San Francisco’s board of supervisors took a significant step this week when it voted to ban the use of facial recognition software for law enforcement purposes, but such measures by themselves won’t resolve the ethical issues surrounding surveillance enabled by artificial intelligence.
At least those are the first impressions from a trio of experts focusing on the social implications of AI’s rapid rise.
David Danks, a philosophy professor at Carnegie Mellon University, said he hasn’t had a chance to delve into the details of the municipal legislation, which was endorsed on Tuesday and will come up for a second procedural vote next week. And he said “this is a case where the details are going to matter.”
” ‘Law enforcement purposes’ in the sense of arresting somebody on the basis of a facial recognition match is this sort of extreme, obvious case,” Danks told GeekWire after participating in a panel discussion on AI ethics at Seattle University on Tuesday night. “But what if it’s monitoring members of a group, where it’s not that I know that this is this individual, but I know that this is a member of a community where I’ve uploaded 20 faces?”
Danks said facial recognition has attracted a lot of criticism from researchers and privacy advocates — in part because authorities have been using the technology to track millions of Muslims in northwest China, in part because of reports of race- and gender-related software fails, and in part because the face is such a big part of a person’s public identity.
“But there’s actually a whole bunch of other things that have similar properties to facial recognition that are equally pernicious, but don’t generate the same visceral reaction,” Cornell University information scientist Solon Barocas said.
Margaret Mitchell, a senior scientist at Google Research and Machine Intelligence, said examples could include analyzing a person’s walking gait, or the cadence of a person’s speech.
“Machine learning is going to discover a whole bunch of new ways,” Barocas said.
The leading companies in AI and machine learning say they’re trying to self-regulate the AI products they put out. “Google’s been working on being more transparent about things like what the values are,” Mitchell said. “One of my favorite ones, because it directly applies to everything that I do, is to avoid reinforcing unfair bias.”
Microsoft, meanwhile, has an internal ethics committee that reviews proposed applications for its AI software — and occasionally turns down what it sees as unethical use cases. Facial recognition is a top-level concern.
But is self-regulation enough? Last December, Microsoft President Brad Smith said the federal government should enact laws governing facial recognition technology, with a focus on issues such as consent, third-party testing, fairness and privacy.
Should the government create a Federal AI Commission?
“I’m not quite sure what that would look like,” Danks said. “It seems to me sort of like having a ‘Federal Internal Combustion Engine Commission.’ What matters is how these technologies are put to use, not the technology in isolation.”
In his view, regulating AI doesn’t necessarily require creating a whole new bureaucracy.
“In many domains, actually, there already are the regulatory powers to do this,” he said. “What is lacking is the technical expertise at the regulatory agencies to understand how to exercise those powers to regulate some new technology or some company. There are going to be things that fall through the gaps.”