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11:00 - 12:30
Parallel sessions 2
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11:00 - 12:30
Room: HSZ - N2
Chair/s:
Nadia Said
The introduction of new technologies has always shaped societies. Artificial intelligence (AI) applications, especially AI chatbots, are already part of everyday human life. Robots – for example in healthcare but also in other service areas – are also becoming more and more common. Generally, perceptions of these new technologies are mixed. Whereas some of them are widely accepted (e.g., use of generative AI tools like ChatGPT or DeepL), others are highly controversial (e.g., use of AI in classrooms or robots as companions in elderly homes). This raises the question of which factors influence human perceptions of and ultimately human interaction with AI and robots? The aim of this symposium is to present novel insights into human-AI and human-robot interaction by taking three different perspectives: (i) how far do social perceptions also extend to robots and how does this influence the interaction with robots?, (ii) what factors shape humans’ interaction with generative AI tools and how does such an interaction impact them?, (iii) do people differ in their perception of AI and robots? To provide answers to these questions, the first talk investigates the perception of robots as social actors. More specifically, the talk focuses on how similar robots are perceived to be, for example, to human partners. The second talk then tackles the question whether established social heuristics (such as the bystander effect) govern human behavior toward robots. Moving from embodied artificial actors to generative AI tools, the third talk focuses on the influence of external factors (explainability, content, culture) on the perception of an AI chatbot. The fourth talk investigates factors influencing the choice to use generative AI as a cognitive offloading tool and its consequences for human memory and performance. In the final talk, the question of whether Artificial Intelligence and robots are perceived differently is discussed. Jointly, these talks provide a broad overview of human-AI and human-robot interaction by examining the topic from different perspectives.
Submission 185
Cognitive Offloading with Generative AI: User Choice and Consequences for Task Performance and Memory
SymposiumTalk-04
Presented by: Frank Papenmeier
Frank Papenmeier, Elias B. Thum, Jana Gehrer, Julia S. Talmon, Anton Klimov
University of Tübingen, Germany
This talk investigates human interaction with generative AI (i.e., chatbots) from the perspective of cognitive offloading. We present two experiments examining (1) the factors influencing the decision to offload cognitive tasks to AI and (2) the consequences of such offloading on task performance and memory. The first experiment focused on choice factors. Participants could solve arithmetic word problems internally or offload them to a chatbot. We manipulated the bot's response speed and measured participants' math skill. Results revealed that bot speed influenced offloading decisions: participants offloaded more frequently to a faster bot. Furthermore, higher math skill predicted less reliance on the AI. The second experiment investigated the consequences of chatbot use on tasks targeting two levels of Bloom's taxonomy: 'apply' and 'remember'. Participants completed text comprehension problems, randomly assigned to either use a chatbot or work unaided. Results showed that while chatbot use did not significantly alter performance on 'apply' tasks, it significantly impaired subsequent memory for the text content. Taken together, these findings demonstrate that the cognitive offloading framework offers a valuable framework for understanding human-AI interaction. This research highlights that both system characteristics (e.g., speed) and user abilities (e.g., skill) shape AI adoption, and that reliance on AI as a cognitive tool can have detrimental effects on later memory performance.