Jakob Schöffer, M.Sc.

Jakob Schöffer, M.Sc.


Jakob is a research associate at the Applied AI Lab within the Karlsruhe Service Research Institute (KSRI). His interests include:

  • Algorithmic Decision Making
  • Fairness and Ethics in Artificial Intelligence
  • Human-Computer Interaction
  • Machine Learning and Natural Language Processing (general)
  • Mathematical Optimization (general)

Please reach out if you are interested in writing a bachelor or master thesis on one of these topics.

Curriculum Vitae

Jakob earned his undergraduate degree in Industrial Engineering and Management from the Karlsruhe Institute of Technology (KIT). In 2017, Jakob graduated from the Georgia Institute of Technology in Atlanta, Georgia (USA) with a master’s in Operations Research. Upon graduation, he joined IBM in Armonk, New York (USA), working as a data scientist. After more than 2 years with IBM, Jakob returned to KIT in October 2019, where he is now working towards his PhD.


Conference Papers
"There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-Making
Schöffer, J.; Kühl, N.; Machowski, Y.
2022. Conference on Fairness, Accountability, and Transparency (ACM FAccT 2022), 21.-24. Juni 2022 
On the Relationship Between Explanations, Fairness Perceptions, and Decisions
Schoeffer, J.; De-Arteaga, M.; Kuehl, N.
2022. ACM CHI Workshop on Human-Centered Explainable AI (HCXAI), 12.-13. Mai 2022 
A Human-Centric Perspective on Fairness and Transparency in Algorithmic Decision-Making
Schoeffer, J.
2022. CHI Conference on Human Factors in Computing Systems Extended Abstracts, 1–6, Association for Computing Machinery (ACM). doi:10.1145/3491101.3503811
Perceptions of Fairness and Trustworthiness Based on Explanations in Human vs. Automated Decision-Making
Schoeffer, J.; Machowski, Y.; Kühl, N.
2022. Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS) : January 4-7, 2022, Hyatt Regency Maui, Hawaii, USA, 1095–1102, University of Hawai’i at Manoa / Hamilton Library. doi:10.24251/hicss.2022.134Full textFull text of the publication as PDF document
Utilizing Active Machine Learning for Quality Assurance: A Case Study of Virtual Car Renderings in the Automotive Industry
Hemmer, P.; Kühl, N.; Schöffer, J.
2022. Proceedings of the Hawaii International Conference on Systems Sciences (HICSS-55) 
Conference Papers
Appropriate Fairness Perceptions? On the Effectiveness of Explanations in Enabling People to Assess the Fairness of Automated Decision Systems
Schoeffer, J.; Kuehl, N.
2021. Companion Publication of the 2021 Conference on Computer Supported Cooperative Work and Social Computing (CSCW ’21 Companion), October 23–27, 2021, Virtual Event, USA. Ed.: J. Birnholtz, 153–157, Association for Computing Machinery (ACM). doi:10.1145/3462204.3481742
A Study on Fairness and Trust Perceptions in Automated Decision Making
Schöffer, J.; Machowski, Y.; Kühl, N.
2021. Joint Proceedings of the ACM IUI 2021 Workshops, April 13–17, 2021, College Station, USA, 170005, RWTH Aachen Full textFull text of the publication as PDF document
A Ranking Approach to Fair Classification
Schöffer, J.; Kühl, N.; Valera, I.
2021. COMPASS ’21: Proceedings of the 4th ACM SIGCAS Conference on Computing and Sustainable Societies, June 28 - July 2, 2021, Virtual Event, Australia, 115–125, Association for Computing Machinery (ACM). doi:10.1145/3460112.3471950
Book Chapters
Service Analytics: Putting the “Smart” in Smart Services
Kühl, N.; Fromm, H.; Schöffer, J.; Satzger, G.
2020. Smart Service Management : Design Guidelines and Best Practices. Ed.: M. Maleshkova; N. Kühl, Axel Springer SE. doi:10.1007/978-3-030-58182-4
Conference Papers
Utilizing Adaptive AI-based Information Systems to Analyze the Effectiveness of Policy Measures in the Fight of COVID-19
Baier, L.; Schöffer, J.; Kühl, N.
2020. ICIS 2020 – Making Digital Inclusive: Blending the Local and the Global : December 13-16, 2020 
DEAL: Deep Evidential Active Learning for Image Classification
Hemmer, P.; Kühl, N.; Schöffer, J.
2020. 19th IEEE International Conference On Machine Learning And Applications, December, Miami, Florida, December 14-17, 2020, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICMLA51294.2020.00141