AI Now 2017 Report - AI Now Institute

AI Now 2017 Report - AI Now Institute 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 

 
 
 
 
 
 
 
 
 
 
 
 

 
 

 
 
 
 
 

 

 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 With key recommendations for the field of artificial intelligence ## AI Now Institute Announces 2017 Report With Key Recommendations for the Field of Artificial Intelligence

 *Second annual report calls for an end to black box predictive systems in core public institutions like the criminal justice system, and outlines specific approaches needed to address bias in AI and related technologies*

 New York, NY – October 18, 2017 – The AI Now Institute, an interdisciplinary research center based at New York University, announced today the publication of its [second annual research report](https://ainowinstitute.org/AI_Now_2017_Report.pdf). In advance of AI Now’s official launch in November, the 2017 report surveys the current use of AI across core domains, along with the challenges that the rapid introduction of these technologies are presenting. It also provides a set of ten core recommendations to guide future research and accountability mechanisms. The report focuses on key impact areas, including labor and automation, bias and inclusion, rights and liberties, and ethics and governance.

 “The field of artificial intelligence is developing rapidly, and promises to help address some of the biggest challenges we face as a society,” said Kate Crawford, cofounder of AI Now and one of the lead authors of the report. “But the reason we founded the AI Now Institute is that we urgently need more research into the real-world implications of the adoption of AI and related technologies in our most sensitive social institutions. People are already being affected by these systems, be it while at school, looking for a job, reading news online, or interacting with the courts. With this report, we’re taking stock of the progress so far and the biggest emerging challenges that can guide our future research on the social implications of AI.”

 The 2017 report comes at a time when AI technologies are being introduced in critical areas like criminal justice, finance, education, and the workplace. And the consequences of incomplete or biased systems can be very real. A team of journalists and technologists at Propublica demonstrated how an algorithm used by courts and law enforcement to predict recidivism in criminal defendants was measurably biased against African Americans. In a different setting, a study at the University of Pittsburgh Medical Center observed that an AI system used to triage pneumonia patients was missing a major risk factor for severe complications. And there are many other high stakes domains where these systems are currently being used, without being tested and assessed for bias and inaccuracy. Indeed, standardized methods for conducting such testing are yet to be developed.

 The 2017 report calls for all core public institutions – such as those responsible for criminal j

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