Last Week in AI #91

AI's replication crisis, government-sponsored medical AI, and more!

Mini Briefs

AI is wrestling with a replication crisis

It's well-known that AI research is plagued by problems of transparency and reproducibility, but the issue has received particular attention recently. For example, a Google Health paper in Nature involving breast cancer detection drew ire because it included so little information about code and testing that "the study amounted to nothing more than a promotion of proprietary tech." While reproducibility is considered a bedrock of scientific research, few AI studies are replicated because of the field's ambition to move forward and produce new studies. In addition to academic incentives and a lack of transparency, differential access to resources and money required to conduct experiments put the ability to produce state-of-the-art research in the hands of large companies.

But there's hope for mitigating some of these issues: reproducibility challenges, in which participants reproduce AI papers, have drawn many participants, while more and more researchers submit code with their papers at top conferences. While publication norms are being fought for by many researchers, the long-term impact of such practices depends on the direction AI takes--if large models like GPT-3 stay trendy, many will be unable to participate in cutting-edge research. There is no question that industry research labs will continue to dominate AI research, but concerned researchers maintain that democratizing participation will be key.

The US Government Will Pay Doctors to Use These AI Algorithms

Medical AI research is continuing to take off, and beyond convincing US government actors like the FDA of its effectiveness in improving outcomes, we're seeing the government begin to use taxpayer dollars to fund the adoption of medical AI:

The US Centers for Medicare & Medicaid Services (CMS) recently said it would pay for use of two AI systems: one that can diagnose a complication of diabetes that causes blindness, and another that alerts a specialist when a brain scan suggests a patient has suffered a stroke.

But the implications are wider than for just Medicare and Medicaid patients: such investment could drive increased adoption of AI in healthcare. This new offer isn't the first: CMS began paying for the use of San Francisco startup's AI software, ContaCT, which alerts a neurosurgeon when algorithms see evidence in a CT scan that a patient has a blood clot in their brain. Speeding up diagnosis and treatment can reduce a patient's disabilities and recovery time. This government willingness to pay for the use of AI tools may not only increase adoption, but also encourage other companies working on medical AI products. While some technologies might not yet be economically feasible, payments like the ones CMS has begun to make could help such technologies propagate much faster.




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