Lab meetings

In our lab, we believe staying engaged with the field, whether it’s through paper discussion or learning about one another’s work, is essential to our development as researchers. Many ideas in I/O psychology are deeply interconnected: we could apply the same methodologies to solve different problems, or integrate a new topic idea with our focus of study to inspire something new… Especially because our lab has a special focus on modern technologies and research methodologies, continuous learning is crucial. Keeping up with emerging research helps us broaden our horizons, engaging in deeper discussions about the future of our field, and its broader implications for work and life. 

Each week, we center our discussion around a selected article or topic. Conversations typically focus on 1) what’s compelling about the paper, 2) areas the study could improve on, 3) methodologies used and their strengths or limitations, 4) practical implications in real-world settings, and 5) connections to our own research work and existing knowledge. Feel free to check out our previous lab schedules to have a glance into our lab routine and learning journey! 

# AI & Sustainability (discussion leader: Moana)

While AI may feel instantly accessible at our fingertips online, the infrastructure powering it often depends on large-scale data centers built through significant land use and, in some cases, the displacement of local communities. At the same time, the technological and financial benefits are often concentrated elsewhere. Unequal access to advanced AI systems, tools, and training can also deepen the digital divide, limiting students and workers from disadvantaged backgrounds in accessing the emerging opportunities AI creates. This raises important questions about how we can implement intentional policies that ensure AI does not reinforce existing socioeconomic inequalities.

Article of Discussion -- (Hammerschmidt et al, 2025)

# AI social chatbots & mental health (discussion leader: Xinyi) 

Research has found that companionship is the most primary reason why individuals interact with chatbots, especially among those with smaller social networks. However, these types of chatbot usage are consistently associated with lower wellbeing, particularly when usage is more intensive, involves higher levels of self-disclosure, and lacks weak human social support networks. While AI may fulfill certain emotional needs, recent cases also highlighted potential risks when individuals rely on AI for emotional support. These encourage us to think about the ethical futures of AI as a source of companionship: the implications of AI’s friendly but unreciprocal nature, concerns of data privacy, differences between AI and actual human relationships, and when human designers and institutions should intervene.

Article of Discussion -- (Zhang et al., 2025)

# Value theoretical framework and goal setting (discussion leader: Dr. Sun)

Values are distinct from preferences. Working in an environment where our core values are fulfilled (having a high fit congruence) is associated with many positive outcomes, e.g., better performance, attitude and health. While it might be difficult to find a job that perfectly aligns with our values, tradeoffs in values are also often inevitable, value frameworks still provide a useful basis for self-reflection and decision making, helping us reflect on our core values and linking them to important long-term decision making, such as future career and the kind of life we want to live.

Article of Discussion -- (Schwartz, 2012)