JASON: Artificial Intelligence for Health Care
The field of artificial intelligence is habitually susceptible to exaggerated claims and expectations. But when it comes to new applications in health care, some of those claims may prove to be valid, says a new report from the JASON scientific advisory panel.
“Overall, JASON finds that AI is beginning to play a growing role in transformative changes now underway in both health and health care, in and out of the clinical setting.”
“One can imagine a day where people could, for instance, 1) use their cell phone to check their own cancer or heart disease biomarker levels weekly to understand their own personal baseline and trends, or 2) ask a partner to take a cell-phone-based HIV test before a sexual encounter.”
Already, automated skin cancer detection programs have demonstrated performance comparable to human dermatologists.
The JASON report was requested and sponsored by the U.S. Department of Health and Human Services. See Artificial Intelligence for Health and Health Care, JSR-17-Task-002, December 2017.
Benefits aside, there are new opportunities for deception and scams, the report said.
“There is potential for the proliferation of misinformation that could cause harm or impede the adoption of AI applications for health. Websites, apps, and companies have already emerged that appear questionable based on information available.”
Fundamentally, the JASONs said, the future of AI in health care depends on access to private health data.
“The availability of and access to high quality data is critical in the development and ultimate implementation of AI applications. The existence of some such data has already proven its value in providing opportunities for the development of AI applications in medical imaging.”
“A major initiative is just beginning in the U.S. to collect a massive amount of individual health data, including social behavioral information. This is a ten year, $1.5B National Institutes of Health (NIH) Precision Medicine Initiative (PMI) project called All of Us Research Program. The goal is to develop a 1,000,000 person-plus cohort of individuals across the country willing to share their biology, lifestyle, and environment data for the purpose of research.”
But all such efforts raise knotty questions of data security and personal privacy.
“PMI has recognized from the start of this initiative that no amount of de-identification (anonymization) of the data will guarantee the privacy protection of the participants.”
Lately, the US Government has barred access by non-US researchers to a National Cancer Institute database concerning Medicare recipients, according to a story in The Lancet Oncology. See “International access to major US cancer database halted” by Bryant Furlow, January 18, 2018 (sub. req’d.).
AI’s high-stakes outputs directly shape American economic, industrial, and technological outcomes. They must not be accepted entirely on the basis of institutional faith rather than verifiable evidence.
The clearinghouse will also neutrally mediate the assignment of auditors to audits—strengthening independence, trust, and ethical governance across the AI ecosystem.
Soft law was never meant to be a permanent solution. Treating it as one, and letting the sandcastle stand in for the skyscraper indefinitely, is how we end up with a decade of voluntary commitments and no enforceable accountability to show for it.
Jobseekers, employees at smaller organizations, and local public workers need more than a weekend crash course in AI. They need practice choosing useful tasks, protecting data, testing outputs, and explaining where human judgment remains necessary.