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ORCIDJakob Schöffer
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2020 – today
- 2024
[j1]Connor Lawless
, Jakob Schoeffer, Lindy Le, Kael Rowan, Shilad Sen, Cristina St. Hill, Jina Suh, Bahareh Sarrafzadeh:
"I Want It That Way": Enabling Interactive Decision Support Using Large Language Models and Constraint Programming. ACM Trans. Interact. Intell. Syst. 14(3): 22:1-22:33 (2024)- [c15]Jakob Schoeffer, Maria De-Arteaga, Niklas Kühl:
Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making. CHI 2024: 836:1-836:18 - [c14]Luca Deck, Jakob Schoeffer, Maria De-Arteaga, Niklas Kühl:
A Critical Survey on Fairness Benefits of Explainable AI. FAccT 2024: 1579-1595 - [i18]Luca Deck, Astrid Schomäcker, Timo Speith, Jakob Schöffer, Lena Kästner, Niklas Kühl:
Mapping the Potential of Explainable Artificial Intelligence (XAI) for Fairness Along the AI Lifecycle. CoRR abs/2404.18736 (2024) - 2023
- [c13]Jakob Schoeffer, Alexander Ritchie, Keziah Naggita, Faidra Monachou, Jessica Finocchiaro, Marc Juarez:
Online Platforms and the Fair Exposure Problem under Homophily. AAAI 2023: 11899-11908 - [c12]Jakob Schoeffer, Johannes Jakubik, Michael Vössing, Niklas Kühl, Gerhard Satzger:
On the Interdependence of Reliance Behavior and Accuracy in AI-Assisted Decision-Making. HHAI 2023: 46-59 - [c11]Lucas Baier, Tim Schlör, Jakob Schoeffer, Niklas Kühl:
Detecting Concept Drift with Neural Network Model Uncertainty. HICSS 2023: 835-844 - [i17]Jakob Schoeffer, Johannes Jakubik, Michael Vössing, Niklas Kühl, Gerhard Satzger:
On the Interdependence of Reliance Behavior and Accuracy in AI-Assisted Decision-Making. CoRR abs/2304.08804 (2023) - [i16]Luca Deck, Jakob Schoeffer, Maria De-Arteaga, Niklas Kühl:
A Critical Survey on Fairness Benefits of XAI. CoRR abs/2310.13007 (2023) - [i15]Connor Lawless, Jakob Schoeffer, Lindy Le, Kael Rowan, Shilad Sen, Cristina St. Hill, Jina Suh, Bahareh Sarrafzadeh:
"I Want It That Way": Enabling Interactive Decision Support Using Large Language Models and Constraint Programming. CoRR abs/2312.06908 (2023) - 2022
- [c10]Jakob Schoeffer:
A Human-Centric Perspective on Fairness and Transparency in Algorithmic Decision-Making. CHI Extended Abstracts 2022: 66:1-66:6 - [c9]Jakob Schoeffer, Niklas Kühl, Yvette Machowski:
"There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-Making. FAccT 2022: 1616-1628 - [c8]Patrick Hemmer, Niklas Kühl, Jakob Schoeffer:
Utilizing Active Machine Learning for Quality Assurance: A Case Study of Virtual Car Renderings in the Automotive Industry. HICSS 2022: 1-10 - [c7]Jakob Schoeffer, Yvette Machowski, Niklas Kühl:
Perceptions of Fairness and Trustworthiness Based on Explanations in Human vs. Automated Decision-Making. HICSS 2022: 1-8 - [c6]Johannes Jakubik, Jakob Schöffer, Vincent Hoge, Michael Vössing, Niklas Kühl:
An Empirical Evaluation of Predicted Outcomes as Explanations in Human-AI Decision-Making. PKDD/ECML Workshops (1) 2022: 353-368 - [i14]Jakob Schöffer, Alexander Ritchie, Keziah Naggita, Faidra Monachou, Jessie Finocchiaro, Marc Juarez:
Online Platforms and the Fair Exposure Problem Under Homophily. CoRR abs/2202.09727 (2022) - [i13]Jakob Schoeffer, Maria De-Arteaga, Niklas Kühl:
