Inaugural MIT AI Policy Congress promotes government engagement
Academics, scientists and policymakers gathered recently for the first MIT AI Policy Congress to explore how the opportunities being created by artificial intelligence can be harnessed while confronting the social challenges that could end up stalling innovation in the field, MIT News reports.
The congress featured 7 panel discussions with 25 speakers, including two former White House chiefs of staff, former cabinet secretaries, homeland security and defense policy chiefs, and leaders from industry, civil society, and academia. Opportunities AI is creating in transportation and safety, medicine, labor, criminal justice, and national security, were covered in the conversation, along with challenges including the potential for bias, and the need for transparency.
“When it comes to AI in areas of public trust, the era of moving fast and breaking everything is over,” said R. David Edelman, director of the Project on Technology, the Economy, and National Security (TENS) at the MIT Internet Policy Research Initiative (IPRI), and former Obama White House advisor.
OECD Director for Science, Technology, and Innovation Andrew Wyckoff says that AI is among the top three policy priorities for the OECD in 2019 and 2020. The congress took place alongside a two-day meeting of the OECD, which sent experts for a half-day hands-on training session in machine learning as they prepare to develop policy recommendations for the 35 countries participating in the group. The actual state of AI technology for applications such as autonomous driving was reviewed, along with the importance of accountability for different organizations, including businesses and governments.
Biometrics were specifically brought up by American Civil Liberties Union’s Massachusetts chapter Executive Director Carol Rose, who suggested that law enforcement and data scientists have to work together to stem the flow of “junk science” into the field. She also cited work by Joy Buolamwini of the MIT Media Lab on differing accuracy rates.
“Sometimes I worry we have an AI hammer looking for a nail,” Rose said.
IPRI Founding Director and MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) principal research scientist Daniel Weitzner called for continued government engagement and cross-disciplinary research at the event’s conclusion.
Researchers at MIT’s CSAIL also recently announced the development of a tool to “de-bias” training data.