Tobias Rieger

The effect of robot abesence/presence on perceived trustworthiness and dependence

Tobias Rieger, Eileen Roesler, Neha Kannan

AI Error Difficulty Modulates the Effectiveness of Explainability in Decision Support Systems

Tobias Rieger, Hanna Schindler, Katharina Koch, Linda Onnasch

In AI decision support, explainability (e.g., disclosing system weaknesses) should help users spot erroneous recommendations, but its efficacy may depend on task difficulty. We ran three experiments in a simulated medical visual detection task. In Experiment 1, we manipulated error difficulty (easy …

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Methodological framework for a user-centered, structured, and digitized training program for exoskeleton pilots in CYBATHLON preparation

Nicola Dobler, Christina Ortelt, Tobias Rieger, Lukas Schneidewind

PURPOSE: Successful participation in the CYBATHLON depends not only on technical innovation but also on effective, systematic training of pilots with spinal cord injury. Current research primarily focuses on clinical rehabilitation, while standardized, task-specific training protocols for applied competition settings are lacking. …

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ChatGPT Is a People Pleaser, Especially When Taking Human vs. AI Advice

Tobias Rieger, Eileen Roesler

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Human learning is an understudied but promising lever for boosting human--AI synergy

Julian Berger, Jason W. Burton, Ralph Hertwig, Thomas Kosch et autres

Humans collaborating with artificial intelligence (AI) hold the promise of achieving superior outcomes compared to either acting alone (i.e., human--AI synergy). However, the conditions that facilitate such synergy when humans are advised by AI are not well understood. A recent meta-analysis showed …

Impact of Voice Assistants’ Conversational Style on Cognitive Driver Distraction

Monique Dittrich, S M Ko, Tobias Rieger

The integration of large language models (LLMs) in voice assistants has introduced a new level of naturalness and functionality into human-assistant interactions, also in cars.These enhancements lead to more engaging interactions that carry the potential cost of increasing cognitive driver distraction.This assumption …

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Why Highly Reliable Decision Support Systems Often Lead to Suboptimal Performance and What We Can Do About it

Tobias Rieger, Linda Onnasch, Eileen Roesler, Dietrich Manzey

In a growing number of application domains, human decision-making is being supported by automated systems. While previous research has focused extensively on the negative consequences of automation support in terms of an overuse of such systems, we argue that this focus has …

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Explaining AI weaknesses improves human–AI performance in a dynamic control task

Tobias Rieger, Hanna Schindler, Linda Onnasch, Eileen Roesler

AI-based decision support is increasingly implemented to support operators in dynamic control tasks. While these systems continuously improve, to truly achieve human–system synergy, one must also study humans’ system understanding and behavior. Accordingly, we investigated the impact of explainability instructions regarding a …

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Likelihood Systems Can Improve Hit Rates in Low-Prevalence Visual Search Over Binary Systems

Tobias Rieger, B. Marx, Dietrich Manzey

ObjectiveTo study the performance consequences of binary versus likelihood decision support systems in low-prevalence visual search.BackgroundHit rates in visual search are often low if target prevalence is low, an issue that is relevant for numerous real-world visual search tasks (e.g., luggage screening …

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ChatGPT Is a People Pleaser, Especially When Taking Human vs. AI Advice

Eileen Roesler, Tobias Rieger

Materials, agent response data, and analysis code for Rieger & Roesler (2026), ChatGPT Is a People Pleaser, Especially When Taking Human vs. AI Advice (CHI EA '26; https://doi.org/10.1145/3772363.3798923). Two preregistered conceptual replications using ChatGPT agents (GPT-5.1) as participants in judge-advisor-system experiments. Experiment …

Numeric vs. verbal information: The influence of information quantifiability in Human–AI vs. Human–Human decision support

Eileen Roesler, Tobias Rieger, Markus Langer

A number of factors, including different task characteristics, influence trust in human vs. AI decision support. In particular, the aspect of information quantifiability could influence trust and dependence, especially considering that human and AI support may have varying strengths in assessing criteria …

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The Pop-Out Effect of Rarer Occurring Stimuli Shapes the Effectiveness of AI Explainability

Pawinee Pithayarungsarit, Tobias Rieger, Linda Onnasch, Eileen Roesler

Explainable artificial intelligence (XAI) is proposed to improve transparency and performance by providing information about AI’s limitations. Specifically, XAI could support appropriate behavior in cases where AI errors occur due to less training data. These error-prone cases might be salient (pop-out) because …

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