Showing posts with label denying accountability. Show all posts
Showing posts with label denying accountability. Show all posts

Wednesday, March 6, 2019

Making a path to ethical, socially-beneficial artificial intelligence, MIT News, March 5, 2019

School of Humanities, Arts, and Social Sciences, MIT News; Making a path to ethical, socially-beneficial artificial intelligence

Leaders from government, philanthropy, academia, and industry say collaboration is key to make sure artificial intelligence serves the public good.

"Many speakers at the three-day celebration, which was held on Feb. 26-28, called for an approach to education, research, and tool-making that combines collective knowledge from the technology, humanities, arts, and social science fields, throwing the double-edged promise of the new machine age into stark relief...

The final panel was “Computing for the People: Ethics and AI,” moderated by New York Timescolumnist Thomas Friedman. In a conversation afterward, Nobles also emphasized that the goal of the new college is to advance computation and to give all students a greater “awareness of the larger political, social context in which we’re all living.” That is the MIT vision for developing “bilinguals” — engineers, scholars, professionals, civic leaders, and policymakers who have both superb technical expertise and an understanding of complex societal issues gained from study in the humanities, arts, and social science fields.  

The perils of speed and limited perspective
 
The five panelists on “Computing for the People” — representing industry, academia, government, and philanthropy — contributed particulars to the vision of a society infused with those bilinguals, and attested to the perils posed by an overly-swift integration of advanced computing into all domains of modern existence.
 
"I think of AI as jetpacks and blindfolds that will send us careening in whatever direction we're already headed," said Joi Ito, director of the MIT Media Lab. "It's going to make us more powerful but not necessarily more wise."


The key problem, according to Ito, is that machine learning and AI have to date been exclusively the province of engineers, who tend to talk only with each other. This means they can deny accountability when their work proves socially, politically, or economically destructive. "Asked to explain their code, technological people say: ‘We're just technical people, we don't deal with racial or political problems,’" Ito said."