Philipp Lorenz-Spreen

Ezequiel Lopez-Lopez, Christoph M. Abels, Philipp Lorenz-Spreen et al.

People navigate complex environments using cues, heuristics, and other strategies, which are often adaptive in stable settings. However, as AI increasingly permeates society's information environments, those become more adaptive and evolving: LLM-based chatbots participate in extended interaction, maintain conversational histories, mirror social cues, and can hypercustomize responses, thereby shaping not only what information is accessed but how questions are framed, how evidence is interpreted, and when action feels warranted. Here we propose a framework for sustained human-AI interaction that rests on invariant features of human cognition and human--AI interaction and centers on three interlinked phenomena: entanglement between users and AI systems, the emergence of cognitive and behavioral drift over repeated interactions, and the role of metacognition in the awareness and regulation of these dynamics. As conversational agents provide cues (e.g., fluency, coherence, responsiveness) that people treat as informative, subjective confidence and action readiness may increase without corresponding gains in epistemic reliability, making drift difficult to detect and correct. We describe these dynamics across micro-, meso-, and macro-levels. The framework identifies four metacognitive intervention points and psychologically informed interventions that provide metacognitive scaffolding (boosting and self-nudging). Finally, we outline a long-horizon research agenda for scientific foresight.

Nils Köbis, Philipp Lorenz-Spreen, Tamer Ajaj et al.

The increasing prevalence of image-altering filters on social media and video conferencing technologies has raised concerns about the ethical and psychological implications of using Artificial Intelligence (AI) to manipulate our perception of others. In this study, we specifically investigate the potential impact of blur filters, a type of appearance-altering technology, on individuals' behavior towards others. Our findings consistently demonstrate a significant increase in selfish behavior directed towards individuals whose appearance is blurred, suggesting that blur filters can facilitate moral disengagement through depersonalization. These results emphasize the need for broader ethical discussions surrounding AI technologies that modify our perception of others, including issues of transparency, consent, and the awareness of being subject to appearance manipulation by others. We also emphasize the importance of anticipatory experiments in informing the development of responsible guidelines and policies prior to the widespread adoption of such technologies.

Joseph B. Bak-Coleman, Stephan Lewandowsky, Philipp Lorenz-Spreen et al.

Social media is nearly ubiquitous in modern life, raising concerns about its societal impacts -- from mental health and polarization to violence and democratic disruption. Yet research on its causal effects is still inconclusive: Various methods, spanning observational to experimental, can yield seemingly conflicting results. Considering the complexity of such socio-technical systems, with coupled networks, feedback loops and collective phenomena, this may not be surprising. Here, we enumerate and examine the features of social media as a complex system that challenge our ability to infer causality at societal scales. Attempts to ascertain and summarize causal effects have tended to prioritize findings from randomized controlled trials (RCTs). However, like observational studies, RCTs rely on assumptions that may frequently be violated in the context of social media, especially regarding societal outcomes at scale. Drawing on insight from disciplines that have faced similar challenges, like climate-science or epidemiology, we propose a path forward that combines the strengths of observational and experimental approaches while acknowledging the limitations of each. Progress, we argue, requires moving beyond isolated, linear effects to mechanistic explanations of how social media platforms generate collective outcomes.