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Found 11 papers, 1 papers with code
Complementarity in Human-AI Collaboration: Concept, Sources, and Evidence
Our work provides researchers with a theoretical foundation of complementarity in human-AI decision-making and demonstrates that leveraging sources of complementarity potential constitutes a viable pathway toward effective human-AI collaboration.
Towards Effective Human-AI Decision-Making: The Role of Human Learning in Appropriate Reliance on AI Advice
We hypothesize that, in addition to the mental model, human learning is a key mediator of appropriate reliance and, thus, CTP.
Human-AI Collaboration: The Effect of AI Delegation on Human Task Performance and Task Satisfaction
In an experimental study with 196 participants, we show that task performance and task satisfaction improve through AI delegation, regardless of whether humans are aware of the delegation.
Towards Meaningful Anomaly Detection: The Effect of Counterfactual Explanations on the Investigation of Anomalies in Multivariate Time Series
We propose to support this anomaly investigation by providing explanations of anomaly detection.
Appropriate Reliance on AI Advice: Conceptualization and the Effect of Explanations
In this paper, we propose Appropriateness of Reliance (AoR) as an underlying, quantifiable two-dimensional measurement concept.
A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making
However, we find no effect of explanations on users' performance compared to sole AI predictions.
On the Effect of Information Asymmetry in Human-AI Teams
Over the last years, the rising capabilities of artificial intelligence (AI) have improved human decision-making in many application areas.
Factors that influence the adoption of human-AI collaboration in clinical decision-making
Recent developments in Artificial Intelligence (AI) have fueled the emergence of human-AI collaboration, a setting where AI is a coequal partner.
On the Influence of Explainable AI on Automation Bias
However, it may also evoke human bias, especially in the form of automation bias as an over-reliance on AI advice.
Should I Follow AI-based Advice? Measuring Appropriate Reliance in Human-AI Decision-Making
However, recent work has shown that AI advice is not always beneficial, as humans have shown to be unable to ignore incorrect AI advice, essentially representing an over-reliance on AI.
Intelligent Decision Assistance Versus Automated Decision-Making: Enhancing Knowledge Work Through Explainable Artificial Intelligence
To test this conceptualization, we develop hypotheses on the impacts of IDA and provide first evidence for their validity based on empirical studies in the literature.
