ai matters, volume 4, issue 44(4) 2018 ai matters
TRANSCRIPT
AI MATTERS, VOLUME 4, ISSUE 4 4(4) 2018
AI MattersAnnotated Table of Contents
Welcome to AI Matters 4(4)Amy McGovern, co-editor & IolandaLeite, co-editor
Full article: http://doi.acm.org/10.1145/3299758.3299759
Welcome and summary
Call for Proposals: Artificial Intelli-gence Activities FundSven Koenig, Sanmay Das, RosemaryParadis, Michael Rovatsos & NicholasMattei
Full article: http://doi.acm.org/10.1145/3299758.3299760
Artificial Intelligence Activities Fund
AI Profiles: An Interview with IolandaLeiteMarion Neumann
Full article: http://doi.acm.org/10.1145/3299758.3299761
Interview with Iolanda Leite
EventsMichael Rovatsos
Full article: http://doi.acm.org/10.1145/3299758.3299762
Upcoming AI events
Conference ReportsMichael Rovatsos
Full article: http://doi.acm.org/10.1145/3299758.3299763
Conference Reports
AI Education Matters: A Modular Ap-proach to AI Ethics EducationHeidi Furey & Fred Martin
Full article: http://doi.acm.org/10.1145/3299758.3299764
AI Ethics Education
AI Policy MattersLarry Medsker
Full article: http://doi.acm.org/10.1145/3299758.3299765
TAI Policy Matters
Epochs of an AI CosmologyCameron Hughes & Tracey Hughes
Full article: http://doi.acm.org/10.1145/3299758.3299868
AI Cosmology
Artificial Intelligence and Jobs of theFuture: Adaptability Is Key for Hu-man EvolutionSudarshan Sreeram
Full article: http://doi.acm.org/10.1145/3299758.3300060
AI and Jobs of the Future
Links
SIGAI website: http://sigai.acm.org/Newsletter: http://sigai.acm.org/aimatters/Blog: http://sigai.acm.org/ai-matters/Twitter: http://twitter.com/acm sigai/Edition DOI: 10.1145/3284751
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Notice to Contributing Authorsto SIG Newsletters
By submitting your article for distribution in thisSpecial Interest Group publication, you herebygrant to ACM the following non-exclusive, per-petual, worldwide rights:
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Submit to AI Matters!
We’re accepting articles and announce-ments now for the next issue. Details onthe submission process are available athttp://sigai.acm.org/aimatters.
AI Matters Editorial Board
Amy McGovern, Co-Editor, U. OklahomaIolanda Leite, Co-Editor, KTHSanmay Das, Washington Univ. in Saint LouisAlexei Efros, Univ. of CA BerkeleySusan L. Epstein, The City Univ. of NYYolanda Gil, ISI/Univ. of Southern CaliforniaDoug Lange, U.S. NavyKiri Wagstaff, JPL/CaltechXiaojin (Jerry) Zhu, Univ. of WI Madison
Contact us: [email protected]
Contents Legend
Book Announcement
Ph.D. Dissertation Briefing
AI Education
Event Report
Hot Topics
Humor
AI Impact
AI News
Opinion
Paper Precis
Spotlight
Video or Image
Details at http://sigai.acm.org/aimatters
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Welcome to AI Matters 4(4)Amy McGovern, co-editor (University of Oklahoma; [email protected])Iolanda Leite, co-editor (Royal Institute of Technology (KTH); [email protected])DOI: 10.1145/3299758.3299759
Welcome to our new co-editor!
Welcome to the fourth issue of the fourth vol-ume of the AI Matters Newsletter! Our biggestnews is that we would like to extend a big wel-come to our new co-editor! Iolanda Leite isan Assistant Professor at the School of Com-puter Science and Electrical Engineering atthe KTH Royal Institute of Technology in Swe-den. Iolanda is excited to join the AI Mat-ters team and to help to continue to grow thenewsletter for ACM SIGAI. She is also ourguest for the interview this month so pleasego to our interview and learn more about ournew co-editor!
Announcements
Joint AAAI/ACM SIGAI DoctoralDissertation Award
The Special Interest Group on Artificial In-telligence of the Association for ComputingMachinery (ACM SIGAI) and the Associationfor the Advancement of Artificial Intelligence(AAAI) are happy to announce that they haveestablished the Joint AAAI/ACM SIGAI Doc-toral Dissertation Award to recognize and en-courage superior research and writing by doc-toral candidates in artificial intelligence. Thisannual award is presented at the AAAI Con-ference on Artificial Intelligence in the form ofa certificate and is accompanied by the op-tion to present the dissertation at the AAAIconference as well as to submit one 6-pagesummary for both the AAAI proceedings andthe newsletter of ACM SIGAI. Up to two Hon-orable Mentions may also be awarded, alsowith the option to present their dissertationsat the AAAI conference as well as submit one6-page summary for both the AAAI proceed-ings and the newsletter of ACM SIGAI. Theaward will be presented for the first time at theAAAI conference in 2020 for dissertations thathave been successfully defended (but not nec-essarily finalized) between October 1, 2018
Copyright c© 2018 by the author(s).
and September 30, 2019. Nominations arewelcome from any country, but only Englishlanguage versions will be accepted. Only onenomination may be submitted per Ph.D. grant-ing institution, including large universities. Dis-sertations will be reviewed for relevance to ar-tificial intelligence, technical depth and signif-icance of the research contribution, potentialimpact on theory and practice, and quality ofpresentation. The details of the nominationprocess will be announced in early 2019.
ACM SIGAI Student Essay Contest
The ACM Special Interest Group on ArtificialIntelligence (ACM SIGAI) supports the devel-opment and responsible application of Artifi-cial Intelligence (AI) technologies. We there-fore invite essay submissions to the 2018ACM SIGAI Student Essay Contest, to be pub-lished in the ACM SIGAI newsletter AI Mat-ters, addressing one or both of the followingtopic areas:
• What requirements, if any, should be im-posed on AI systems and technology wheninteracting with humans who may or may notknow that they are interacting with a ma-chine?
• What requirements, if any, should be im-posed on AI systems and technology whenmaking decisions that directly affect hu-mans?
Win one of several $500 monetary prizes ora Skype conversation with a leading AI re-searcher, including Joanna Bryson, MurrayCampbell, Eric Horvitz, Peter Norvig, IyadRahwan, Francesca Rossi, or Toby Walsh.
The deadline for submissions is January10th, 2019.
For details, please visit the blog announce-ment.
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*New Conflict of Interest andRetractions Policies
The ACM Publications Board has approvednew Conflict of Interest and Retractions poli-cies. Both of these new policies are nowposted on ACM’s website at:
https://www.acm.org/publications/policies/conflict-of-interest
Issue overview
This issue opens with an interview from Mar-ion Newmann of our new co-editor: IolandaLeite. We also have a summary of recent AIconferences and events from Michael Rovat-sos. Our educational column this issue pro-vides a model AI assignment for teachingethics in AI focused on autonomous vehicles.
Larry Medsker’s policy column summarizes avariety of policy issues of interest to the SIGAIcommunity including the creation of a newRoadmap for Artificial Intelligence, FTC hear-ings on AI, and recent discussions on how todesign AI to be safe as well as issues sur-rounding legality of AI. He closes with a shortdiscussion of privacy for AI Matters. ACM’sagreement with EasyChair specifies that wecollect age and gender data and we welcomeany discussion on our proposed response tothis data collection.
Finally, we close with two paper contributions.The first is a continuation of the discussion ofan AI “cosmology” by our contributing editorsCameron Hughes and Tracey Hughes. Theypropose the idea of epochs of AI in their cur-rent article. The second paper discusses thefuture of AI and how it will affect jobs.
Submit to AI Matters!Thanks for reading! Don’t forget to sendyour ideas and future submissions to AIMatters! We’re accepting articles and an-nouncements now for the next issue. De-tails on the submission process are avail-able at http://sigai.acm.org/aimatters.
Amy McGovern is co-editor of AI Matters. Sheis a Professor of com-puter science at the Uni-versity of Oklahoma andan adjunct Professor ofmeteorology. She directsthe Interaction, Discovery,Exploration and Adapta-tion (IDEA) lab. Her re-search focuses on ma-
chine learning and data mining with applica-tions to high-impact weather.
Iolanda Leite is co-editorof AI Matters. She is anAssistant Professor at theSchool of Computer Sci-ence and Electrical Engi-neering at the KTH RoyalInstitute of Technology inSweden. Her research in-terests are in the areas of
Human-Robot Interaction and Artificial Intelli-gence. She aims to develop autonomous so-cially intelligent robots that can assist peopleover long periods of time.
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Call for Proposals: Artificial Intelligence Activities FundSven Koenig (elected; ACM SIGAI Chair)Sanmay Das (elected; ACM SIGAI Vice-Chair)Rosemary Paradis (elected; ACM SIGAI Secretary/Treasurer)Michael Rovatsos (appointed; ACM SIGAI Conference Coordination Officer)Nicholas Mattei (appointed; ACM SIGAI AI and Society Officer)DOI: 10.1145/3299758.3299760
ACM SIGAI invites funding proposals for arti-ficial intelligence (AI) activities with a strongoutreach component to either students, re-searchers, or practitioners not working on AItechnologies or to the public in general.
