funds and other information which might also be published in the ACM SIGAI newsletter “AI Matters.”

The deadline for submissions is 11:59pm on March 15, 2019 (UTC-12). Proposals should be submitted as pdf documents in any style at

https://easychair.org/conferences/?conf=sigaiaaf2019.

The funding decisions of ACM SIGAI are final and cannot be appealed. Some funding earmarked for this call might not be awarded at the discretion of ACM SIGAI, for example, in case the number of high-quality proposals is not sufficiently large. In case of questions, please first check the ACM SIGAI blog for announcements and clarifications: https://sigai.acm.org/aimatters/blog/. Questions should be directed to Sven Koenig (skoenig@usc.edu).

ACM and ACM SIGAI

ACM brings together computing educators, researchers, and professionals to inspire dialogue, share resources, and address the field’s challenges. As the world’s largest computing society, ACM strengthens the profession’s collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM’s reach extends to every part of the globe, with more than half of its 100,000 members residing outside the U.S.  Its growing membership has led to Councils in Europe, India, and China, fostering networking opportunities that strengthen ties within and across countries and technical communities. Their actions enhance ACM’s ability to raise awareness of computing’s important technical, educational, and social issues around the world. See https://www.acm.org/ for more information.

ACM SIGAI brings together academic and industrial researchers, practitioners, software developers, end users, and students who are interested in AI. It promotes and supports the growth and application of AI principles and techniques throughout computing, sponsors or co-sponsors AI-related conferences, organizes the Career Network and Conference for early-stage AI researchers, sponsors recognized AI awards, supports AI journals, provides scholarships to its student members to attend conferences, and promotes AI education and publications through various forums and the ACM digital library. See https://sigai.acm.org/ for more information.

Sven Koenig, ACM SIGAI chair
Sanmay Das, ACM SIGAI vice-chair
Rosemary Paradis, ACM SIGAI secretary/treasurer
Michael Rovatsos, ACM SIGAI conference coordination officer
Nicholas Mattei, ACM SIGAI AI and society officer

Follow the Data

The Ethical Machine — Big Ideas for Designing Fairer AI and Algorithms – is a “project that presents ideas to encourage a discussion about designing fairer algorithms” of the Shorenstein Center on Media, Politics, and Public Policy, Harvard Kennedy School. The November 27, 2018, publication is “Follow the Data! Algorithmic Transparency Starts with Data Transparency” by Julia Stoyanovich and Bill Howe. Their focus is local and municipal governments and NGOs that deliver vital human services in health, housing, and mobility. In the article, they give a welcome emphasis on the role of data instead of the common focus these days on just algorithms. They write, “data is used to customize generic algorithms for specific situations—that is to say that algorithms are trained using data. The same algorithm may exhibit radically different behavior—make different predictions; make a different number of mistakes and even different kinds of mistakes—when trained on two different data sets. In other words, without access to the training data, it is impossible to know how an algorithm would actually behave.” See their article for more discussion on designing systems for data transparency.

US and European Policy
Adam Eisgrau, ACM Director of Global Policy and Public Affairs, published an update on the ACM US and Europe Policy Committees in the November 29 ACM MemberNetKey points are