We are pleased to announce that the recipients of the 2018 ACM A.M. Turing Award are AI researchers Yoshua Bengio, Professor at the University of Montreal and Scientific Director at Mila; Geoffrey Hinton, Professor at the University of Toronto and Chief Scientific Advisor at the Vector Institute; and Yann LeCun, Professor at New York University and Chief AI Scientist at Facebook.
Their citation reads as follows:
For conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing.
Bengio, Hinton, and LeCun will be presented with the Turing Award at the June 15, 2019 ACM Awards Banquet in San Francisco.
Editor-In-Chief ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)
The term of the current Editor-in-Chief (EiC) of the ACM Trans. on Asian and Low-Resource Language
Information Processing (TALLIP) is coming to an end, and the ACM Publications Board has set up a nominating
committee to assist the Board in selecting the next EiC. TALLIP was established in 2002 and has been
experiencing steady growth, with 178 submissions received in 2017.
Nominations, including self nominations, are invited for a three-year term
as TALLIP EiC, beginning on June 1, 2019. The EiC appointment may be renewed at most one
time. This is an entirely voluntary position, but ACM will provide appropriate
administrative support.
Appointed by the ACM Publications Board,
Editors-in-Chief (EiCs) of ACM journals are delegated full responsibility for
the editorial management of the journal consistent with the journal’s charter
and general ACM policies. The Board relies on EiCs to ensure that the content
of the journal is of high quality and that the editorial review process is both
timely and fair. He/she has final say on acceptance of papers, size of
the Editorial Board, and appointment of Associate Editors. A complete list of
responsibilities is found in the ACM
Volunteer Editors Position Descriptions. Additional information can be
found in the following documents:
Nominations should include a vita along with a brief statement of why the
nominee should be considered. Self-nominations are encouraged, and should
include a statement of the candidate’s vision for the future development of TALLIP.
The deadline for submitting nominations is April 15, 2019, although nominations
will continue to be accepted until the position is filled.
Please send all nominations to the nominating committee chair, Monojit
Choudhury (monojitc@microsoft.com).
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)
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
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. Seehttps://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. Seehttps://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
The Special Interest Group on Artificial Intelligence of the Association for Computing Machinery (ACM SIGAI) and the Association for the Advancement of Artificial Intelligence (AAAI) are happy to announce that they have established the Joint AAAI/ACM SIGAI Doctoral Dissertation Award to recognize and encourage superior research and writing by doctoral candidates in artificial intelligence. This annual award is presented at the AAAI Conference on Artificial Intelligence in the form of a certificate and is accompanied by the option to present the dissertation at the AAAI conference as well as to submit one 6-page summary for both the AAAI proceedings and the newsletter of ACM SIGAI. Up to two Honorable Mentions may also be awarded, also with the option to present their dissertations at the AAAI conference as well as submit one 6-page summary for both the AAAI proceedings and the newsletter of ACM SIGAI. The award will be presented for the first time at the AAAI conference in 2020 for dissertations that have been successfully defended (but not necessarily finalized) between October 1, 2018 and September 30, 2019. Nominations are welcome from any country, but only English language versions will be accepted. Only one nomination may be submitted per Ph.D. granting institution, including large universities. Dissertations will be reviewed for relevance to artificial intelligence, technical depth and significance of the research contribution, potential impact on theory and practice, and quality of presentation. The details of the nomination process will be announced in early 2019.
It’s no secret the general public has mixed views about artificial intelligence, largely stemming from a misunderstanding of the topic. In the public’s mind, AI tends to be equated to the creation of nearly lifelike robots and, although sometimes it is, there is much more to the rapidly-advancing technology.
In today’s society AI is playing an everyday role in the lives of most people, ranging from ride-hailing apps like Uber and Lyft to Facebook’s facial recognition, but the technology is constantly advancing. For example, Google’s new AI assistantis revolutionizing the way people go about their daily tasks, and recent advancements made possible by AI in healthcare are changing the way cancer research is approached.
Although the term “AI” dates back to the mid-1950s, it has become so sophisticated in recent years that a cure for cancer could be around the corner. Vice President Joe Biden’s Cancer Moonshot Initiative aims to find a cure for cancer and provide patients with more treatment options using AI technology to process and sort data from cancer researchers. In an attempt to reach its mission of driving 10 years’ worth of research in only five, AI is also being used to detect certain cancers earlier than what’s possible using other currently available diagnostic procedures.