The purpose of this call is to promote a betterunderstanding of current AI technologies, in-cluding their strengths and limitations, as wellas their promise for the future. Examples offundable activities include (but are not limitedto) AI technology exhibits or exhibitions, hold-ing meetings with panels on AI technology (in-cluding on AI ethics) with expert speakers,creating podcasts or short films on AI tech-nologies that are accessible to the public, andholding AI programming competitions. ACMSIGAI will look for evidence that the informa-tion presented by the activity will be of highquality, accurate, unbiased (for example, notinfluenced by company interests), and at theright level for the intended audience.
ACM SIGAI has set aside $10,000 to providegrants of up to $2,000 each, with priority givento a) proposals from ACM affiliated organiza-tions other than conferences (such as ACMSIGAI chapters or ACM chapters), b) out-of-the-box ideas, c) new activities (rather than ex-isting and recurring activities), d) activities withlong-term impact, e) activities that reach manypeople, and f) activities co-funded by others.We prefer not to fund activities for which suf-ficient funding is already available from else-where or that result in profit for the organiz-ers. Note that expert talks on AI technologycan typically be arranged with financial sup-port of the ACM Distinguished Speaker pro-gram (https://speakers.acm.org/) andthen are not appropriate for funding via thiscall.
A proposal should contain the following infor-
Copyright c© 2018 by the author(s).
mation on at most 3 pages:
• a description of the activity (including whenand where it will be held); a budget forthe activity and the amount of funding re-quested, and whether other organizationshave been or will be approached for fund-ing (and, if so, for how much); an explana-tion of how the activity fits this call (includingwhether it is new or recurring, which audi-ence it will benefit, and how large the audi-ence is);
• a description of the organizers and otherparticipants (such as speakers) involved inthe activity (including their expertise andtheir affiliation with ACM SIGAI or ACM);
• a description of what will happen to the sur-plus in case there is, unexpectedly, one; and
• the name, affiliation, and contact details (in-cluding postal and email address, phonenumber, and URL) of the corresponding or-ganizer.
Grantees are required to submit a report toACM SIGAI following completion of their ac-tivities with details on how they utilized thefunds and other information which might alsobe published in the ACM SIGAI newsletter “AIMatters”.
The deadline for submissions is 11:59pm onMarch 15, 2019 (UTC-12). Proposals shouldbe submitted as pdf documents in any style at
https://easychair.org/conferences/?conf=sigaiaaf2019.
The funding decisions of ACM SIGAI are fi-nal and cannot be appealed. Some fund-ing earmarked for this call might not beawarded at the discretion of ACM SIGAI,for example, in case the number of high-quality proposals is not sufficiently large. Incase of questions, please first check the
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ACM SIGAI blog for announcements andclarifications: https://sigai.acm.org/aimatters/blog/. Questions should be di-rected to Sven Koenig ([email protected]).
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AI Profiles: An Interview with Iolanda LeiteMarion Neumann (Washington University in St. Louis; [email protected])DOI: 10.1145/3299758.3299761
Introduction
This column is the seventh in our series pro-filing senior AI researchers. This month weare happy to interview Iolanda Leite, AssistantProfessor at the School of Computer Scienceand Electrical Engineering at the KTH RoyalInstitute of Technology in Sweden. This is agreat opportunity to get to know Iolanda, thenew AI Matters co-editor in chief. Welcome onboard!
Figure 1: Iolanda Leite
Biography
Iolanda Leite is an Assistant Professor atthe School of Computer Science and Electri-cal Engineering at the KTH Royal Institute ofTechnology in Sweden. She holds a PhD inInformation Systems and Computer Engineer-ing from IST, University of Lisbon. Prior to join-ing KTH, she was a Research Assistant at theIntelligent Agents and Synthetic CharactersGroup at INESC-ID Lisbon, a Postdoctoral As-sociate at the Yale Social Robotics Lab and anAssociate Research Scientist at Disney Re-search Pittsburgh. Iolanda’s research inter-ests are in the areas of Human-Robot Inter-action and Artificial Intelligence. She aims todevelop autonomous socially intelligent robotsthat can assist people over long periods oftime.
Copyright c© 2018 by the author(s).
Getting to Know Iolanda Leite
When and how did you become interestedin CS and AI?
I became interested in CS at the age of 4 whenthe first computer arrived at our home. It ismore difficult to establish a time to define myinterest in AI. I was born in the 80s and havealways been fascinated by toys that had somelevel of “intelligence” or “life-likeness” like theTamagotchi or the Furby robots. During myMaster’s degree, I chose the Intelligent Sys-tems specialization. That time was probablywhen I seriously considered a research careerin this area.
What professional achievement are youmost proud of?
Seeing my students accomplish great thingson their own.
What would you have chosen as yourcareer if you hadn’t gone into CS?
I always loved to work with children so maybesomething related to child education.
What do you wish you had known as aPh.D. student or early researcher?
As an early researcher I often had a hard timedealing with the rejection of papers, applica-tions, etc. What I wish the “past me” couldknow is that if one keeps working hard, thingswill eventually work out well in the end. Inother words, keeping faith in the system.
What is the most interesting project youare currently involved with?
All of them! If I have to highlight one, weare working with elementary schools that haveclasses of newly arrived children in a projectwhere we are using social robots to promoteinclusion between newly arrived and local chil-dren. This is part of an early career fellowshipawarded by the Jacobs Foundation.
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We currently observe many promising andexciting advances in using AI ineducation, going beyond automatingPiazza answering, how should we makeuse of AI to teach AI?
I believe that AI can be used to complementteachers and provide personalized instructionto students of all ages and in a variety of top-ics. Robotic tutors can play an important rolein education because the mere physical pres-ence of a robot has shown to have a positiveimpact on how much information students canrecall, for example when compared to a virtualagent displayed in a computer screen deliver-ing the exact same content.
How can we make AI more diverse? Doyou have a concrete idea on what we as(PhD) students, researchers, andeducators in AI can do to increasediversity our field?
Something we can all do is to participate inoutreach initiatives targeting groups underrep-resented in AI to show them that there isspace for them in the community. If we startbottom-up, in the long-term I am positive thatour community will be more diverse at all lev-els and the bias in opportunities, recruiting,etc. will go away.
What was your most difficult professionaldecision and why?
Leaving my home country (Portugal) after fin-ishing my PhD to continue my research careerbecause I miss my family and friends, and alsothe good weather!
How do you balance being involved in somany different aspects of the AIcommunity?
I love what I do and I currently don’t have anyhobbies :-)
AI is grown up - it’s time to make use of itfor good. Which real-world problem wouldyou like to see solved by AI in the future?
If AI could fully address any of the SustainableDevelopment Goals established by the United
Nations, it would be (more than) great. Al-though there are excellent research and fund-ing initiatives in that direction, we are still notthere yet.
What is your favorite AI-related movie orbook and why?
One of my favorite ones recently was theWestworld TV Series because of the powerrelationships between the human and therobotic characters. I find it hard to believethat humans will treat robots the way they aretreated in the series, but it makes me reflecton how our future interactions with technol-ogy that is becoming more personalized and“human-like” might look like.
Help us determine whoshould be in the AI Mat-ters spotlight!
If you have suggestionsfor who we should pro-file next, please feel freeto contact us via email [email protected].
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EventsMichael Rovatsos (University of Edinburgh; [email protected])DOI: 10.1145/3299758.3299762
This section features information about up-coming events relevant to the readers of AIMatters, including those supported by SIGAI.We would love to hear from you if you areorganizing an event and would be interestedin cooperating with SIGAI, or if you haveannouncements relevant to SIGAI. For moreinformation about conference support visitsigai.acm.org/activities/requesting sponsor-ship.html.
21st International Conference onEntreprise Information SystemsHeraklion, Crete, Greece, May 3-5, 2019www.iceis.orgThe purpose of the 21st International Con-ference on Enterprise Information Systems(ICEIS) is to bring together researchers, en-gineers and practitioners interested in the ad-vances and business applications of informa-tion systems. Six simultaneous tracks will beheld, covering different aspects of EnterpriseInformation Systems Applications, includingEnterprise Database Technology, Systems In-tegration, Artificial Intelligence, Decision Sup-port Systems, Information Systems Analysisand Specification, Internet Computing, Elec-tronic Commerce, Human Factors and Enter-prise Architecture. ICEIS 2019 will be held inconjunction with ENASE 2019, GISTAM 2019and FEMIB 2019.
2018 IEEE/WIC/ACM InternationalConference on Web IntelligenceSantiago, Chile, December 3-6, 2018webintelligence2018.comWeb Intelligence (WI) aims to achieve amulti-disciplinary balance between researchadvances in the fields of collective intelli-gence, data science, human-centric comput-ing, knowledge management, and networkscience. It is committed to addressing re-search that deepens the understanding ofcomputational, logical, cognitive, physical aswell as business and social foundations of the
Copyright c© 2018 by the author(s).
future Web, and enables the development andapplication of intelligent technologies. WI’18features high-quality, original research papersand real-world applications in all theoreticaland technological areas that make up the fieldof WI. WI’18 welcomes research, applicationas well as Industry/Demo-Track paper sub-missions. Tutorial, Workshop and Special-Session proposals and papers are also wel-come.