On the Relationship Between Explanations, Fairness Perceptions, and Decisions. CoRR abs/2204.13156 (2022) - [i12]Jakob Schoeffer:
A Human-Centric Perspective on Fairness and Transparency in Algorithmic Decision-Making. CoRR abs/2205.00033 (2022) - [i11]Jakob Schoeffer, Niklas Kühl, Yvette Machowski:
"There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-Making. CoRR abs/2205.05758 (2022) - [i10]Johannes Jakubik, Jakob Schöffer, Vincent Hoge, Michael Vössing, Niklas Kühl:
An Empirical Evaluation of Predicted Outcomes as Explanations in Human-AI Decision-Making. CoRR abs/2208.04181 (2022) - [i9]Jakob Schoeffer, Maria De-Arteaga, Niklas Kühl:
On Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making. CoRR abs/2209.11812 (2022) - 2021
- [c5]Jakob Schöffer, Niklas Kühl:
Appropriate Fairness Perceptions? On the Effectiveness of Explanations in Enabling People to Assess the Fairness of Automated Decision Systems. CSCW Companion 2021: 153-157 - [c4]Jakob Schöffer, Niklas Kühl, Isabel Valera:
A Ranking Approach to Fair Classification. COMPASS 2021: 115-125 - [c3]Jakob Schöffer, Yvette Machowski, Niklas Kühl:
A Study on Fairness and Trust Perceptions in Automated Decision Making. IUI Workshops 2021 - [i8]Jakob Schöffer, Niklas Kühl, Isabel Valera:
A Ranking Approach to Fair Classification. CoRR abs/2102.04565 (2021) - [i7]Jakob Schöffer, Yvette Machowski, Niklas Kühl:
A Study on Fairness and Trust Perceptions in Automated Decision Making. CoRR abs/2103.04757 (2021) - [i6]Lucas Baier, Tim Schlör, Jakob Schöffer, Niklas Kühl:
Detecting Concept Drift With Neural Network Model Uncertainty. CoRR abs/2107.01873 (2021) - [i5]Jakob Schöffer, Niklas Kühl:
Appropriate Fairness Perceptions? On the Effectiveness of Explanations in Enabling People to Assess the Fairness of Automated Decision Systems. CoRR abs/2108.06500 (2021) - [i4]Jakob Schöffer, Yvette Machowski, Niklas Kühl:
Perceptions of Fairness and Trustworthiness Based on Explanations in Human vs. Automated Decision-Making. CoRR abs/2109.05792 (2021) - [i3]Patrick Hemmer, Niklas Kühl, Jakob Schöffer:
Utilizing Active Machine Learning for Quality Assurance: A Case Study of Virtual Car Renderings in the Automotive Industry. CoRR abs/2110.09023 (2021) - 2020
- [c2]Lucas Baier, Jakob Schöffer, Niklas Kühl:
Utilizing Adaptive AI-based Information Systems to Analyze the Effectiveness of Policy Measures in the Fight of COVID-19. ICIS 2020 - [c1]Patrick Hemmer, Niklas Kühl, Jakob Schöffer:
DEAL: Deep Evidential Active Learning for Image Classification. ICMLA 2020: 865-870 - [p1]Niklas Kühl, Hansjörg Fromm, Jakob Schöffer, Gerhard Satzger:
Service Analytics: Putting the "Smart" in Smart Services. Smart Service Management 2020: 151-159 - [i2]Patrick Hemmer, Niklas Kühl, Jakob Schöffer:
DEAL: Deep Evidential Active Learning for Image Classification. CoRR abs/2007.11344 (2020) - [i1]Lucas Baier, Niklas Kühl, Jakob Schöffer, Gerhard Satzger:
Utilizing Concept Drift for Measuring the Effectiveness of Policy Interventions: The Case of the COVID-19 Pandemic. CoRR abs/2012.03728 (2020)
Coauthor Index
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