Tobias Fahse
11 results
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Item type:Publication, Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods(2022); Scopus© Citations 207 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Improving AI-Assisted Decision-Making: Insights into Example-Based Explanations and Cognitive Load in Sales Forecasting(2025); ; ; AI-assisted decision-making often underperforms due to users' difficulties in effectively interacting with AI-based systems. This study investigates how example-based explanations—specifically factual and counterfactual explanations—impact users' decision-making performance and their tendency to overrule algorithmic advice in a sales forecasting task. We also examine the mediating role of cognitive load. By analyzing 1330 forecasts made in an online lab experiment, we find that factual explanations significantly enhance forecasting performance by enabling users to more effectively overrule algorithmic advice. While counterfactual explanations also result in performance gains, the increase is smaller and operates primarily through reduced deviation from AI advice due to cognitive overload. Our findings suggest that factual explanations align well with human cognitive processes, facilitating better decision outcomes, while counterfactuals may overwhelm users cognitively. This study contributes to a deeper understanding of explainable AI design in decision-making contexts, emphasizing the importance of aligning explanations with users' cognitive capacities.Type:conference paper - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Exploring the Synergies in Human-AI Hybrids: A Longitudinal Analysis in Sales Forecasting(2023-08-10); Despite the promised potential of artificial intelligence (AI), insights into real-life human-AI hybrids and their dynamics remain obscure. Based on digital trace data of over 1.4 million forecasting decisions over a 69-month period, we study the implications of an AI sales forecasting system's introduction in a bakery enterprise on decision-makers' overriding of the AI system and resulting hybrid performance. Decisionmakers quickly started to rely on AI forecasts, leading to lower forecast errors. Overall, human intervention deteriorated forecasting performance as overriding resulted in greater forecast error. The results confirm the notion that AI systems outperform humans in forecasting tasks. However, the results also indicate previously neglected, domain-specific implications: As the AI system aimed to reduce forecast error and thus overproduction, forecasting numbers decreased over time, and thereby also sales. We conclude that minimal forecast errors do not inevitably yield optimal business outcomes when detrimental human factors in decision-making are ignored.Type:conference paper - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Modern Centaurs: How Humans and AI Systems Interact in Sales Forecasting(2023-06-14); Recent achievements of artificial intelligence (AI) have caused organizations to increasingly bring AI capabilities into their core business processes. Such AI-supported business processes often result in human-AI hybrid systems, which consist of an AI system, which performs most of the execution, and humans, who monitor this execution and occasionally provide additional inputs and overrides. Using sales data from Walmart, we conduct an online study to investigate if human supervision can improve upon state-of-the-art AI forecasts. Furthermore, we analyze the perceptions and behavioral intentions of the human participants over time. We find that human interventions consistently lead to less accurate forecasts and that participants initially underestimate the AI system’s accuracy and overestimate their own potential to improve upon AI forecasts. However, perceptions quickly shift over the course of the study, causing the participants to perceive the AI system increasingly favorably, which also leads to behavioral changes and better hybrid system performance.Type:conference paperJournal:Proceedings of the European Conference on Information Systems - Some of the metrics are blocked by yourconsent settings
Item type:Publication, - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Explanation Interfaces for Sales Forecasting(Association for Information Systems, 2022-06-18); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Effectiveness of Example-Based Explanations to Improve Human Decision Quality in Machine Learning Forecasting Systems(2022-12-09); ; Algorithmic forecasts outperform human forecasts by 10% on average. State-of-the-art machine learning (ML) algorithms have further expanded this discrepancy. Because a variety of other activities rely on them, sales forecasting is critical to a company's profitability. However, individuals are hesitant to use ML forecasts. To overcome this algorithm aversion, explainable artificial intelligence (XAI) can be a solution by making ML systems more comprehensible by providing explanations. However, current XAI techniques are incomprehensible for laymen, as they impose too much cognitive load. We contribute to this research gap by investigating the effectiveness in terms of forecast accuracy of two example-based explanation approaches. We conduct an online experiment based on a two-by-two between-subjects design with factual and counterfactual examples as experimental factors. A control group has access to ML predictions, but not to explanations. We report results of this study: While factual explanations significantly improved participants' decision quality, counterfactual explanations did not.Type:conference paper - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Managing Bias in Machine Learning Projects(2021-03-09); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Die Datenschutzgrundverordnung der EU: Ein "zahnloser Tiger" oder ein wirksames Instrument? Ein datenanalytisches ExperimentIn terms of content, the results of the data analysis experiment can be with the answer to the research question: "Is the European General Data Protection Regulation (GDPR) an effective instrument to strengthen data data protection in Europe or a "toothless tiger"?": The GDPR is taking effect and is having an impact, or as Hoeren summarizes in a review after two years of the GDPR: "Inconspicuous, but effective". full". However, the effects are limited to a few companies, especially the gatekeepers, a few countries and only a few articles serve serve as the basis for the penalties. Methodologically, this article can be summarized as follows: Data analytic approaches in legal scholarship can make sense. However, the critical question is not which algorithms and methods are used for for analysis, but whether the data used as the basis for the analyses are of the necessary quality.Type:book section - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Künstliche Intelligenz in Bäckereien: Weniger Foodwaste und auch weniger Kosten(2021-07-29); ; Saxer, StefanType:discussion paper