14th ACM/IEEE InternationalConference on Human-RobotInteractionDaegu, Korea, March 11-14, 2019humanrobotinteraction.org/2019HRI 2019 is the 14th annual conference forbasic and applied human-robot interaction re-search. Researchers from across the worldattend and submit their best work to HRI to ex-change ideas about the latest theories, tech-nology, data, and videos furthering the state-of- the-art in human-robot interaction. Eachyear, the HRI Conference highlights a particu-lar area through a theme. The theme of HRI2019 is “Collaborative HRI”. The HRI confer-ence is a highly selective annual internationalconference that aims to showcase the verybest interdisciplinary and multidisciplinary re-search in human-robot interaction with rootsin and broad participation from communitiesthat include but not limited to robotics, human-computer interaction, human factors, artificialintelligence, engineering, and social and be-havioral sciences.
11th International Joint Conference onBiomedical Engineering Systems andTechnologiesPrague, Czech Republic, February 22-24,2019www.biostec.orgThe purpose of BIOSTEC is to bring togetherresearchers and practitioners, including en-gineers, biologists, health professionals andinformatics/computer scientists, interested in
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both theoretical advances and applications ofinformation systems, artificial intelligence, sig-nal processing, electronics and other engi-neering tools in knowledge areas related to bi-ology and medicine. BIOSTEC is composedof five co-located conferences, each special-ized in a different knowledge area. BIOSTEC2019 will be held in conjunction with MOD-ELSWARD 2019 and ICISSP 2019. Regis-tration to BIOSTEC allows free access to theMODELSWARD and ICISSP conferences (asa non-speaker).
Michael Rovatsos isthe Conference Coordi-nation Officer for ACMSIGAI, and a facultymember at the Univer-sity of Edinburgh. Hisresearch is in multiagentsystems and human-friendly AI. Contact him [email protected].
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Conference ReportsMichael Rovatsos (University of Edinburgh; [email protected])DOI: 10.1145/3299758.3299763
This section features brief reports from recentevents sponsored or run in cooperation withACM SIGAI.
The 5th international Workshop onSensor-based Activity Recognitionand Interaction (iWOAR 2018)Berlin, Germany, September 20-21, 2018www.iwoar.org/2018This conference-like workshop was initiatedand organized by the Fraunhofer IGD and theUniversity of Rostock. It offers scientists, inter-ested parties, and users in the area of sensor-based activity recognition and interaction thepossibility to an exchange of experiences anda presentation of best-practice examples, aswell as technical and scientific results. Theworkshop focuses on technologies for humanactivity recognition and interaction via iner-tial sensors (accelerometers, gyroscopes etc.)and their scientific applications. In this year’sedition of iWOAR there were 28 submissions,and the program committee chairs decided toaccept 15 papers, resulting in an overall ac-ceptance rate of 54%. For the first time atiWOAR, we invited 5 Posters, which were alsopeer-reviewed. Although the majority of au-thors are based in Germany, there were alsosubmissions from Austria, Denmark, Greece,India, Japan, New Zealand, Spain, Sweden,Switzerland, Turkey, and USA.
The 31st International Conference onIndustrial, Engineering and OtherApplications of Applied IntelligentSystems (IEA/AIE-2018)Montreal, Canada, June 25–28, 2018ieaaie2018.encs.concordia.caIEA/AIE-2018 was held at Concordia Univer-sity in Montreal, Canada this year. As inpast years, the conference was sponsoredby the International Society of Applied In-telligence (ISAI), held in cooperation withAAAI, SIGAI/ACM, and several other inter-national organizations. The conference pro-
Copyright c© 2018 by the author(s).
vides a medium for presenting and exchang-ing new scientific research ideas and techno-logical achievements accomplished by the in-ternational community in applied intelligence.IEA/AIE 2018 received 146 submissions fromCanada along with 44 other countries. 64 pa-pers were selected for oral presentation at theconference and included in the related pro-ceedings published by Springer in the LectureNotes in Artificial Intelligence (LNCS/LNAI)series. In addition to the papers acceptedat the main track, 22 papers were selected(from the papers submitted directly to the spe-cial session chairs) for presentation at thefollowing four special sessions and for inclu-sion in the proceedings: Artificial Intelligence,Law and Justice Track, Data Science, Privacy,and Security Track, Intelligent Systems Ap-proaches in Information Extraction Track, andInternet of Things and Ubiquitous Computingand Big Data Track.
The 15th International Conference onInformatics in Control, Automation andRobotics (ICINCO 2018)Porto, Portugal, July 29-31, 2018www.icinco.org/?y=2018ICINCO 2018 was held on Porto from 29thto 31st July, 2018, and was sponsored bythe Institute for Systems and Technologies ofInformation, Control and Communication (IN-STICC). ICINCO 2018 was also organizedin cooperation with the ACM SIGAI, INNS,AAAI, Euromicro, Associacao Portuguesa deControlo Automatico, euRobotics AISBL, So-ciedade Portuguesa de Robotica, SociedadeBrasileira de Automatica and the Robotics So-ciety of Japan. It was also technically co-sponsored by International Federation of Au-tomatic Control (IFAC) and IEEE Robotics& Automation Society. ICINCO received209 paper submissions from 40 countries,22.49% of which were published and pre-sented as full papers. Four invited talkswere delivered by internationally distinguishedspeakers, namely Keith Clark (Imperial Col-lege London), Christian Schlette (Univer-
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sity of Southern Denmark), and Bruno Sicil-iano (University of Naples Federico II). Ad-ditionally, a “Best Paper Award”, a “BestStudent Paper Award” and a “Best PosterAward” was conferred at the conferencevenue. More information can be found atwww.icinco.org/PreviousAwards.aspx.
The 20th International Conference onEnterprise Information Systems (ICEIS2018)Funchal, Portugal, March 21-24, 2018www.iceis.org/?y=2018ICEIS 2018 (20th International Conferenceon Enterprise Information Systems) was heldon Funchal, Madeira, Portugal from 21-24March, 2018. It was sponsored by the Insti-tute for Systems and Technologies of Informa-tion, Control and Communication (INSTICC).ICEIS 2018 was also organized in coopera-tion with the ACM SIGMIS, ACM SIGAI, ACMSIGCHI, AAAI, and SWIM (the IEICE SpecialInterest Group on Software Interprise Mod-elling).
ICEIS received 242 paper submissions from45 countries. To evaluate each submission,a double blind paper review was performedby the Program Committee. After a strin-gent selection process, 18% of the paperswere accepted for publication and presentedas full papers. Four invited talks were de-livered by internationally distinguished speak-ers: Alexander Brodsky (George Mason Uni-versity), Plamen Angelov (Lancaster Univer-sity), Salvatore Distefano (Universita degliStudi di Messina), and David Aveiro (Univer-sity of Madeira / Madeira-ITI).
The conference also awarded a “Best PaperAward”, a “Best Student Paper Award” anda “Best Poster Award”, which were conferredat the conference. More information can befound at: www.iceis.org/PreviousAwards.aspx
The 10th International Conference onAgents and Artificial Intelligence(ICAART 2018)Funchal, Portugal, January 16-18, 2018www.icaart.org/?y=2018ICAART 2018 was held on Funchal, Madeira- Portugal, from January 16 to 18, 2018. Itwas sponsored by the Institute for Systems
and Technologies of Information, Control andCommunication with the Madeira InteractiveTechnologies Institute (MITI) as a local part-ner. The conference was also technicallyco-sponsored by IEEE Computational Intelli-gence Society. The conference was organizedin cooperation with the ACM SIGAI, the Por-tuguese Association for Artificial Intelligence,Associazione Italiana per l’Intelligenza Artifi-ciale, the IberoAmerican Society of ArtificialIntelligence, European Society for Fuzzy Logicand Technology, the Asociacion Espanolapara la Inteligencia Artificial, the InternationalFuzzy Systems Association, European As-sociation for Artifical Intelligence, and AAAI.ICAART received 161 paper submissions from34 countries, of which 27.95% were acceptedas full papers. Four invited talks were de-livered by internationally distinguished speak-ers: Luc Steels (ICREA and UPF Barcelona),Virginia Dignum (Delft University of Technol-ogy), Eduard Hovy (CMU), and Luıs Antunes,Universidade de Lisboa, Portugal. A “Best Pa-per Award”, a “Best Student Paper Award” anda “Best Poster Award” were conferred at theconference venue. More information can befound at www.icaart.org/PreviousAwards.aspx
Michael Rovatsos is theConference CoordinationOfficer for ACM SIGAI,and a faculty memberof the School of Infor-matics at the Universityof Edinburgh, UK. Hisresearch is in multiagentsystems and human-friendly AI. Contact him at
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AI Education Matters: A Modular Approach to AI Ethics EducationHeidi Furey (Manhattan College; [email protected])Fred Martin (University of Massachusetts Lowell; fred [email protected])DOI: 10.1145/3299758.3299764
Introduction
In this column, we introduce our Model AIAssignment, A Module on Ethical Thinkingabout Autonomous Vehicles in an AI Course,and more broadly introduce a conversation onethics education in AI education.
