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Illustration: Eniola Odetunde/Axios

The idea that AI can replicate or amplify human prejudice, once argued mostly at the field's fringes, has been thoroughly absorbed into its mainstream: Every major tech company now makes the necessary noise about "AI ethics."

Yes, but: A critical split divides AI reformers. On one side are the bias-fixers, who believe the systems can be purged of prejudice with a bit more math. (Big Tech is largely in this camp.) On the other side are the bias-blockers, who argue that AI has no place at all in some high-stakes decisions.

Why it matters: This debate will define the future of the controversial AI systems that help determine people's fates through hiring, underwriting, policing and bail-setting.

What's happening: Despite the rise of the bias-blockers in 2019, the bias-fixers remain the orthodoxy.

  • A recent New York Times op-ed laid out the prevailing argument in its headline "Biased algorithms are easier to fix than biased people."
  • "Discrimination by algorithm can be more readily discovered and more easily fixed," says UChicago professor Sendhil Mullainathan in the piece. Yann LeCun, Facebook's head of AI, tweeted approvingly: "Bias in data can be fixed."
  • But the op-ed was met with plenty of resistance.

The other side: At the top academic conference for AI this week, Abeba Birhane of University College Dublin presented the opposing view.

  • Birhane's key point: "This tool that I'm developing, is it even necessary in the first place?"
  • She gave classic examples of potentially dangerous algorithms, like one that claimed to determine a person's sexuality from a photo of their face, and another that tried to guess a person's ethnicity.
  • "[Bias] is not a problem we can solve with maths because the very idea of bias really needs much broader thinking," Birhane tells Axios.

The big picture: In a recent essay, Frank Pasquale, a UMD law professor who studies AI, calls this a new wave of algorithmic accountability that looks beyond technical fixes toward fundamental questions about economic and social inequality.

  • "There's definitely still resistance around it," says Rachel Thomas, a University of San Francisco professor. "A lot of people are getting the message about bias but are not yet thinking about justice."
  • "This is uncomfortable for people who come up through computer science in academia, who spend most of their lives in the abstract world," says Emily M. Bender, a University of Washington professor. Bender argued in an essay last week that some technical research just shouldn't be done.

The bottom line: Technology can help root out some biases in AI systems. But this rising movement is pushing experts to look past the math to consider how their inventions will be used beyond the lab.

  • "AI researchers need to start from the beginning of the study to look at where algorithms are being applied on the ground," says Kate Crawford, co-founder of NYU's AI Now Institute.
  • "Rather than thinking about them as abstract technical problems, we have to see them as deep social interventions."

The impact: Despite a flood of money and politics propelling AI forward, some researchers, companies and voters hit pause this year.

  • Most visibly, campaigns to ban facial recognition technology succeeded in San Francisco, Oakland and Somerville, Mass. This week, nearby Brookline banned it, too.
  • One potential outcome: freezes or restrictions on other controversial uses of AI. This scenario scares tech companies, who prefer to send plumbers in to repair buggy systems rather than to rip out the pipes entirely.

But the question at the core of the debate is whether a fairness fix even exists.

The swelling backlash says it doesn't — especially when companies and researchers ask machines to do the impossible, like guess someone's emotions by analyzing facial expressions, or predict future crime based on skewed data.

  • "It's anti-scientific to imagine that an algorithm can solve a problem that humans can't," says Cathy O'Neil, an auditor of AI systems.
  • These applications are "AI snake oil," argues Princeton professor Arvind Narayanan in a presentation that went viral on nerd Twitter recently.
  • The main offenders are AI systems meant to predict social outcomes, like job performance or recidivism. "These problems are hard because we can’t predict the future," Narayanan writes. "That should be common sense. But we seem to have decided to suspend common sense when AI is involved."

This blowback's spark was a 2017 research project from MIT's Joy Buolamwini. She found that major facial recognition systems struggled to identify female and darker-toned faces.

What's next: Companies are tightening access to their AI algorithms, invoking intellectual property protections to avoid sharing details about how their systems arrive at critical decisions.

  • "The real problem is we citizens have no power to even examine or scrutinize these algorithms," says O'Neil. "They're being used by private actors for commercial gain."

Go deeper

1 hour ago - World

U.S. will give Russians written response to NATO demands, Blinken says

Blinken and Lavrov shake hands in Geneva. Photo: Russian Foreign Ministry / Handout/Anadolu Agency via Getty Images

Secretary of State Antony Blinken confirmed after a meeting with his Russian counterpart on Friday that the U.S. will provide written answers to Russia's security demands next week.

Why it matters: Russia claims to be waiting for "concrete answers" to its demands that NATO rule out further expansion and roll back its presence in eastern Europe before deciding its next steps on Ukraine. But the U.S. and NATO have called those proposals "non-starters," and Friday's meeting offered no breakthroughs, so it's unclear how written answers might change the equation.

More surprises await scientists at Antarctica's "Doomsday Glacier"

Cliffs along the edge of the Thwaites Ice Shelf in West Antarctica. Photo: James Yungel/NASA

Researchers like David Holland, an atmospheric scientist at New York University, are in a race to understand the fate of a massive glacier in West Antarctica that has earned a disquieting nickname: "The Doomsday Glacier."

Why it matters: Studies show the Thwaites Glacier (its official name) could already be on an irreversible course to melt during the next several decades to centuries, freeing up enough inland ice to raise global sea levels by at least several feet.

Updated 4 hours ago - Health

The case for Operation Warp Speed 2.0

Illustration: Annelise Capossela/Axios

Omicron's blitz around the world has underscored the need for a new arsenal of COVID vaccines and therapeutics, experts say — and that may require an effort akin to Operation Warp Speed 2.0.

Why it matters: The virus will continue to evolve, potentially in a way that further escapes vaccine protection, and the best way to prevent more global disruptions to everyday life is to have tools ready to combat whatever comes next.