Professor Steve Hoffman reflects on predictions for Artificial Intelligence

Steve G. HoffmanProfessor Steve G. Hoffman recently published a piece in Backchannels, the blog of the Society for Social Studies of Science. Backchannels publishes a variety of “less formal writings” on “the current and future state of the field or subfields within science and technology studies.” Professor Hoffman is an Assistant Professor of Sociology at the University of Toronto, with teaching responsibilities at the Mississauga campus. His research studies the cultural politics of knowledge production.

The blog piece is available on the Backchannels’ webpage. We have posted an excerpt here:

AI’s Prediction Problem

Steve G. Hoffman
04 July, 2017

Artificial Intelligence is finding hype again. Big money has arrived from Google, Elon Musk, and the Chinese government. Global cities like Berlin, Singapore and Toronto jockey to become development hubs for application-based machine intelligence. AlphaGo’s victories over world class Go players make splashy headlines far beyond the pages of IEEE Transactions. Yet in the shadows of the feeding frenzy, a familiar specter haunts. Bill Gates and Stephen Hawking echo the worries of doomsayer futurists by fretting over the rise of superintelligent machines that might see humanity as obsolete impediments to their algorithmic optimization.

There is a familiar formula to all this. AI has long struggled with a prediction problem, careening between promises of automating human drudgery and warnings of Promethean punishment for playing the gods. Humans have been imagining, and fearing, their thinking things for a very long time. Hephaestus built humans in his metal workshop with the help of golden assistants. Early modern era art and science are filled with brazen heads, automated musicians, and an infamous defecating duck. [2] The term “robot” came into popular use in the midst of European industrialization thanks to Karel Čapek’s play, Rossum’s Universal Robots, which chronicled the organized rebellion of mass produced factory slaves. Robot, not coincidently, is derived from the Old Church Slavonic “rabota,” which means “servitude.” Overall, then, we find thinking machines in myth and artifact built to glorify gods, to explain the mystery of life, to amuse, to serve, and to punish. They were, and are, artifacts that test the limits of technical possibility but, more importantly, provide interstitial arenas wherein social and political elites work through morality, ethics, and the modalities of hierarchical domination.

Contemporary AI was launched with a gathering of mathematicians, computer engineers, and proto-cognitive scientists at the Dartmouth Summer Workshop of 1956. The workshop proposal named the field and established an expectation that “every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” The work that followed in the wake of this workshop institutionalized a tendency toward overconfident prediction. In 1966, workshop alum and co-founder of the MIT AI Lab, Marvin Minsky, received a summer grant to hire a first-year undergraduate student, Gerald Sussman, to solve robot vision. Sussman didn’t make the deadline. Vision turned out to be one of the most difficult challenges in AI over the next four decades. The vision expert Berthold Horn has summarized, “You’ll notice that Sussman never worked in vision again.” [3]

Expectations bring blessing and curse. Horn is among the now senior figures in AI who believe that predictions were and are a mistake for the field. He once pleaded with a colleague to stop telling reporters that robots would be cleaning their house within 5 years. “You’re underestimating the time it will take,” Horn reasoned. His colleague shot back, “I don’t care. Notice that all the dates I’ve chosen were after my retirement!” [3]

Researchers at the Future of Humanity Institute at Oxford have recently stitched together a database of over 250 AI predictions offered by experts and non-experts between 1950 and 2012. Their main results yield little confidence in the forecasting abilities of their colleagues. [1]

Read the full article.


Working Paper 2016-04

The Shelf Life of a Socio-Technical Disaster: Post Fukushima Policy Change in the United States, France and Germany

