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This week in AI, actuality got here knocking — each for AI well being tech and semi-autonomous driving programs. IBM agreed to promote the property from its Watson Well being enterprise to funding agency Francisco Companions, following the division’s steeply declined efficiency. In the meantime, the Insurance coverage Institute for Freeway Security (IIHS), a nonprofit financed by the insurance coverage trade, introduced a brand new scores program designed to guage how nicely “partial” automation programs like Tesla’s Autopilot present protections to stop misuse.
The dual developments are emblematic of the AI trade’s perennial downside: acknowledging AI’s limitations. Slate’s Jeffrey Funk and Gary Smith do a thorough job of recapping overly optimistic AI predictions in recent times, together with Ray Kurzweil’s pronouncement that computer systems could have “human-level” intelligence and “the flexibility to inform a joke, to be humorous, to be romantic, to be loving, to be horny” by 2029.
As any skilled will verify, AI is nowhere near approaching human-level intelligence — emotional or in any other case. (Kurzweil’s new estimate is 2045.) Equally, autonomous vehicles and AI-driven well being care haven’t achieved the lofty heights futurists as soon as envisioned they might attain. It’s an essential lesson in setting expectations — the longer term isn’t straightforward to foretell, in spite of everything — but additionally an instance of how the pursuit of revenue supercharges the hype cycle. Beneath stress to indicate ROI, some well being tech and autonomous automobile corporations have collapsed underneath the load of their overpromises, as this week’s information reveals.
Driving excessive on the Watson win in opposition to Jeopardy! champion Ken Jennings, IBM launched Watson Well being in 2015, positioning the suite of AI-powersed companies as the way forward for augmented care. The corporate’s gross sales pitch was that Watson Well being may analyze reams of medical knowledge — far quicker than any human physician may, ostensibly — to generate insights that enhance well being outcomes.
IBM reportedly spent $4 billion beefing up its Watson Well being division with acquisitions, however the expertise proved to be inefficient at greatest — and dangerous at worst. A STAT report discovered that the platform usually gave poor and unsafe most cancers remedy recommendation as a result of Watson Well being’s fashions have been educated utilizing faulty, artificial medical data somewhat than actual affected person knowledge.
Watson Well being’s demise may be partially attributed to IBM CEO Arvind Krishna’s shifting priorities, however rising cynicism about AI’s well being capabilities little doubt additionally performed a task. Research have proven that almost all eye illness datasets come from sufferers in North America, Europe, and China, that means eye disease-diagnosing algorithms are much less sure to work nicely for racial teams from underrepresented international locations. An audit of a UnitedHealth Group algorithm decided that it may underestimate by half the variety of Black sufferers in want of better care. And a rising physique of labor means that pores and skin cancer-detecting algorithms are typically much less exact when used on Black sufferers, partially as a result of AI fashions are educated totally on photographs of light-skinned sufferers.
Semi-autonomous, AI-powered driving programs are coming underneath comparable scrutiny, significantly as automakers ramp up the rollout of merchandise they declare can practically drive a automobile themselves. In October 2021, Tesla was ordered to show over knowledge to the Nationwide Freeway Site visitors Security Administration as a part of an investigation into the corporate’s vehicles crashing into parked automobiles. The suspicion was that Tesla’s Autopilot was accountable — both partially or complete — for the damaging behaviors.
It’s not an unreasonable assumption. Late final yr, Tesla rolled out an replace to Autopilot with a bug that induced the automated braking system in Teslas to have interaction for no obvious cause. This induced vehicles to quickly decelerate as they traveled down the freeway, placing them vulnerable to being rear-ended.
Tesla isn’t the one vendor that’s struggled to good semi-autonomous automobile expertise. A sobering 2020 examine from the American Car Affiliation discovered that almost all semi-autonomous programs in the marketplace — together with these from Kia and BMW — bumped into issues a median of each eight miles. For instance, when encountering a disabled automobile, the programs induced a collision 66% of the time.
That brings us to this week’s information: the Insurance coverage Institute’s scores program to guage semi-autonomous programs’ security protections. The group hopes it’ll encourage automakers to create higher designs as soon as the primary set of scores, at present in growth, are issued this yr.
“The best way many of those programs function offers individuals the impression that they’re able to doing greater than they are surely,” Insurance coverage Institute analysis scientist Alexandra Mueller mentioned in an announcement. “However even when drivers perceive the restrictions of partial automation, their minds can nonetheless wander. As people, it’s more durable for us to stay vigilant once we’re watching and ready for an issue to happen than it’s once we’re doing all of the driving ourselves.”
That’s all to say that AI — whether or not self-driving or disease-diagnosing — is fallible, identical to the people who design it. Visions of a Jetsons future may be tantalizing, however when lives are at stake, historical past has proven that it’s greatest to be overly cautions.
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Senior Workers Author
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