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Illustration: Sarah Grillo/Axios
The criminal justice system has eagerly taken up AI tools for surveillance, policing and sentencing — software that can track people's faces, deploy patrols where crime appears most likely, and recommend whether to grant bail.
Kaveh reports: But these tools are often cloaked in secrecy, so that it can be impossible to judge their accuracy, or even know where and how they are being used. Critics say this opens the door to misuse and discrimination.
Driving the news: San Francisco yesterday approved the most restrictive government surveillance regulations in the U.S.
Why it matters: When poorly coded or deployed, AI systems can make huge mistakes or harm some groups more than others. But where faulty facial recognition in Snapchat might mean some people can't use a fun filter, flawed police software can land the wrong people in jail.
"You can't meaningfully build up a criminal defense, or change policies, if you don't know how these tools are being used," says Alice Xiang, a researcher at the Partnership on AI.
San Francisco will soon have its first-ever complete public list of surveillance technology currently in use, says Lee Hepner, legislative aide to San Francisco Supervisor Aaron Peskin, who introduced the measure.
The big picture: The uptake of AI in criminal justice mirrors a broad push to automate difficult or sensitive decisions, like hiring and diagnosing diseases from medical scans. But they are often implemented without proper safeguards, says Peter Eckersley, research director at the Partnership on AI.
What's next: Facial recognition is the most publicly controversial of the various AI tools governments use, and it's the one most likely to be regulated. Companies have asked the federal government to put rules in place for law enforcement use of the technology.
Illustration: Sarah Grillo/Axios
As we reported before Uber's massive IPO, the company's two business areas — ride-hailing and Uber Eats — are both experiencing slowing growth and drained coffers.
The company had a disappointing debut. And now, four days into trading, investors are still in the red — today Uber shares were trading 10% below the open price on IPO day.
Axios' Dan Primack reports: That has got to worry other money-losing "unicorns" that operate in similar sectors.
In descending order of fear factor:
The bottom line: If these companies' most recent financings were benchmarked to Uber's valuation, at least in part, then we could be in for a series of high-profile down-rounds. Or orphaned unicorns. These things have a tendency to feed on themselves.
Go deeper: Shorting Uber
Photo: Derek Berwin/Fox Photos/Getty
Several readers wrote in about our post on the U.S. intelligence community's effort to find new "superforecasters." Here is one:
If you can’t make useful predictions, you aren’t really an expert. That said, I think results like this are overstated (and I love Philip Tetlock’s work). Policymakers aren’t asking what price gold will be or even how many missile strikes will happen. Essentially that tests gambling skill, or the ability to find a central tendency among many future outcomes. That seems to me to be a more useful skill for policymakers who need to judge risk than intelligence analysts. I never saw any questions that were job relevant during previous prediction contests, at least in my field (science and technology).
Prediction in intelligence work requires identifying key drivers that policymakers can affect, or predicting really specific outcomes.
Counterargument: This work is great for impersonal epidemics, possibly to include criminal cyber at scale.— Christopher Porter, CTO, Global Cybersecurity Policy, FireEye, Reston, Va.
McDonald's in Vienna in 1980. Photo: Barbara Alper/Getty
If you're vacationing in Vienna and you lose your passport, don't panic. Just go get a Big Mac.
Erica writes: Per a new agreement with the State Department, McDonald's is becoming a quasi-U.S. Embassy. All 194 locations in Austria have been given special access to a 24-hour embassy hotline, Fast Company reports.