Social media platforms are too often understood as monoliths with clear priorities. Instead, we analyze them as complex organizations torn between starkly different justifications of their missions. Focusing on the case of Meta, we inductively analyze the company’s public materials and identify three evaluative logics that shape the platform’s decisions: an engagement logic, a public debate logic, and a wellbeing logic. There are clear trade-offs between these logics, which often result in internal conflicts between teams and departments in charge of these different priorities. We examine recent examples showing how Meta rotates between logics in its decision-making, though the goal of engagement dominates in internal negotiations. We outline how this framework can be applied to other social media platforms such as TikTok, Reddit, and X. We discuss the ramifications of our findings for the study of online harms, exclusion, and extraction.

Seed grants will fund 29 research teams pursuing novel research ideas across disciplines.

Few young people with type 1 diabetes (T1D) meet glucose targets. Continuous glucose monitoring improves glycemia, but access is not equitable. We prospectively assessed the impact of a systematic and equitable digital-health-team-based care program implementing tighter glucose targets (HbA1c < 7%), early technology use (continuous glucose monitoring starts <1 month after diagnosis) and remote patient monitoring on glycemia in young people with newly diagnosed T1D enrolled in the Teamwork, Targets, Technology, and Tight Control (4T Study 1). Primary outcome was HbA1c change from 4 to 12 months after diagnosis; the secondary outcome was achieving the HbA1c targets. The 4T Study 1 cohort (36.8% Hispanic and 35.3% publicly insured) had a mean HbA1c of 6.58%, 64% with HbA1c < 7% and mean time in the range (70-180 mg dl-1) of 68% at 1 year after diagnosis. Clinical implementation of the 4T Study 1 met the prespecified primary outcome and improved glycemia without unexpected serious adverse events. The strategies in the 4T Study 1 can be used to implement systematic and equitable care for individuals with T1D and translate to care for other chronic diseases.

"The 2026 Stanford AI Index Report, released this month, highlights a sharp increase in AI adoption in medicine. It notes a significant rise in AI uses for clinical documentation, medical imaging, and diagnostic reasoning. That growth may improve efficiency. But it also expands the attack surface for public health if mis-deployed."

Using three large-scale longitudinal datasets collected from a cohort of university students over the span of 3 years (total N = 2,896 participants; ecological momentary assessments = 129,414), we found that engagement in meaningful social interactions with peers was associated with lower momentary loneliness and greater affective well-being. We also examined the role of four contextual factors (interaction partners, communication channels, places, and co-occurring activities) in explaining the relationships between meaningful social interactions and momentary well-being. Across samples, we found (a) participants reported experiencing greater loneliness and lower affective well-being after engaging in meaningful social interaction via computer-mediated channels (and via direct messaging in particular), compared to face-to-face, and (b) participants reported experiencing lower affective well-being after engaging in meaningful social interactions while dining and studying or working, compared to while resting. Taken together, our findings provide insight into the relationships between meaningful social interactions, momentary well-being, and contextual factors.

Sha Sajadieh, AI Index Lead, comments on HAI's 2026 AI Index findings.