Why Ethics in an AI Course?
Recognition of the need for ethics education inthe engineering-related disciplines goes backat least a hundred years (Layton Jr, 1986), butit’s only been since the 1990s that expecta-tions for ethics education have been adoptedby accreditation bodies (Stephan, 1999).
The use of artificial intelligence and machinelearning has become increasingly pervasive inour society, and this is accompanied by greatlyexpanding interest in the ethical considera-tions regarding their use. A crucial event wasProPublica’s 2016 report investigating the useof AI tools by judges in criminal courts for de-termining the nature and lengths of sentencesfor convicts (Angwin, Larson, Mattu, & Kirch-ner, 2016). The article made a compellingcase that the commercial software (which isin widespread use and employs secret algo-rithms) is racially biased.
International standards bodies are also tack-ling issues related to the ethical use of AItechniques, and specifically, the use of au-tonomous vehicles. The USA published a Na-tional Artificial Intelligence Research and De-velopment (NAIRD) Strategic Plan, and theEU published a report, “Recommendationsto EU Commission on Civil Law Rules onRobotics” (Martin & Makoundou, 2017).
Broadly, there is deep concern about the in-creasingly wide-reaching societal impact of AIapproaches. It is urgent that our students areready to think through the implications of theirwork, and make ethical choices.
Copyright c© 2018 by the author(s).
Why A Modular Approach?
Here we are presenting a modular approach:a way of incorporating an introductory lessonabout ethics into a one-semester AI course.Our module introduces students to the objec-tivist framework, and opens a specific conver-sation about the ethics of self-driving cars.
The modular approach is easily integrated intoa single course. If the course is popular (or re-quired), it reaches a large portion (or all) ofthe student population. Most importantly, stu-dents can connect the specific AI ideas theyare learning to their ethical implications.
The limitations of the modular approach aremostly related to its short duration—there isonly so much that can be accomplished withonly one week of instruction.
A modular approach would be complementarywith a whole-semester course on ethical think-ing. Doing both would be more effective thanonly one or the other.
The Model AI Assignment
In our Module on Ethical Thinking aboutAutonomous Vehicles in an AI Course, weshared a set of resources for faculty use:
• Two days of lecture, in-class exercises, anddiscussion, introducing Utilitarianism andthe Trolley Problem.
• A requirement that the course final projectpaper includes a discussion of the ethicalimplications of the project idea.
• A question on the final examination assess-ing students’ understanding of the TrolleyProblem.
These materials are elaborated in (Furey &Martin, 2018); here, we add further reflec-tions and share more resources for introduc-ing ethics to AI students.
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Reflections on Ethics Teaching
One challenge to incorporating ethics into anAI course is helping students recognize thestructure of ethical problems and their solu-tions. The field of ethics is both complex andfar-ranging. Because of this, it can be difficultto meet this challenge within the space of anAI course without getting too far a field of thestandard course material. With this concernin mind, we selected a topic that could serveas an example both of an ethical problem andethical problem solving: the ethics of algorithmdevelopment for autonomous vehicles.
In the module, students were first introducedto the connection between ethical algorithmsfor autonomous vehicles and a classic eth-ical dilemma: the Trolley Problem. After-word, students were guided through a work-sheet driven group exercise designed to fos-ter discussion and debate on the topic. Thisdiscussion helped prepare students to eval-uate the potential benefits and shortcomingsof an intuitive solution to ethical problems—Utilitarianism. Finally, students were offeredexamples of how one might construct a solu-tion to these problems and challenged to con-tinue thinking about the issue.
Thoughts on Implementation
The Trolley Problem presents a seeming in-tractable ethical dilemma — one in whichevery solution comes with an ethical cost.One benefit of exposing students to a some-what eccentric philosophical example is thatstudents become familiar with a key ethicalproblem-solving tool — the use of “thoughtexperiment” — highly idealized hypotheticalcases designed to test ethical theories andto isolate relevant moral variables. Anotherbenefit is that students come to understandthe complex nature of ethical dilemmas, andto recognize that solutions to such problemsare rarely straightforward and may perhapsbe equally complex. Too often, students whoare unfamiliar with ethical problem solving re-sist thinking about ethical dilemmas becausethe answers appear “unknowable.” Here, it isuseful to draw parallels between difficult moralquestions and difficult technical questions, re-minding them that that complexity does notnecessarily equal intractability.
It is useful to give them some general back-ground in the field of ethics. For instance, It isimportant for students to recognize that thereare different sorts of questions that one mightask regarding human behavior, only some offall under the domain of ethical inquiry. Ethi-cists, as opposed to psychologists or soci-ologist, are interested in what people oughtmorally do to apart from what they in fact door why they do it.
Other Resources
Burton et al.’s “Ethical Considerations in Ar-tificial Intelligence Courses” (2017) providesan in-depth introduction to this conversation,including case studies and resource links.These authors also contribute the idea of us-ing science fiction to engage students in think-ing through ethical considerations (Burton,Goldsmith, & Mattei, 2015).
For a short video introduction to some ethicsissues in AI, see Atlantic Magazine’s MoralCode: The Ethics of AI.
For a variety of AI ethics resources includingresearch, symposia, workshops, and reports,visit the AI Now Institute at New York Univer-sity.
The AI Ethics Lab is a virtual organization that“brings together researchers and practitionersfrom various disciplines to detect and solve is-sues related to ethical design in AI.”
Several articles from popular media addressthe challenges of introducing AI ethics into theclassroom. For instance, see (Tugend, 2018)and (Holmes, 2018).
To date, more research has been done in en-gineering ethics pedagogy than in AI ethicspedagogy. For this reason, it can be use-ful to look for resources in engineering ethics.For a problem-solving approach to ethics in-struction, see (Whitbeck, 1996). For a briefoverview of some of the major ethical theoriesalong with a discussion benefits and difficul-ties of teaching ethical theory, see (Bouville,2008). For an article on teaching higher-orderethical concepts in engineering, see (Haws,2004). For an example of an alternative tostand-alone ethics instruction in engineering,see (Riley, Davis, Jackson, & Maciukenas,2009).
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References
Angwin, J., Larson, J., Mattu, S., & Kirchner, L.(2016, May). Machine bias: There’s soft-ware used across the country to predictfuture criminals. And it’s biased againstblacks. ProPublica, 23.
Bouville, M. (2008). On using ethical theoriesto teach engineering ethics. Science andEngineering Ethics, 14(1), 111–120.
Burton, E., Goldsmith, J., Koenig, S.,Kuipers, B., Mattei, N., & Walsh, T.(2017). Ethical considerations in artifi-cial intelligence courses. arXiv preprintarXiv:1701.07769.
Burton, E., Goldsmith, J., & Mattei, N. (2015).Teaching AI ethics using science fiction.In Aaai workshop: Ai and ethics.
Furey, H., & Martin, F. (2018). Introducing eth-ical thinking about autonomous vehiclesinto an AI course. In AAAI-2018.
Haws, D. R. (2004). The importance of meta-ethics in engineering education. Scienceand Engineering Ethics, 10(2), 204–210.
Holmes, W. (2018). The ethics of artificial in-telligence in education. University Busi-ness.
Layton Jr, E. T. (1986). The revolt of the engi-neers. social responsibility and the amer-ican engineering profession. ERIC.
Martin, C. D., & Makoundou, T. T. (2017). Tak-ing the high road ethics by design in AI.ACM Inroads, 8(4), 35–37.
Riley, K., Davis, M., Jackson, A. C., &Maciukenas, J. (2009, March). ”ethics inthe details”: Communicating engineeringethics via micro-insertion. IEEE Trans-actions on Professional Communication,52(1), 95-108. doi: 10.1109/TPC.2008.2012286
Stephan, K. D. (1999). A survey of ethics-related instruction in U.S. engineeringprograms. Journal of Engineering Edu-cation, 88(4), 459-464.
Tugend, A. (2018). Colleges grapple withteaching the technology and ethics of A.I.New York Times.
Whitbeck, C. (1996). Ethics as design: Do-ing justice to moral problems. HastingsCenter Report , 26(3), 9–16.
Heidi Furey is an As-sistant Professor ofPhilosophy and Directorof the Ethics Center atat Manhattan College.Furey researches appliedethics and ethical peda-gogy. Her current projectsinclude work on the ethicsof autonomous vehicles.
Fred Martin is Profes-sor of Computer Scienceand Associate Dean forStudent Success in theKennedy College of Sci-ences at the Universityof Massachusetts Low-ell. Martin develops noveltechnologies for CS and
data science education, particularly for K–12.
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AI Policy MattersLarry Medsker (George Washington University; [email protected])DOI: 10.1145/3299758.3299765
Abstract
AI Policy is a regular column in AI Mattersfeaturing summaries and commentary basedon postings that appear twice a month in theAI Matters blog (https://sigai.acm.org/aimatters/blog/). Selected posts are summarized in is-sues of AI Matters.
