Social Technology Use and Life Satisfaction in a Five-Wave Panel Study of US Adults

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Kushlev, K., Moon, K., Motyl, M., Fast, N., Schroeder, J., (2026). Social technology use and life satisfaction in a five-wave panel study of US adults. [Nature Human Behavior Link]

  • Short Summary: Using five waves of panel data from 1,966 U.S. adults tracking use of ten common social technologies over time, this study finds little credible evidence that using any of them predicts later changes in life satisfaction, or vice versa (one modest exception: rising life satisfaction predicted more video calling in some groups). Comparing across people rather than within them, texting frequency was linked to higher life satisfaction while YouTube and TikTok use was linked to lower life satisfaction — suggesting who uses which platforms matters more than any real effect of the platforms themselves on wellbeing.

  • Materials, Data, and Analysis code

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From Social Media to Empathic Artificial Intelligence: Applying Past Lessons to Future Technologies [PDF]→

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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. 

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Gaps in Large Language Model Awareness, Usage, and Perceptions in the United States: Evidence from a Nationally Representative Longitudinal Survey [PDF]→

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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)

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Does Thinking About God Increase Acceptance of Artificial Intelligence in Decision-Making? [PDF]→

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Moore, D. A., Schroeder, J., Bailey, E. R., Gershon, R., Moore, J. E., & Simmons, J. P. (2024). Does thinking about God increase acceptance of artificial intelligence in decision making? Proceedings of the National Academy of Sciences (Letter to Editor), 121(31), e2402315121. [PNAS Link]

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Computational Ethics [PDF]→

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Awad, E., Levine, S., Anderson, M., Anderson, S. L., Conitzer, V., Crockett, M. J., Everett, J. A. C., Evgeniou, T., Gopnik, A., Jamison, J. C., Kin, T. W., Liao, S. M., Lin, P., Meyer, M. N., Mikhail, J., Opoku-Agyemang, K., Schaich Borg, J., Schroeder, J., Sinnott-Armstrong, W., Slavkovik, M., & Tennenbaum, J. B. (2022). Computational ethics. Trends in Cognitive Sciences, 26(5), 388-405.[Article link]

  • Short Summary: This paper proposes a framework – computational ethics – that specifies how the ethical challenges of AI can be addressed better by incorporating the study of how humans make moral decisions.

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Consumer Decisions with Artificially Intelligent Voice Assistants [PDF]→

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Dellaert, B., Shu, S., Arentze, T., Baker, T., Diehl, K., Donkers, B., Haeubl, G., Johnson, H., Karmarkar, U., Oppewal, H., Schmitt, B., Schroeder, J., Spiller, S., & Steffel, M. (2020). Consumer decisions with artificially intelligent voice assistants. Marketing Letters, 31(4), 335-347. [Springer Link]

  • Short Summary: Consumers are widely adopting Artificially Intelligent Voice Assistants. This paper (1) provides an overview of how consumer decision-making may change in the presence of AI voice assistants and (2) discusses how marketing managers and policymakers could effectively respond to these effects of AI voice assistants on consumer decisions.

  • Based on an Invitational Choice Symposium on Automated Decision Dialogues (2019)

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Power and Decision Making: New Directions for Research in the Age of Artificial Intelligence [PDF]→

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Fast, N., & Schroeder, J. (2020). Power and decision making: new directions for research in the age of artificial intelligence. Current Opinion in Psychology, 33, 172-176. [Science Direct Link]

  • Short Summary: New advances in artificial intelligence (AI) are creating the potential to experience power in human–AI interactions. This paper reviews findings on power and decision making in the context of human–human interactions and then considers how they may be meaningfully extended through interactions with artificially intelligent digital assistants.

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Two Social Lives: How Differences Between Online and Offline Interaction Influence Social Outcomes [PDF]→

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Lieberman, A., & Schroeder, J. (2019). Two social lives: How differences between online and offline interaction influence social outcomes. Current Opinion in Psychology, 31, 16-21. [Science Direct Link]

  • Short Summary: Today, people communicate more online than offline. What does this shift mean for human social life? This paper provides a framework for studying the influence of technology on social life.

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Mistaking Minds and Machines: How Speech Affects Dehumanization and Anthropomorphism [PDF]→

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Schroeder, J., & Epley, N. (2016). Mistaking minds and machines: How speech affects dehumanization and anthropomorphism. Journal of Experimental Psychology: General, 145, 1427-1437. [APA PsycNet Link]

  • Short Summary: This paper shows that hearing a human speech (compared with reading the same words in text or watching a human communicator with subtitles) makes evaluators more likely to believe a script was created by a human (vs. computer) regardless of whether it actually was created by a human (4 experiments).

  • Data and Materials

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