The ability to diagnose certain cancers, including brain cancer, skin cancer and mesothelioma, through the use of this technology is, arguably, one of the most important advancements in healthcare as a result of AI. This is especially groundbreaking for patients battling mesothelioma, a rare cancer that develops in the mesotheliumof the lungs, heart or abdomen. Mesothelioma has a decades-long latency period and symptoms are often mistaken for those associated with more common ailments. Unfortunately, the disease has an average prognosis of 6-12 months and leaves patients with little time to coordinate treatment. Ultimately, the earlier detection and diagnosis of cancers may lead to better prognoses and outcomes.s
Using AI, the cloud and other tools, companies like IBM and Microsoft are attempting to change the way healthcare is approached. Following its creation in 2013, IBM’s supercomputer, Watson, successfully won $1 million in a game of Jeopardy!against two of the show’s most successful contestants, and is making attempts to streamline the process of diagnosing diseases in patients more efficiently.
Although IBM Watson hasn’t made as much progress as anticipated, the technology was proven capable during a 2017 study. The research monitored the amount of time it took Watson to create a treatment plan versus the amount of time it took doctors. The results showed that Watson was able to create a plan of treatment for a brain cancer patient in 10 minutes, while the process took between 160 hours for doctors.
However, the study wasn’t a complete win for Watson. Comparatively, Watson’s suggested plan of action was short sighted due to an inefficiency to consider multiple treatment options. While doctors were able to consider several possibilities at once, Watson could not.
Healthcare NExT, Microsoft’s internal initiative announced in 2017, is also focusing on using technology to find solutions to questions in the healthcare industry, including a cure for cancer.
In a Microsoft blog post about Healthcare NExT, Peter Lee, Corporate Vice President of Microsoft AI + Research says, Microsoft is “expanding [its] commitment to building a healthier future with new initiatives and solutions, making it easier for health industry partners and organizations to use intelligent technology to improve the lives of people around the world.”
Technology has changed dramatically within the past decade. Newly-developed diagnostic methods and an advanced approach to healthcare that we could have only dreamed of in the past are changing the way we see the world today. Although machines are still learning and there is a lot of room to improve, the work that’s been done in such a short period of time is nothing short of incredible.
Are we closer to a cure for cancer than even we know?
The selection committee for the ACM/SIGAI Autonomous Agents Research Award is pleased to announce that Dr. Craig Boutilier, Principal Research Scientist at Google, is the recipient of the 2018 award. Over the years, Dr. Boutilier has made seminal contributions to research on decision-making under uncertainty, game theory, and computational social choice. He is a pioneer in applying decision-theoretic concepts in novel ways in a variety of domains including (single- and multi-agent) planning and reinforcement learning, preference elicitation, voting, matching, facility location, and recommender systems. His recent research continues to significantly influence the field of computational social choice through the novel computational and methodological tools he introduced and his focus on modeling realistic preferences. In addition to his reputation for outstanding research, Dr. Boutilier is also recognized as an exceptional teacher and mentor.
Artificial Intelligence Journal:
FUNDING OPPORTUNITIES for PROMOTING AI RESEARCH
Deadline for proposals: extended to January 20th, 2018
The Artificial Intelligence Journal (AIJ) is one of the longest established and most respected journals in AI, and since it was founded in 1970, it has published many of the key papers in the field. The operation of the Editorial Board is supported financially through an arrangement with AIJ’s publisher, Elsevier. Through this arrangement, the AIJ editorial board is able to make available substantial funds (of the order of 230,000 Euros per annum), to support the promotion and dissemination of AI research. Most of these funds are made available through a series of competitive open calls (the remaining part of the budget is reserved for sponsorship of studentships for the annual IJCAI conference).
The current call has a deadline of January 20th, 2018 and a budget of 120,000 Euros.
Proposals should be submitted following the format and content guidelines, as well as submission instructions, that can be found on the AIJ web site:
(We posted this call at a time when the above website had not yet been updated but it will soon be, hopefully by the time when you are reading this blog post. In the meantime, you can click here for the details.)
