Rodriguez, M., Motyl, M., & Schroeder, J. (2026). From social media to empathic artificial intelligence: Applying past lessons to future technologies. In Cameron, C. D., & Perry, A. (Eds.) Empathy and Artificial Intelligence: Challenges, Advances, and Ethical Considerations. Cambridge University Press.

• Short Summary: This chapter synthesizes two decades of research on social media to extract lessons for new forms of social technology like GenAI. It recommends future research on social technology consider three sources of heterogeneity — 1) the type and features of the technology, 2) how it is used, and 3) who is using it — to better understand how tech will affect social life.

• This chapter leverages the Neely Social Media Index and Neely Technology Indices. Interested readers can see the links for more information. 

Angrisani, M., Casanova, M., Fast, N. J., Narang, J., & Schroeder, J. (2026). Gaps in large language model awareness, usage, and perceptions in the United States: Evidence from a nationally representative longitudinal survey. [PNAS Nexus Link]

• Short Summary: Across two survey waves spanning one year with more than 12,000 nationally representative U.S. adults, we observed marked gaps in LLM usage: groups more likely to use LLMs included men, younger adults, those with college education and higher incomes, individuals in more analytical occupations (e.g., STEM), Democratic-leaning respondents, and those with above-median cognitive ability, internet literacy, and openness to experience. These usage gaps are not declining over time; some are getting larger.

• Data available on the Understanding America Survey website: https://uasdata.usc.edu/index.php (datasets UAS 574 and UAS 607)

• Analysis code

• Appendix

• Updated figures with third wave of data (2023, 2024, and 2025 waves)