Charting the Ethical and Moral Landscapes of Human-AI Interactions

Abstract

Unlike previous technological advancements, AI possesses unique characteristics that set it apart from traditional tools: AI systems are dynamic, adaptive, and capable of operating without human intervention (Anthony, Bechky, Fayard, 2023). Their ability to mimic and exceed human intelligence compels individuals and organizations to confront shifting boundaries between human and machine capabilities (Raisch and Krakowski, 2021). These shifts have profound ethical and moral implications for individual subjectivity, professional identity, judgment, and responsibility, as well as the ensuing societal and workplace norms (Faraj, Pachidi, Sayegh, 2018; Latonero, 2018; Frank et al., 2019). As AI integration accelerates, understanding how we define agency, identity, collaboration, autonomy, and ethical responsibility in hybrid human-AI systems becomes increasingly more important. To illustrate, at an individual level, AI’s ability to augment or even redefine roles and responsibilities has significant implications for personal identity and subjectivity. In professional settings, AI tools designed to improve efficiency often reshape how individuals perceive their skills, autonomy, and value (Faulconbridge, Sarwar, and Spring, 2023; Mirbabaie, Brünker, Möllmann, Stieglitz, 2022). These interactions influence how people understand themselves and their place within increasingly hybrid human-machine environments, prompting ethical concerns about deskilling, over-reliance on automation, and shifts in agency. On a broader scale, AI is transforming societal norms, professional practices, and collective understandings of fairness and accountability. Its integration into fields such as law, healthcare, and education raises questions about equity, bias, and trust, as AI systems often reflect and amplify systemic inequalities embedded in the data they process (e.g., Baker and Hawn, 2024; Fast and Schroeder, 2020; Frank et al., 2019; Glikson and Woolley, 2020; Schepers et al., 2024). These dynamics compel us to consider how human-AI collaborations reshape not only individual experiences but also the shared values and frameworks that underpin our social and organizational structures. Focusing on the challenges to our understanding of human agency, identity, fairness, and ethical responsibility, this symposium explores the multi-level dynamics of human-AI interactions. This symposium brings together theoretically and methodologically diverse perspectives to examine these dynamics and address how AI reshapes roles, relationships, skills, and responsibilities in work and beyond. The selected papers explore the complex, multi level dynamics of human-AI interaction and reflect these dynamics by starting the discussion at the level of subjective, individual experiences, proceeding to societal-level implications via professional and organizational issues. Khoreva and Einola open the discussion by examining how interactions with AI-powered chatbots influence employee subjectivity, revealing the delicate balance between technological efficiency and human agency. Going a level up from individual subjectivity, Feng and Morozova focus on the basic gender identity and highlight the gendered dynamics of generative AI adoption, uncovering social and psychological barriers that disproportionately affect women hindering equitable AI integration. Gachayeva further extends the identity focus to high-skilled professions investigating how AI reshapes professional identity, work practices, and ethical norms. Hillebrand then extends this shift from the professional to the organizational level and delves into the organizational implications of human-AI collaboration, introducing the concept of

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