Welcome! This column is the fifth in our series profiling senior AI researchers. This month focuses on Dr. Ayanna Howard. In addition to our interview, Dr. Howard was recently interviewed by NPR and they created an animated video about how “Being Different Helped A NASA Roboticist Achieve Her Dream.”
Ayanna Howard’s Bio
Ayanna Howard
Ayanna Howard, Ph.D. is Professor and Linda J. and Mark C. Smith Endowed Chair in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. As an educator, researcher, and innovator, Dr. Howard’s career focus is on intelligent technologies that must adapt to and function within a human-centered world. Her work, which encompasses advancements in artificial intelligence (AI), assistive technologies, and robotics, has resulted in over 200 peer-reviewed publications in a number of projects – from assistive robots in the home to AI-powered STEM apps for children with diverse learning needs. She has over 20 years of R&D experience covering a number of projects that have been supported by various agencies including: National Science Foundation, NewSchools Venture Fund, Procter and Gamble, NASA, and the Grammy Foundation. Dr. Howard received her B.S. in Engineering from Brown University, her M.S.E.E. from the University of Southern California, her M.B.A. from the Drucker Graduate School of Management, and her Ph.D. in Electrical Engineering from the University of Southern California. To date, her unique accomplishments have been highlighted through a number of awards and articles, including highlights in USA Today, Upscale, and TIME Magazine, as well as being named a MIT Technology Review top young innovator and recognized as one of the 23 most powerful women engineers in the world by Business Insider. In 2013, she also founded Zyrobotics, which is currently licensing technology derived from her research and has released their first suite of STEM educational products to engage children of all abilities. From 1993-2005, Dr. Howard was at NASA’s Jet Propulsion Laboratory. She has also served as the Associate Director of Research for the Georgia Tech Institute for Robotics and Intelligent Machines and as Chair of the multidisciplinary Robotics Ph.D. program at Georgia Tech.
How did you become interested in Computer Science and AI?
I first became interested in robotics as a young, impressionable, middle school girl. My motivation was the television series called The Bionic Women – my goal in life, at that time, was to gain the skills necessary to build the bionic women. I figured that I had to acquire combined skill sets in engineering and computer science in order to accomplish that goal. With respect to AI, I became interested in AI after my junior year in college, when I was required to design my first neural network during my third NASA summer internship in 1992. I quickly saw that, if I could combine the power of AI with Robotics – I could enable the ambitious dreams of my youth.
What was your most difficult professional decision and why?
The most difficult professional decision I had to make, in the past, was to leave NASA and pursue robotics research as an academic. The primary place I’d worked at from 1990 until 2005 was at NASA. I’d grown over those 15 years in my technical job positions from summer intern to computer scientist (after college graduation) to information systems engineer, robotics researcher, and then senior robotics researcher. And then, I was faced with the realization that, in order to push my ambitious goals in robotics, I needed more freedom to pursue robotics applications outside of space exploration. The difficulty was, I still enjoyed the space robotics research efforts I was leading at NASA, but I also felt a need to expand beyond my intellectual comfort zone.
What professional achievement are you most proud of?
The professional achievement I am proudest of is founding of a startup company, Zyrobotics, which has commercialized educational products based on technology licensed from my lab at Georgia Tech. I’m most proud of this achievement because it allowed me to combine all of the hard-knock lessons I’ve learned in designing artificial intelligence algorithms, adaptive user interfaces, and human-robot interaction schemes with a real-world application that has large societal impact – that of engaging children of diverse abilities in STEM education, including coding.
What do you wish you had known as a Ph.D. student or early researcher?
As a Ph.D. student, I wish I had known that finding a social support group is just as important to your academic growth as finding an academic/research home. I consider myself a fairly stubborn person – I consider words of discouragement a challenge to prove others wrong. But psychological death by a thousand cuts (i.e. words of negativism) is a reality for many early researchers. A social support group helps to balance the negativism that others, sometimes unconsciously, subject others too.
What would you have chosen as your career if you hadn’t gone into CS?
If I hadn’t gone into the field of Robotics/AI, I would have chosen a career as a forensic scientist. I’ve always loved puzzles and in forensic science, as a career, I would have focused on solving life puzzles based on the physical evidence. The data doesn’t lie (although, as we know, you can bias the data so it seems to).
What is a “typical” day like for you?