IntroductionThe SIGAI Public Policy goals are to• promote discussion of policies related to AI
through posts in the AI Matters blog on the1st and 15th of each month,
• help identify external groups with commoninterests in AI Public Policy,
• encourage SIGAI members to partner inpolicy initiatives with these organizations,and
• disseminate public policy ideas to the SIGAImembership through articles in the newslet-ter.
I welcome everyone to make blog commentsso we can develop a rich knowledge base ofinformation and ideas representing the SIGAImembers.
AI Appointments
The Computing Community Consortium(CCC) announced a new initiative to createa Roadmap for Artificial Intelligence. SIGAI’sYolanda Gil (University of Southern Californiaand President-Elect of AAAI) will work withBart Selman (Cornell University) to lead theeffort. The initiative will support the U.S. Ad-ministration’s efforts in this area and involveacademic and industrial researchers to helpmap a course for needed research in AI. Theywill hold a series of workshops in 2018 and2019 to produce the Roadmap by Spring of2019.
Ed Felten, Princeton Professor of ComputerScience and Public Affairs, has been con-firmed by the U.S. Senate to be a member ofthe U.S. Privacy and Civil Liberties Oversight
Copyright c© 2018 by the author(s).
Board, a bipartisan agency within the execu-tive branch. He will serve as a part-time mem-ber of the board while continuing his teachingand research at Princeton. The five-personboard is charged with evaluating and advisingon executive branch anti-terrorism measureswith respect to privacy and civil liberties. It isa very important issue, Felten said. Federalagencies, in the course of doing national se-curity work, have access to a lot of data aboutpeople and they do intercept data. Its impor-tant to make sure they are doing those thingsin the way they should and not overstepping.Felten added that the board has the authorityto review programs that require secrecy. Thepublic has limited visibility into some of theseprograms, Felten said. The board’s job is tolook out for the public interest.
FTC Hearings on AI
On November 13 and 14, the Federal TradeCommission (FTC) held the seventh hearingin its series of nine planned Hearings on Com-petition and Consumer Protection in the 21stCentury. From the FTC: ”The hearing will ex-amine competition and consumer protectionissues associated with the use of algorithms,artificial intelligence, and predictive analyticsin business decisions and conduct. See de-tailed agenda. The record of that proceed-ing will be open until mid-February. To furtherits consideration of these issues, the agencyseeks public comment on the questions, andit welcomes input on other related topics notspecifically listed in the 25 questions.” See theagenda and more information in the press re-lease. Comments can be submitted online nolater than February 15, 2019.
AI Safety By Design
Policymakers need to think of AI and Au-tonomous Systems (AI/AS) as always need-ing varying degrees of the human role (hy-brid human/machine systems). Understand-ing the potential and limitations of combiningtechnologies and humans is important for re-
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alistic policymaking. A key element, along withaccurate forecasts of the changes in technol-ogy, is the safety of AI/AS-Human products asdiscussed in the IEEE report Ethically AlignedDesign, which is subtitled “A Vision for Prior-itizing Human Wellbeing with Artificial Intelli-gence and Autonomous Systems”, and BenShneidermans excellent summary and com-ments on the report as well as the YouTubevideo of his Turing Institute Lecture on “Algo-rithmic Accountability: Design for Safety”.
In Shneidermans proposal for a National Al-gorithms Safety Board, he writes What mighthelp are traditional forms of independent over-sight that use knowledgeable people whohave powerful tools to anticipate, monitor, andretrospectively review operations of vital na-tional services. The three forms of inde-pendent oversight that have been used inthe past by industry and governmentsplanningoversight, continuous monitoring by knowl-edgeable review boards using advanced soft-ware, and a retrospective analysis of disaster-sprovide guidance for responsible technologyleaders and concerned policy makers. Con-sidering all three forms of oversight could leadto policies that prevent inadequate designs, bi-ased outcomes, or criminal actions.
Efforts to provide safety by design includework at Google on Human-Centered MachineLearning and a general human-centered ap-proach “that foregrounds responsible AI prac-tices and products that work well for all peo-ple and contexts. These values of responsibleand inclusive AI are at the core of the AutoMLsuite of machine learning products ”. Fur-ther work is needed to systemize and enforcegood practices in human-centered AI designand development, including algorithmic trans-parency and guidance for selection of unbi-ased data used in machine learning systems.
Legal AI
AI is impacting law and policy issues as botha tool and a subject area. Advances in AI pro-vide tools for carrying out legal work in busi-ness and government, and the use of AI in allparts of society is creating new demands andchallenges for the legal profession.
Lawyers and AI Tools: In a recent study, “20top US corporate lawyers with decades of ex-
perience in corporate law and contract reviewwere pitted against an AI. ”Their task wasto spot issues in five Non-Disclosure Agree-ments (NDAs), which are a contractual ba-sis for most business deals.” The LawGeexAI system attempted correct identification ofbasic legal principles in contracts The re-sults suggest that AI systems can producehigher accuracy in shorter times comparedto lawyers. As with other areas of AI appli-cations, issues include trust in automation tomake skilled legal decisions, safety in usingAI systems, and impacts on the workforce ofthe future. For legal work, AI systems poten-tially reduce the time needed for high-volumeand low-risk contracts and give lawyers moretime to work on less mundane work. Policiesshould focus on automation where possibleand safe, and the AI for legal work is anotherexample of the need for collaborative roles forhuman and AI systems.
AI Impact on Litigation: Litigation is emergingin all parts of society related to the use of AI.Understanding the nature of adaptive AI sys-tems can be crucial for fact-finders and diffi-cult to explain to non-experts. Smart policy-making needs to make clear the liability is-sues and ethics in cases involving the useof AI technology. Artificial Intelligence andthe Role of Expert Witnesses in AI Litigationby Dani Alexis Ryskamp, writing for The Ex-pert Institute, discusses artificial intelligencein civil claims and the role of expert witnessesin elucidating the complexities of the technol-ogy in the context of litigation. “Over the pastfew decades, everything from motor vehiclesto household appliances has become morecomplex and, in many cases, artificial intelli-gence only adds to that complexity. For end-users of AI products, determining what wentwrong and whose negligence was responsiblecan be bafflingly complex. Experts retainedin AI cases typically come from fields likecomputer or mechanical engineering, informa-tion systems, data analysis, robotics, and pro-gramming. They may specialize in questionssurrounding hardware, software, 3D-printing,biomechanics, Bayesian logic, e-commerce,or other disciplines. The European Com-mission recently considered the question ofwhether to give legal status to certain robots.One of the issues weighed in the decision in-volved legal liability: if an AI-based robot or
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system, acting autonomously, injures a per-son, who is liable?”
Pew Research Report
Pew Research Center recently released a re-port “Public Attitudes Toward Computer Algo-rithms”, by Aaron Smith, on Americans con-cerns about fairness and effectiveness in mak-ing important decisions. The report says “Thisskepticism spans several dimensions. At abroad level, 58 percent of Americans feel thatcomputer programs will always reflect somelevel of human bias although 40 percent thinkthese programs can be designed in a way thatis bias-free. And in various contexts, the pub-lic worries that these tools might violate pri-vacy, fail to capture the nuance of complexsituations, or simply put the people they areevaluating in an unfair situation. Public per-ceptions of algorithmic decision-making arealso often highly contextual the survey pre-sented respondents with four different scenar-ios in which computers make decisions by col-lecting and analyzing large quantities of pub-lic and private data. Each of these scenarioswere based on real-world examples of algo-rithmic decision-making and included: a per-sonal finance score used to offer consumersdeals or discounts; a criminal risk assess-ment of people up for parole; an automatedresume screening program for job applicants;and a computer-based analysis of job inter-views. The survey also included questionsabout the content that users are exposed toon social media platforms as a way to gaugeopinions of more consumer-facing algorithms.”
EasyChair Policy Issue
We are revisiting an issue raised last June in-volving data privacy for SIGAI and ACM mem-bers using EasyChair to submit articles forpublication, including the AI Matters Newslet-ter. As part of entering a new submissionthrough EasyChair, the following message ap-pears: “AI Matters, 2014-present, is an ACMconference. The age and gender fields areadded by ACM. By providing the informationrequested, you will help ACM to better under-stand where it stands in terms of diversity tobe able to focus on areas of improvement. It ismandatory for the submitting author (but youcan select prefer not to submit) and it is de-
sirable that you fill it out for all authors. Thisinformation will be deleted from EasyChair af-ter the conference.”
We recommend that to evaluate the likelihoodof privacy protection, one should pay atten-tion to the EasyChair Terms of Service, par-ticularly Section 6 “Use of Personal Informa-tion” to assess better the level of risk if ourmembers choose to enter personal informa-tion. Your Public Policy Officer recommendsfurther discussion among the SIGAI member-ship about requesting changes in ACM policy.Please send your views on this topic to SIGAIofficers and contribute comments to the policyblog.
