I research the psychology of media and technology. Since outlining a research agenda for prosociality with and through interactive media (Ng, 2016), I have been especially interested in understanding human reciprocity and cooperation with/through interactive media technologies, including but not limited to artificial intelligence (AI) media and social media.

Ng, Y.-L. (2016). More than social–cultural influences: A research agenda for evolutionary perspectives on prosocial media effects. Review of General Psychology, 20, 317–335. https://doi.org/10.1037/gpr0000084

Reciprocity and Cooperation with Interactive Media Technologies (AI Media)

I have investigated interactive media technologies with which people apply social rules and expectations, i.e., communicative AI media. I conducted a prisoner’s dilemma experiment on human–communicative AI cooperation with communicative agents to examine the associated social dilemmas (Ng, 2023b). Furthermore, sophisticated social cues and cognitive heuristics elicited by AI can prompt people to use social rules and expectations not only in initial interactions with AI, but also in interactions with people. Accordingly, I conducted a representative survey exploring the conversational AI use–social capital association (Ng, 2024a).

Ng, Y.-L. (2023b). When communicative AIs are cooperative actors: A prisoner’s dilemma experiment on human–communicative artificial intelligence cooperation. Behaviour & Information Technology, 13, 2141–2151. https://doi.org/10.1080/0144929X.2022.2111273

Ng, Y.-L. (2024a). Exploring the association between use of conversational artificial intelligence and social capital: Survey evidence from Hong Kong. New Media & Society, 26, 1429–1444. https://doi.org/10.1177/14614448221074047

A student and I used ecologically valid social media data to identify motivations and relevant topics regarding human–AI interaction in a natural setting. We examined user conversations on Reddit, a social mediated community of practice, to understand how users collaboratively discuss technical and societal issues and concerns (Lin & Ng, 2025) and learn how to improve their practice (Ng & Lin, 2022). Extending these findings, I constructed an integrated longitudinal model to test functional and motivational factors impacting trust in and use of conversational AI (Ng, 2025). Beyond acceptance of conversational AI, I also investigated passenger acceptance of AI-enabled autonomous vehicles in the driverless dilemma, a real-world social-dilemma scenario (Ng, 2024b).

Ng, Y.-L. (2025). A longitudinal model of continued acceptance of conversational artificial intelligence. Information Technology & People, 38, 1871–1889. https://doi.org/10.1108/ITP-06-2023-0577

Ng, Y.-L. (2024b). Understanding passenger acceptance of autonomous vehicles through the prism of the trolley dilemma. International Journal of Human–Computer Interaction, 40, 2185–2194. https://doi.org/10.1080/10447318.2022.2163347

Ng, Y.-L., & Lin, Z. (2022). Exploring conversation topics in conversational artificial intelligence–based social mediated communities of practice. Computers in Human Behavior, 134, 107326. https://doi.org/10.1016/j.chb.2022.107326

Lin, Z., & Ng, Y.-L. (2025). Unraveling gratifications, concerns, and acceptance of generative artificial intelligence. International Journal of Human–Computer Interaction, 41, 10725-10742. https://doi.org/10.1080/10447318.2024.2436749

To conclude, these studies could contribute to the broader literature on moral machine and reciprocal AI.

Reciprocity and Cooperation through Interactive Media Technologies (Social Media)

Beyond understanding human–communicative AI cooperation, I have studied human–human reciprocity and cooperation through social media. It has been argued that, compared with other species, humans are highly ecologically successful because of their large-scale ingroup cooperation. I reviewed social media research and proposed that humans have evolved to cooperate with others and now use social media to enact ingroup cooperation, including getting and giving emotional support, sharing knowledge, and pursuing common goals (Ng, 2020a). I found empirically that social media use, particularly active use, was associated with increased perceived relatedness of people in need and with a decreased influence of genetic relatedness on helping (Ng, 2020b). In another study, a student and I explored the potential for meme sharing (as a form of social grooming) on social media to be related to enhanced online social capital and well-being (Luo & Ng, 2025).

Ng, Y.-L. (2020a). Toward an evolutionary perspective on social media use for cooperation. Evolutionary Behavioral Sciences, 14, 132–146. https://doi.org/10.1037/ebs0000172

Ng, Y.-L. (2020b). Active and passive Facebook use and associated costly off-line helping behavior. Psychological Reports, 123, 2562–2581. https://doi.org/10.1177/0033294119860262

Luo, Y., & Ng, Y.-L. (2025). Exploring the mediating role of online social capital in the association between sharing memes using four humor styles and subjective well-being. Social Media + Society, 11, 1–14. https://doi.org/10.1177/20563051251348922

Beyond ingroup reciprocity through social media, my colleagues and I studied reciprocity toward outgroup people through social media. Specifically, we examined supportive expressions in discussions about outgroups by ingroup members (Ng et al., 2022).