Although I have no “typical” day – I can categorize my activities into five main buckets, in no priority order: 1) human-human interactions, 2) experiments and deployments, 3) writing (including emails), 4) life balance activities, and 5) thinking/research activities. Human-human interactions involve everything from meeting with my students to talking with special education teachers to one-on-one observations in the pediatric clinic. Experiments and deployments involve everything from running a participant study to evaluating the statistics associated with a study hypothesis. Writing involves reviewing my students’ publication drafts, writing proposals, and, of course, addressing email action items. Life-balance activities include achieving my daily exercise goals as well as ensuring I don’t miss any important family events. Finally thinking/research activities covers anything related to coding up a new algorithm, consulting with my company, or jotting down a new research concept on a scrap of paper.
What is the most interesting project you are currently involved with?
The most interesting project that I currently lead involves an investigation in developing robot therapy interventions for young children with motor disabilities. For this project, we have developed an interactive therapy game called SuperPop VR that requires children to play within a virtual environment based on a therapist-designed protocol. A robot playmate interacts with each child during game play and provides both corrective and motivational feedback. An example of corrective feedback is when the robot physically shows the child how to interact with the game at the correct movement speed (as compared to a normative data profile). An example of motivational feedback is when the robot, through social interaction, encourages the child when they have accomplished their therapy exercise goal. We’ve currently deployed the system in pilot studies with children with Cerebral Palsy and have shown positive changes with respect to their kinematic outcome metrics. We’re pushing the state-of-the-art in this space by incorporating additional factors for enhancing the long-term engagement through adaptation of both the therapy protocol as well as the robot behaviors.
How do you balance being involved in so many different aspects of the AI community?
In order for me to become involved in any new AI initiative and still maintain a healthy work-life balance, I ask myself – Is this initiative something that’s important to me and aligned with my value system; Can I provide a unique perspective to this initiative that would help to make a difference; Is it as important or more important than other initiatives I’m involved in; and Is there a current activity that I can replace so I have time to commit to the initiative now or in the near-future. If the answer is yes to all those questions, then I’m usually able to find an optimal balance of involvement in the different AI initiatives of interest.
What is your favorite CS or AI-related movie or book and why?
My favorite AI-related movie is the Matrix. What fascinates me about the Matrix is the symbiotic relationship that exists between humans and intelligent agents (both virtual and physical). One entity can not seem to exist without the other. And operating in the physical world is much more difficult than operating in the virtual, although most agents don’t realize that difference until they accept the decision to navigate in both types of worlds.
Nominations are solicited for the 2018 ACM SIGAI Autonomous Agents Research Award. This award is made for excellence in research in the area of autonomous agents. It is intended to recognize researchers in autonomous agents whose current work is an important influence on the field. The award is an official ACM award, funded by an endowment created by ACM SIGAI from the proceeds of previous Autonomous Agents conferences. The recipient of the award will receive a monetary prize and a certificate, and will be invited to present a plenary talk at the AAMAS 2018 conference in Stockholm, Sweden.
Previous winners of the ACM SIGAI Autonomous Agents Research Award are: David Parkes (2017), Peter Stone (2016), Catherine Pelachaud (2015), Michael Wellman (2014), Jeff Rosenschein (2013), Moshe Tennenholtz (2012), Joe Halpern (2011), Jonathan Gratch and Stacy Marsella (2010), Manuela Veloso (2009), Yoav Shoham (2008), Sarit Kraus (2007), Michael Wooldridge (2006), Milind Tambe (2005), Makoto Yokoo (2004), Nicholas R. Jennings (2003), Katia Sycara (2002), and Tuomas Sandholm (2001). For more information on the award, see the Autonomous Agents Research Award page.
How to nominate
Anyone can make a nomination. Nominations should be made by email to the chair of the award committee, Jeff Rosenschein (jeff@cs.huji.ac.il), and should consist of a short (< 1 page) statement that emphasizes not only the research contributions that the individual has made that merit the award but also how the individual’s current work is an important influence on the field.
NOTE: a candidate can only be considered for the award if they are explicitly nominated. If you believe that someone deserves the award, then NOMINATE THEM — don’t assume that somebody else will!
Important dates
17 January 2018 — Deadline for nominations
7 February 2018 — Announcement of 2017 winner
10-15 July 2018 — AAMAS-2018 conference in Stockholm
