Psychology of AI
Psychology of AI
Data science by people for people
Successful introduction of artificial intelligence ultimately depends on humans’ beliefs and adoption behavior. The Psychology of AI lab is a group of interdisciplinary experts examining the human side of data and AI.
While research in information systems, computer science, and other disciplines focuses on the technical computations of algorithms and the output that they deliver, we focus on the humans who interpret and interact with AI and algorithmic advice.
We work with numerous stakeholders, such as employers, employees, customers, policy makers, and AI-developers and study a variety of topics, including: consumer acceptance of AI solutions, and of automated products; employee beliefs about technological replacement of human labor, and how analysts make sense of data and AI.
From an organizational perspective, data application projects and AI-driven innovations are only successful when they are positively received and correctly used by employers, employees and customers. Important psychological processes such as social comparison, attribution, need for uniqueness, and self-consciousness explain how individuals react to, and think about, intelligent machines. We conduct experiments with human participants and apply a behavioral science approach to AI
From a societal perspective, current forecasts show that significant sections of the labor force will disappear or change, due to the increasing ability of robots and algorithms to automate tasks. Regardless of whether this displacement will be transitional or permanent, it is important for the impact on society to understand potential threats to the psychological wellbeing of affected individuals. Our lab investigates the psychological consequences of technological replacement of human activities.
- Autonomous Shopping Systems
- Consumer Reactions to Decisions by Algorithms versus Humans
- Does Personalized Advertising Work as Well as Tech Companies Claim?
- Preference for Materiality in Identity-based Consumption
- Robots Save Us Time — But Do They Make Us Happier?
- The Impact of Recommendation Agent Effort on Perceived Recommendation Agent Quality
- User- Versus Item-Based Framings on Recommendation Click-Throughs
- Why Recommendations On Netflix, Amazon, Or WeChat Could Be More Influential Than You Think
- Anne-Kathrin Klesse, Associate Professor of Marketing & Academic Director of the Psychology of AI lab // Tech devices and decision-making, algorithmic recommendations
- Mirjam Tuk, Associate Professor of Marketing & Director of the Brownbag Seminar Series // Self-control, perceptions of technology and educational choices
- Jelle de Vries, Associate Professor of Operations Management // Human-machine collaboration in operations
- Johannes Boegershausen, Assistant Professor of Marketing // Acceptance of robots, technological unemployment
- Antonia Krefeld-Schwalb, Assistant Professor of Marketing // measuring preferences, temporal discounting, meta-science
- Colin Lee, Assistant Professor of Organization and Personnel Management // AI in recruitment and selection
Affiliated PhD Students
- Almira Abilova, PhD student // Perceptions of technology and educational choices
- Begum Celiktutan, PhD student // Tech devices and decision-making
- Yue Zhang, PhD student // ChatGTP, Consumer-AI interactions
- Ragna-Britt Taube // AI & Consumer well-being, personalization, advertisement
- Begum Celiktutan // Human-AI interactions
- Jenny Lena Zimmerman, PhD student // University of St. Gallen // Consumer perceptions of, and evolving relationships with, autonomous products
- Emanuel de Bellis, Associate Professor // University of St. Gallen // Consumer perceptions of autonomous products and algorithms
- Martin Paul Fritze, Assistant Professor // University of Cologne // Materiality, experiential marketing, technology & innovation diffusion
- Melanie Clegg, PhD student, University of Lucerne // Consumer perceptions of algorithms, AI, ethics of AI
- Reto Hofstetter // Professor of Digital Marketing //University of Lucerne // Creativity and AI, Algorithm Perception, applying AI/ML in consumer research
- Stefano Puntoni //Professor of Marketing //The Wharton School// Adoption of automation, AI experiences, technological unemployment, decision-making with data
- Gizem Yalcin // Assistant Professor of Marketing // University of Texas Auston // Perceptions of algorithmic decision-makers, algorithmic recommendations
- Eugina Leung // Assistant Professor of Marketing // Tulane University Freeman School of Business // Automation, dematerialization, AI, Search algorithms
- Phyliss Gai // Assistant Professor of Marketing // Guanghua School of Management, Peking University // Consumer-AI interaction, consumer welfar