AI: Project Listings and Collaborations

I recently defended my dissertation, "Computational Health Literacy Assessments: Risks, Opportunities & Future Directions" and wanted to contribute to the broader conversation around AI and public health more quickly than the pace of an academic journal article.

One key takeaway: for one communication problem you might address through AI, you will be creating a few more.

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Samuel Mendez, PhD
Harvard T.H. Chan School of Public Health
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Sharing the second post in my newsletter series on AI and Health Literacy: https://www.linkedin.com/pulse/3-data-quality-problems-deflate-ai-hype-health-samuel-mendez-phd-yi8pc

After analyzing 48,000+ health messages, I discovered 3 critical data quality problems that challenge prominent AI narratives:

Problem #1: Data redundancy killed 1/3 of our training set.
Duplicate content shrunk our dataset from 48K to 32K samples. Public health's repetitive messaging helps humans remember-but hurts AI training.

Problem #2: Even experts can disagree on "clear" standards Our trained raters struggled with consistency on certain questions for a national audience. If humans can't agree on active voice in tweets, how can AI? Deeper community engagement is key.

Problem #3: Simple tools can beat complex AI.
A basic keyword search for command verbs like "wear" or "wash" can identify calls to action, at a fraction of the cost. It won't capture every possible call to action, but it can capture those you want to promote.

The bottom line: Evidence, not industry hype, should drive our tech choices. Sometimes that means AI. Sometimes it means a simple keyword list.

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Samuel Mendez
PhD Student
Harvard T.H. Chan School of Public Health
Boston, MA United States
smendez@g.harvard.edu
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AI can improve health literacy by gradually introducing user-friendly tools that simplify complex medical language, tailor content to diverse needs, and expand access to reliable information. However, this must be done with a human-centered approach, where clinicians, educators, and patients co-design and oversee these systems. By supporting rather than replacing interpersonal communication, AI becomes a translator and enhancer of knowledge, while humans provide empathy, cultural nuance, and contextual judgment. This synergy ensures health literacy efforts remain trustworthy, personalized, and ethically grounded.

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Anas Malik Radif Alubaidi, MBChB, MSc, PgDip, Prof Dip Paeds(RCPI), FRSPH

LinkedIn: http://linkedin.com/in/anas-malik-radif-alubaidi-9516b8285
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