Ng, Y.-L., Song, Y., & Huang, Y. (2022). Supportive and uncivil expressions in discussions on out-groups by in-group members in anonymous computer-mediated communication. Telematics and Informatics, 69, 101785. https://doi.org/10.1016/j.tele.2022.101785

Extending this interest from reciprocity with ingroup and outgroup humans to other species through digital media, I have also studied human–nature reciprocity in digital contexts. According to Edward Wilson’s biophilia hypothesis, humans have evolved to affiliate with nature and other species. By integrating the uses and gratifications approach with the biophilia hypothesis, I coined the term biophilia gratification to refer to the psychological need to affiliate with mediated nature. I have conducted three studies to empirically test biophilia gratification. First, a survey was conducted to test the uses and gratifications of mediated nature and associated interdependence with nature and pro-environmental behavior (Ng, 2022). Second, a student and I computationally analyzed three million social media posts (10% were image-based) to test whether user reactions reflect biophilia gratification derived from mediated nature (Ng & Lin, In press). Third, extending the human–nature inquiry from social media to digital games, I investigated gaming gratifications from biophilic simulation games designed to simulate natural environments (Ng, In press). To conclude, these empirical studies imply that biophilia gratification can benefit the human–nature relationship.

Ng, Y.-L. (2022). Uses and gratifications of and exposure to nature 2.0 and associated interdependence with nature and pro-environmental behavior. Social Science Computer Review, 40, 61–76. https://doi.org/10.1177/0894439320901490

Ng, Y.-L. (In press). Uses and gratifications of biophilic simulation games. Games and Culture. Advance online publication. https://doi.org/10.1177/15554120241249518

Ng, Y.-L., & Lin, Z. (In press). Biophilia gratification: Evidence from nature-related posts and images on social media. New Media & Society. Advance online publication. https://doi.org/10.1177/14614448241303776

Apart from the above research topics, I have also studied the psychological and social antecedents and consequences of interacting with and through various media technologies, including surveillance technology (Ng & Lin, 2024), deepfakes (Ng, 2023a), virtual and augmented reality (Ng, Ma, et al., 2019), life-threatening news (Ng, 2025; Ng & Zhao, 2020), online incivility (Ng et al., 2020), and digital divide (Ng, Chan, et al., 2019).

Ng, Y.-L. (2025). An error management approach to the human alarm system for correct and incorrect news content involving direct life-threatening risks. Journal of Risk Research, 28, 486-502. https://doi.org/10.1080/13669877.2025.2512079

Ng, Y.-L. (2023a). An error management approach to perceived fakeness of deepfakes: The moderating role of perceived deepfake targeted politicians’ personality characteristics. Current Psychology, 42, 25658–25669. https://doi.org/10.1007/s12144-022-03621-x

Ng, Y.-L., Chan, K., Balwicki, Ł., Huxley, P. J., & Chiu, M. Y.-L. (2019). The digital divide, social inclusion, and health among persons with mental illness in Poland. International Journal of Communication, 13, 1652–1672.

Ng, Y.-L., & Lin, Z. (2024). Between technological utopia and dystopia: Online expression of compulsory use of surveillance technology. Science and Engineering Ethics, 30, 19. https://doi.org/10.1007/s11948-024-00483-3

Ng, Y.-L., Ma, F., Ho, F. K., Ip, P., & Fu, K. (2019). Effectiveness of virtual and augmented reality-enhanced exercise on physical activity, psychological outcomes, and physical performance: A systematic review and meta-analysis of randomized controlled trials. Computers in Human Behavior, 99, 278–291. https://doi.org/10.1016/j.chb.2019.05.026

Ng, Y.-L., Song, Y., Kwon, K. H., & Huang, Y. (2020). Toward an integrative model for online incivility research: A review and synthesis of empirical studies on the antecedents and consequences of uncivil discussions online. Telematics and Informatics, 47, 101323. https://doi.org/10.1016/j.tele.2019.101323

Ng, Y.-L., & Zhao, X. (2020). The human alarm system for sensational news, online news headlines, and associated generic digital footprints: A uses and gratifications approach. Communication Research, 47, 251–275. https://doi.org/10.1177/0093650218793739

“Essentially, all models are wrong, but some are useful.”