Larry Medsker is Re-search Professor ofPhysics and was foundingdirector of the Data Sci-ence graduate program atThe George WashingtonUniversity. Dr. Medskeris a former Dean of theSiena College School ofScience, and Professor
in Computer Science and in Physics. Hisresearch in AI includes work on artificialneural networks, hybrid intelligent systems,and the impacts of AI on society and policy.a.He is the Public Policy Officer for the ACMSIGAI.
ahttp://humac-web.org/
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Epochs of an AI CosmologyCameron Hughes (Northeast Ohio ACM Chair; [email protected])Tracey Hughes (Northeast Ohio ACM Secretary; [email protected])DOI: 10.1145/3299758.3299868
Epochs and Hype Cycles
We began the discussion about the educa-tional benefits to the general public of a stan-dard AI Cosmology in Volume 4 Issue 2 of “AIMatters”. But the mere notion of such a stan-dard immediately raises lots of questions. Inthis column, we only focus on a very narrowset of those questions: First and foremost:Is there an AI Cosmology? If in fact the no-tion of cosmology applies to AI, is there onlyone valid AI Cosmology or are there compet-ing valid cosmologies? If there is only onevalid cosmology, what is its structure? How farcan we take an AI Cosmology analogy? Likeour Universe, did AI have the equivalent of aBig Bang? Is the field or structure of AI ex-panding or contracting? In an interview withNikola Danaylov, podcaster of Singularity.FM,the late Marvin Minsky1, one of the early AIpioneers, suggested that the evolution of AI inthe 21st century maybe be contracting or evenstalled! We posit that an AI Cosmology wouldhelp to educate the general public about ourresearch and work, and its impact on society.Internally, it would help us to fix the objects,structure, and dynamics of the field. A stan-dard cosmological model would help us all dis-tinguish spurious AI mythos, pseudo science,hype, and fake news from the genuine arti-cle. A true cosmology of Artificial Intelligencewould help us fix its origins, understand its tra-jectory, and predict its fate.
We are currently at the beginning of what wecould consider the epoch of Machine Learn-ing. Of course how the field will ultimatelymeasure the epochs of AI remains an openquestion. But dividing the history of AI intoepochs might help us better understand thecosmology of AI a little better. For instance,we could say that before the epoch of MachineLearning was the epoch of Expert Systems,and prior to that, the epochs of Cybernetics
Copyright c© 2018 by the author(s).1https://www.youtube.com/watch?v=
3PdxQbOvAlI
and Mathematical Logic Machines. We couldask ourselves what causes one AI epoch tostart and another to end? We might look at anAI epoch from the points of view of (research,investment, utilization) funding, media, indus-try, and social impact. For critical or perhapseven cynical purposes, we might ask how orif AI epochs correspond or correlate to tech-nology hype cycles. Figure 1 shows how ageneric tech hype cycle curve.
Figure 1: A Generic Tech Hype Curve.
Notice that a hype cycle reaches a peak whereexpectations are unrealistically high, the pub-lic is at its height of misinformation, and claimsof technologys applications are inflated. Fol-lowing the curve in Figure 1 is the realiza-tion that the inflated claims are not comingtrue, funding and investment decreases, andthen the public becomes disillusioned. Is itthe case that AI epochs happen to coincidewith AI hype cycles? Are AI hype cycles typi-cally components of epochs? Are they one inthe same? One of our current interests withrespect to the general public’s vulnerability toAI hype cycles, how much do technical termi-nology misnomers, misconstrued AI concepts,and ill-defined AI vocabulary contribute? In
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Figure 2, we show our first rough draft of AIsEpochs we’ve discussed so far.
Figure 2: Rough Draft of AI’s Epochs.
In Figure 2, each AI epoch has a timeline andwithin each epoch, there has been a hype cy-cle. For now we conjecture that hype cyclesand epochs are not the same. Epochs startprior to the hype cycle and continues after thehype cycle is over.
Machine Learning and Back toCybernetics
We are in the Machine Learning epoch. In AIMatters Volume 4 Issue 2, we talked aboutthe age of Expert Systems. But before AImanifested itself in the form of Expert Sys-tems, Cybernetics represented the promise ofArtificial Intelligence. In June 1975, our ownSIGART Newsletter No. 52 contained an arti-cle by Edward M. Riseman entitled “AAI ANDBRAIN THEORY AT THE UNIV. OF MAS-SACHUSETTS”. Riseman defines Cybernet-ics accordingly:
At the University of Massachusetts atAmherst, we use the name to describethe study of Artificial Intelligence (AI) andBrain Theory (BT). At the University ofMassachusetts in 1975, the Computer Sci-ence and Information Science Program wasroughly divided into three major areas: Com-puter Systems, Theory of Computation andCybernetics.
In Riseman’s SIGART article, he describesthe 1974-1975 graduate courses in the Fun-damentals of Cybernetics as including:
• Computational Cybernetics• Artificial Intelligence• Neurocybernetics of the Cerebral Cortex
• Scene analysis• Natural vs. Artificial Intelligence• Theorem Proving• Implementing A Question-Answering sys-
tems
AI Magazine Volume 3 Number 1 (1982) re-ports that AI and Brain Theory at UMASS wasstill intermingling the notions of AI and Cyber-netics.
Our program in AI is part of the larger depart-mental focal area of Cybernetics which inte-grates both AI and Brain Theory (BT). Our re-search also draws upon a new and expandinginterdepartmental program in Cognitive Sci-ence that brings together researchers in Cy-bernetics, Linguistics, Philosophy, and Psy-chology.
The same fervor that Pop Culture now hasfor Machine learning was once had for ExpertSystems. Prior to Expert Systems, feedbackcommunication and control in animals andmachines was all the craze and we were in theepoch of Cybernetics. It was just like the par-allels between the AI/Machine Learning andthe AI/Expert System explosions. Cybernet-ics was the talk of the town complete with sci-entific breakthroughs, industrial innovations,massive social change and a strong doseof Cyber-Techno-Hype. In 1969, GeorgesBoulanger, the president of the InternationalAssociation of Cybernetics noted that “To thegeneral public cybernetics conjures up visionsof some fantastic world of the future peopledby robots and electronic brains” (Boulanger,1969). Cybernetics represented the embod-iment, incarnation, goals, aspirations, andfunding targets of some of the same subjectmatter that is reserved for AI/Machine Learn-ing. Cybernetics was a staple of science fic-tion and a fad among artists, musicians, andintellectuals in the 1950s and 1960s. Thesefacts are well documented in Ronald Kline’s2015 tour de force book “The Cybernetics Mo-ment” (Kline, 2015) where he painstakinglycaptures the history of Cybernetics, Informa-tion Theory, and the early AI Ethos. Upon aclose reading of Kline’s “The Cybernetics Mo-ment”, one can almost see how the ArtificialIntelligence baton would eventually pass fromCybernetics to Expert Systems.
The intersection between the actual artifacts
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of AI research and the general publics un-derstanding and expectations with regard tothose artifacts can be perilous. It appearsthat this has been the case for each of theAI epochs! As AI researchers, educators,and practitioners, we have an obligation tominimize (as best we can) the misconstruc-tions, misunderstandings, and misrepresenta-tions of our work and our field. At Ctest Lab-oratories, we are positing the notion of de-vising a “Standard Model” for an AI Cosmol-ogy that would standardize the structure, tax-onomy, and ontology in a form that is suit-able for consumption by early college STEMprograms, high schools, and the general pub-lic. The moniker AI remains for much of thegeneral public a reference to vague, ambigu-ous, futuristic, even threatening subject mat-ter. This was also the case for the monikerCybernetics. But after all what is cybernetics?Or rather what is it not, for paradoxically themore people talk about cybernetics the lessthey seem to agree on a definition, GeorgeBoulanger 1969 (Boulanger, 1969).
In this column, we would like to instigate aconversation with our fellow SIGAI memberson this notion of a standard model for AIs Cos-mology. So far we’ve offered conjectured no-tions of standardized epochs of AI, AI HypeCycles, standard AI taxonomies, and a stan-dard AI domain ontology as a starting point.What do we really mean by “Artificial Intel-ligence”? If the evolution of Artificial Intelli-gence can be divided into epochs, where arewe now, and what was the first one? Canwe understand the evolution of Artificial Intelli-gence, its technologies and applications in thecontext of a AI cosmological standard model?If we can construct an AI cosmological stan-dard model, can we represent it in way that issuitable for consumption by the general pub-lic? If the epoch of Cybernetics preceded theepoch of Expert Systems, was there an AIepoch that preceded Cybernetics? We’ll tryto fill in more of the timeline in the next article.
References
Kline, R. (2015). The Cybernetics Moment.Baltimore, MD, USA: John Hopkins UniversityPress.
Boulanger, G.R. (1969) Prologue: What is Cy-bernetics?, in Survey of Cybernetics: A Trib-
ute to Dr. Norbert Weiner, ed. J. Rose. Lon-don, England. Iliffe Books.