Steve G. Hoffman, University of Toronto

Paul Durlak, University of Buffalo, SUNY

UT Sociology Working Paper No. 2016-04

September 2016

Keywords: disaster, Fukushima, nuclear energy, policy change, risk, technology

Full Article


How can large-scale socio-technical disasters prompt policy shifts beyond their local environment? We compare the impact of the Fukushima Daiichi nuclear power plant disaster of March 11, 2011, on subsequent American, French, and German nuclear energy policies. This paper introduces the sensitizing concept of a “shelf life” to identify mechanisms that limited the impact of this disaster in the US and France but that enabled it to travel to Germany. American and French policymakers placed symbolic distance between their nation’s nuclear infrastructure and Fukushima by framing the disaster as a contingent and technical problem to be resolved with superior safety preparation. While this technicist orientation can be found in the initial German response, its distancing effects are offset by a conjunction of three mechanisms that moved Fukushima to the center of German society and politics and ultimately created the conditions for a complete phase out of all of Germany’s nuclear power generation. This included 1) a renewables energy industry eager to move into the void left from nuclear power reduction, 2) deep cultural and socio-political affinities across the two nations that were expertly mobilized by German anti-nuclear protest organizations, and 3) the unequivocal ethical messaging produced by a high-profile national committee. Taken together, these mechanisms collapsed interpretive and cultural distance between Japanese and German nuclear infrastructures, enabling the shock of Fukushima to ripple powerfully through the German energy grid for generations to come.

University of Toronto Sociology Working Paper 2016-04

Welcome New Faculty

This year the Department of Sociology welcomes ten new faculty members into our community of scholars. This is the largest cohort of new faculty members we have seen in decades. They cover research and teaching interests ranging from classical theory to criminology and immigration studies and will help shape the character of the department in the years to come. Though housed across the three campuses, all faculty join together in contributing to the tri-campus graduate department.

Professor Ellen Berrey joins the faculty at the University of Toronto, Mississauga teaching in the area of Law and Society. She graduated with a PhD in Sociology from Northwestern University in 2008 and has previously taught at the University at Buffalo, SUNY and at the University of Denver.

Professor Irene Boeckmann is a new faculty member in Family and Demography, teaching at the St. George campus. Professor Boeckmann completed her PhD at the University of Massachusetts-Amherst in 2014 and spent 2015 as a post-doctoral fellow at the WZB Berlin Social Science Center in Germany.

Professor Emine Fidan Elcioglu brings her expertise in political sociology and immigration to the University of Toronto at Scarborough. Professor Elcioglu received her doctorate from the University of California at Berkeley in 2016.

Professor Steve G. Hoffman received his PhD at Northwestern University in 2009 and taught for several years at the University at Buffalo, SUNY before coming to the University of Toronto at Mississauga. Professor Hoffman teaches in the area of social theory and the sociology of disaster.

Professor Rachel La Touche comes to the University of Toronto at St George this year where she is teaching in the areas of research methods and inequality. She received her PhD from Indiana University-Bloomington in 2016 and has previously taught at the University of Mannheim-Germany and at the Inter-University Consortium for Political and Social Research(ICPSR) Summer Program at the University ofMichigan.

Professor Yoonkyung Lee joins the faculty at the University of Toronto, St. George. Professor Lee received her PhD at Duke University in 2006 and has previously taught at Binghamton University. Professor Lee is a political sociologist with a focus on Korean studies.

Professor Sida Liu is a new faculty member at the University of Toronto, Mississauga. Professor Liu is a specialist in the sociology of law. He received his PhD from the University of Chicago in 2009. Before coming to Toronto, Professor Liu taught at the University of Wisconsin-Madison. He is also currently a Faculty Fellow at the American Bar Foundation and a Member of the Institute for Advanced Study in Princeton.

Professor Akwasi Owusu-Bempah received his doctorate in 2014 from the Centre for Criminology and Socio-legal Studies here at the University of Toronto, Mississauga. Before coming back to Toronto, Professor Owusu-Bempah taught for a year at the Indiana University, Bloomington. Professor Owusu-Bempah is a specialist in policing and race.

Professor Kim Pernell comes to the University of Toronto, St. George with expertise in economic sociology, organizational sociology and social policy. Professor Pernell received a PhD in Sociology from Harvard in 2016.

Professor Ashley Rubin joins the faculty at the University of Toronto, Mississauga bringing expertise in the sociology of punishment and prisons. Professor Rubin received her PhD from the University of California, Berkeley in 2013 and previously taught at Florida State University.