Chaiwoo Lee Presents AI and Longevity Research for Journalist Fellows
by Adam Felts
AgeLab Research Scientist Chaiwoo Lee presented findings from an AgeLab project on AI and longevity at a fellowship retreat for journalists hosted by the National Press Foundation and sponsored by AARP.
For journalists, the fellowship website says, covering the 65-plus set no longer means focusing on assisted living and failing health. Still, older adults are often undervalued by society and underrepresented in media coverage and images due to a range of factors – including outdated stereotypes and biases.
Dr. Lee discussed the AgeLab’s study on public and expert attitudes toward AI across domains that are relevant for the aging population. She summarized three key findings from the study:
A perception gap: Experts were optimistic about consumer willingness to adopt AI-enabled technologies than consumers were themselves. Additionally, among consumers, being a millennial or of generation X, having a higher income, being employed, having a higher level of education, and being more generally technology savvy were all correlated with a greater willingness to use AI, suggesting a potential future adoption gap.
Diversity, equity, and inclusion: Experts frequently mentioned the replication of systematic biases as a potential risk of AI. If programmed conscientiously, AI could potentially negate common human biases, such as ageism in the workplace. But AI could just as well replicate and perpetuate those biases in its automated decisions.
A desire for regulation: While generally showing support for development, consumers universally agreed on a need for government regulation of AI. This finding appeared across generations and demographic groups.
Dr. Lee also suggested some topics that journalists might explore in their work about AI and longevity. She noted the importance of consumer education to increase understanding of the technology and minimize potentially dangerous confusion. She observed that, when reporting about the application of AI for older adults, one can focus on “universal” applications as well as those that are typically associated with “old age” (such as in healthcare). And finally, she spoke about the need to advocate for equitable decisionmaking in the development and application of AI early in the life of the technology.
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