Cameron Hughes is acomputer and robot pro-grammer. He is a Soft-ware Epistemologist atCtest Laboratories wherehe is currently working onA.I.M. (Alternative Intelli-gence for Machines) andA.I.R (Alternative Intelli-gence for Robots) tech-nologies. Cameron isthe lead AI Engineer forthe Knowledge Group atAdvanced Software Con-
struction Inc. He is a member of the advisoryboard for the NREF (National Robotics Edu-cation Foundation) and the Oak Hill RoboticsMakerspace. He is the project leader of thetechnical team for the NEOACM CSI/CLUERobotics Challenge and regularly organizesand directs robot programming workshops forvarying robot platforms. Cameron Hughesis the co-author of many books and blogson software development and Artificial Intelli-gence.
Tracey Hughes is a soft-ware and epistemic visu-alization engineer at CtestLaboratories. She isthe lead designer for theMIND, TAMI, and NO-FAQS projects that uti-lize epistemic visualiza-tion. Tracey is also amember of the advisoryboard for the NREF (Na-tional Robotics EducationFoundation) and the OakHill Robotics Makerspace.
She is the lead researcher of the technicalteam for the NEOACM CSI/CLUE RoboticsChallenge. Tracey Hughes is the co-authorwith Cameron Hughes of many books on soft-ware development and Artificial Intelligence.
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Artificial Intelligence and Jobs of the Future: Adaptability Is Keyfor Human EvolutionSudarshan Sreeram (Vidya Mandir Senior Secondary School, Mylapore, Chennai - 04, India;[email protected])DOI: 10.1145/3299758.3300060
Humans, the most intelligent species onplanet Earth, have always found a way toadapt to their dynamic environment and sur-vive in a consistent manner. We have madetremendous progress in evolving from primi-tive men and women in small, dreary cavesto modern men and women in large, bustlingcities. Our passionate strive to survive andaffinity to adapt is similar to that shown bymosquitoes; regardless of the continuous de-velopment and massive deployment of in-sect repellent products, these undeniably irk-ing insects, which cause a plethora of life-threatening diseases, always make a strikingcomeback (Stanczyk, Brookfield, Field, & Lo-gan, 2013).
Humans have a natural tendency to be preoc-cupied with what interests us the most. Welack the ability to not think of anything, evenfor a second. Boredom is not an option for hu-mans; this is evidenced by a research exper-iment conducted in 2014 by Timothy Wilson,a social psychologist professor at the Univer-sity of Virginia, Charlottesville (Wilson et al.,2014). The results of this research found thathumans would go to the extent of shockingthemselves with small jolts of electricity, whenlocked alone in a lab, just to keep themselvesoccupied. Our minds were built to be awareof the world around us and engage in actionsand decisions that shape it. Thus, it is not pos-sible to stop continuously flowing thought pro-cesses (Whitehead, 2014).
Our rich and vivid history may be describedas a continuously flowing river, which does notheed to a specific, predictable pattern. How-ever, the river does take similar looking turnsas it flows. Applying this hypothetical case toreal world history, we see that major events,be it global revolutions, wars, famines, naturaldisasters, and even plagues, do recur, though,and at irregular intervals.
The time interval between two successive
Copyright c© 2018 by the author(s).
events is influenced by two factors our mind-set and our reaction towards change. Forexample, consider an article published byColumbia University on the psychology ofgullible mindsets (Valhouli, n.d.). According tothis publication, a fourteen-year-old boy con-vinced forty-three of fifty people to support aban on water. The boy referred to water asdihydrogen monoxide, the chemical name ofwater, in a petition that was circulated throughthe internet. An important factor to consideris the way this petition was framed to influ-ence human minds; he claimed that dihydro-gen monoxide was a harmful chemical thatwas found in tumors of cancer patients. Sim-ilar convincing sentences use widely knownterms such as sweating, vomiting, erosion,and lethal to lure an uninformed reader. Thereader takes the authenticity of the providedinformation for granted without checking factsor running background checks on its source.The information is then dispersed through ca-sual conversations and discussions to a widernetwork, leading to the general public be-ing falsely informed. Therefore, it is evidentthat our mindsets are one of the most gullibleand volatile entities on our planet; widespreadcontroversies, futuristic sci-fi movies, factu-ally inaccurate data, and popularized opinionsof highly influential representatives do a verygood job at molding it.
Change-events are stimuli for human soci-eties. When the change is for the better andprovides visible benefits, the reaction is mostlikely positive. For example, the establishmentof independence or democracy in a country,the creation of new job opportunities, etc. Ina similar way, when the change is disruptiveand removes certain key defining aspects ofhuman life, the reaction is most likely negative.For example, the increase in income taxes andfuel prices or the decrease in job satisfactionleading to lack of peaceful life (Rohani & Pa-hazri, 2018).
Industrial revolutions, dubbed as the perma-
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nent markers of change, have had monumen-tal impacts, both positive and negative, on thelives of humans. An industrial revolution canbe thought of as a steering wheel of a car thatrepresents the human civilization; this car hasmade three sharp turns and is on a straightroad, looking forward to making a fourth turn.
The first turn, which had the largest radius,witnessed the urbanization and industrializa-tion of several rural societies as well as thedeployment of steam engines, which played amajor role in the development of transporta-tion technologies during the 18th and 19thcenturies. The second turn saw the growthof industrial centers around the world rightbefore the first world war and the introduc-tion of mass-produced electrical appliances,which included technological advancementsthat would change the world forever. The thirdturn, which started during the early 1980s,took the car onto the digital highway; the dig-ital revolution and the boom of the internetmade it possible for almost everyone in theworld to stay connected. The fourth turn, themost anticipated of them all, deals with signifi-cant advancements in the fields of 3D printing(Kyle, 2018), bio-circuits (Prox, Smith, Holl,Chehade, & Guo, 2018), quantum comput-ing (Chong, 2018), robotics, IoT (Agiwal, Sax-ena, & Roy, 2018), nanotechnology (Alvarez,Chan, Elimelech, Halas, & Villagran, 2018),renewable energy technologies, self-drivingvehicle technologies (Bansal & Kockelman,2018), and finally, the most controversial andpopular of them all Artificial Intelligence (AI)(Lu, Li, Chen, Kim, & Serikawa, 2018).
Ever since its inception in 1956, when JohnMcCarthy held a conference on the subject(McCarthy, Minsky, Rochester, & Shannon,1955), Artificial Intelligence has always caughtthe imagination of those who take it uponthemselves to predict the outline of future so-cieties (Barrat, 2015). It is undoubtedly aninspiring and captivating field; however, it ismet with a great deal of controversies andmisconceptions regarding its purpose and in-tention. Some research suggests controver-sial ways in which it would influence humanlife while others see the potential for a futurewhere AI systems complement human soci-eties. An oversimplified and partially misun-derstood influence of AI is its effective takeover of human-centralized jobs in the future.
The reason behind these misconceptions andcontroversies is due to a misunderstanding ofone word Technology. Technology is a life-altering word that has found its place in hu-man society. Over the past few decades, ithas been integrating itself into all aspects ofhuman life, and now, it is integral to our dailylifestyles. Our connection with technology hasgrown so deep that we cannot even fathom analternate timeline in which humans live withoutit. Although widely debated, its intended pur-pose is to make human life simple and easy. Ithelps us achieve milestones and immenselyspeeds up the progress of our society as awhole.
We have witnessed the rapid transformationof our landscapes and interests as technologymolds the shape of our future. It functions asa tool of change that teaches us how to adaptand evolve to meet the requirements of futuresocieties. Today, some of us question theserequirements and are doubtful of what this fu-ture might hold. It is easier and faster for hu-mans to find flaws in an idea or a concept thanit is to understand its true value.
Humans have shown varied reactions to theuse of automation technology and roboticsin several industrial areas (Knight, 2018).Consider the widely discussed transition ofthe manufacturing industry from recruitingskilled human workers to employing auto-mated robotic technologies. The first flaw hu-mans see with this transition is the massiveunemployment of skilled laborers. What wefail to see is that this transition not only pre-vents us from working in hazardous conditionsbut also reduces a companys expenditure inmanufacturing processes. In addition, the endproduct is of a much higher quality due to re-duction in human errors, and the time takenby the different processes is significantly re-duced, thereby increasing production rates tomeet the demand. Yet, despite all these ad-vantages, we still consider the loss of jobs asa prominent result.
Humans have always developed a notion ofresistance and anxiety over advanced devicesand technologies, be it self-driving cars or arti-ficial intelligence. Even in the 1980s, the termcomputerphobia was widely circulated in mag-azines, newspapers, and psychology studies(Lafrance, 2015). The term was mainly used
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to address a persons fear of being threat-ened and replaced by a computer. In addi-tion, people felt hostile in the presence of acomputer. Eventually the presence of comput-ers in our daily lives grew exponentially. Thisis quite synonymous to what is going on inthe present day with artificial intelligence tech-nologies. The general trend marks a peakperiod of hype and gradually settles into thebooks of history.
The Gartner hype cycle (Hype Cycle Re-search Methodology , n.d.) for emerging tech-nologies in 2018 depicts the presence of arti-ficial intelligence on two of the five regions inthe hype cycle graph innovation trigger andpeak of inflated expectations. In addition, thegraph also predicts that these various tech-nologies under AI may reach the plateau ofproductivity a period of mainstream adapta-tion in roughly ten or more years (Panetta,2018).
Ever since its creation, a computer was taskedwith replicating and efficiently performing hu-man tasks. It is just human notion that when acomputer is able to do something new, we re-gain those feelings of anxiety and resistance.People, who are not properly informed of aspecific technology, are easily persuaded bythe depictions of AI as a threat. So, what isArtificial Intelligence?
Todays AI is a system of complex algorithmsthat do an exceptional job at processing andanalyzing large volumes of data; it is a skillthat humans lack due to the volatility and com-putational limitations of their memory systems.AI systems are purpose built for executingspecific tasks, so there are several severe lim-itations on what it can accomplish; to put it insimple terms, AI is not yet anywhere near theability to freely think as we do.
Super intelligence or true AI, on the otherhand, is a form that current AI technolo-gies could possibly take in the future as wegain a deeper knowledge regarding its fun-damental concept the working of the hu-man brain (Hassabis, Kumaran, Summerfield,& Botvinick, 2017). This future is not com-ing anytime soon; currently, there is no oneon our planet who actually understands howsuper intelligence works (Byttner, 2017). Itsprogress is most entirely dependent on humanbrain research, which is currently progress-
ing at a snails pace. Marlene Behrmann, acognitive neuroscience professor at CarnegieMellon University, claimed that neuroscientistsonly have a primitive understanding of humanbrain functions despite decades of research(Gornall, 2014). Thus, when humans them-selves have not yet understood the completeworking of their brains, it is improbable to cre-ate an intelligent system that can replicate it.
AI systems are excellent at performing repet-itive tasks, which is evidenced by theirpurpose-built nature. It can automate almostany system that is repetitive or predictable.Thus, it is not surprising to see the results ofAI technologies from Google and IBM (Hiner,2018; Russell, 2017; Best, n.d.). Even if AIwere to advance to match the human intellect,their only way of physically interacting with thisworld is through robotic bodies. Even the high-est quality of robots are prone to failures, giventhat their developments should be cost effec-tive. Regardless, robotic technicians will berequired to diagnose and address any techni-cal issues. Thus, there will always be spacefor humans.
Moreover, educational institutions around theworld are offering courses on robotic systemsto advance the technical skills required to workin this field. In fact, there is pressure onthe educational sector to teach students tocode from a young age (Barone, 2017). Sev-eral technology giants, including Apple, arebringing forward their support to educate chil-dren on coding practices (Education - Teach-ing Code, n.d.). Since the world is movingforward with technology as its backbone, thepeople living in it are expected to be well in-formed of it in a transparent manner.
As for the role of Artificial Intelligence (AI)in jobs of the future, AI systems would en-gage in cooperation with humans; these intel-ligent systems would provide humans with rel-evant data and suggestions to solve a particu-lar task. There is a clear line that distinguishesjobs and tasks when considering the potentialof current AI technologies (Pring, 2018). A jobis a simple term for the human state of beingpreoccupied with multiple tasks while benefit-ing from a source of income; whereas, a taskis a piece of work that acts as a subset of ajob. It is a definite possibility that in the future,AI systems would complement the human job
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workload rather than completely making it ob-solete.
It is evident and inevitable, though, that newfields of interest to humans will rise as thedepths of our knowledge in existing fields in-crease. Our future is influenced by a greatdeal of factors, AI being just one of them. Con-trary to the notion that AI would make us un-employed in the future, this intelligence would,in actuality, boost job growth; though, the vari-ety of jobs offered in the future may not be thesame as what is offered in the present day.For example, humans may expect titles suchas organ fabricator, commercial space pilot,alternate energy consultant, and trash engi-neer (9 Top Jobs in 2030: Future Skills YouNeed To Learn Now , n.d.). Prior to advance-ments in AI, it would have been hard to imag-ine job titles such as Machine Learning Devel-oper or Artificial Intelligence Specialist. Usingthe same analogy, we may expect several newjob titles in the future as technology evolves.
As jobs evolve over time so do the tools weuse. This is evidenced by the history of art;during the 1800s, people had the time and pa-tience to sit for days, months, or even yearsto complete a single painting, made entirelyby hand. Today, we take aid of digital drawingprograms and highly precise graphics pen dis-plays or tablets to speed up that process andexpress our thoughts as they flow. Though,this example does bring into question thevalue of art and the presence of human touch,which, in my opinion, would fade as we moveinto the future. However, we do not surren-der our creativity and intellectual abilities, butexpress the same in a different form that con-sumes less time and effort. Artists of the 19thcentury had brushes and canvases, artists ofthe 21st century have graphics tablets anddigital canvases, and artists of the future mayhave technologies that combine the use of AIand Augmented Reality (AR), supported bythe human brain, to provide everyone with anartistic toolset. This shows that creativity isa human characteristic that cannot simply dis-appear in the presence of artificial intelligence.
A research paper from Oxford university (Frey& Osborne, 2017), which claims that AI wouldtake over human jobs of the future, bases itsresults on assuming that all jobs are repeti-tive and predictable (Surowiecki, 2017). This
is not true in the real world as its dynamicshold innumerable factors. Consider the casewhere a robotic machine breaks down in alarge scale factory. A human technician is re-quired at this point for analyzing the situationand factoring multiple variables and carryingout an in-depth root cause analysis. Humansare better at decision making as they have alot more input and background knowledge towork with and consider, which are not just de-rived from text book sources (Why humanslearn faster than AI-for now., 2018). Criticalsituations such as fire emergencies and natu-ral disaster management, where even robotsarent effective, do require human presence(Why humans learn faster than AI-for now.,2018). Unless super intelligence is reached,AI is nothing all by itself apart from being afollower of specific instructions given by hu-mans. To reach a future where AI would sup-port job growth and cooperate with humans,three fundamental principles must be estab-lished: transparency in actions and decisions,restriction on information collection and ac-cess of data sources, and foundation for long-term reliability and trust.
In the far future, we may reach a state whenartificial intelligence will prioritize and reorga-nize our skillsets; humans will think but not do.The creation of objects and physical comple-tion of tasks will be taken care by humanoidspowered by intelligent AI, as shown in filmadaptations of popular sci-fi novels. Contraryto what is shown in these films, humanoidsare less likely to turn against humanity as thethree principles, coupled with safety protocolsand other measures, would be enforced uponthem. Humans would also have to make surethat the AI or AI based systems cannot finda way to bypass these security measures andgain access to unauthorized sections of dataand services. In the same way, the generalpublic should also be restricted from gainingprivileges to access the core of the AI system.This would keep intelligence away from peo-ple who would utilize it for social misconduct,disinformation, and to promote corruption.
With these security measures in mind, hu-mans can look forward to a future filled withcooperation and responsibility. In addition,with heavy investments in nuclear fusion andspace mining research (James, 2018), hu-mans may soon develop their first zero pollu-
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tion, sustainable energy resource. This, alongwith further advancements in AI, would heav-ily influence the industries including the man-ufacturing and agriculture sectors. This wouldeventually reduce global resource prices andreach a stage wherein everyone would haveaccess to resources. The same holds true forglobal inflation, where we may observe stableand controlled prices.
It is a social responsibility of humans to cre-ate a balance with ecology by which robotsbacked up by AI would contribute to the hu-man community and its wellbeing; food gen-eration, disease prevention, and medical careshould be given the first priority. This wouldhelp us ensure a balance and mutual trust be-tween AI based technology and humans.
For now, humans should focus on utilizingthese intelligent platforms to solve global chal-lenges such and global warming, climatechange, and resource management. Further-more, humans would need to be educatedon the potential of such technological devel-opments and refrain from exaggerating futureoutcomes to a point where it alters the ex-pectations of general public on our future withAI. As change is inevitable, humans wouldlearn to adapt and live with AI powered hu-manoids and robots in a harmonious manner.This would be accomplished through shed-ding our highly opinionated self and embrac-ing AI based technologies as our way forwardinto the future.
In summary, humans will continue to see fur-ther advancements in the field of technol-ogy and experience its impacts on their lives.In these situations, humans are required tochange their mindsets, be informed of thecase, and use their ability to adapt to the en-vironment. Artificial Intelligence would play aprime role in future societies. However, de-spite widespread controversies, AI systems ofthe future would be cooperative and collabo-rative with humans, providing them with thenecessary data and suggestions to speed upthe completion of job related tasks. This mayhold true only if strict security measures aretaken to ensure that these intelligent systemsare not utilized for the wrong purposes. In con-clusion, humans may look forward to an inter-esting future where adaptability is key for hu-man evolution.
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Sudarshan Sreeramis a grade XII studentat Vidya Mandir SeniorSecondary School, My-lapore, Chennai, India.He is a dedicated stu-dent researcher and haspublished two technicalpapers at internationalconferences: 18th IEEEEEEIC, Palermo, Italyand 2018 IEEE SMCJunior, Miyazaki, Japan.Sudarshan is an Apple
WWDC18 Scholar and the TUNZA Eco-Generation (Samsung-UNEP) RegionalAmbassador to India. His wish is to become amature researcher in the future and contributeto the field of computing. In addition, he isdetermined to advance his education to adoctoral level.
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