Adjusting to the GDPR: The Impact on Data Scientists and Behavioral Researchers. - Travis Greene; Galit Shmueli; Soumya Ray; Jan Fell (Big Data, 2019)

How Personal is Machine Learning Personalization? - Travis Greene; Galit Shmueli (CoRR, 2019)

Beyond Human-Centered Design: Proposing a Biocentric View on Design Research Involving Vegetal Subjects. - Jan Fell; Travis Greene; Jyun-Cheng Wang; Pei-Yi Kuo (Conference on Designing Interactive Systems (Companion Volume), 2020)

Beyond Our Behavior: The GDPR and Humanistic Personalization. - Travis Greene; Galit Shmueli (CoRR, 2020)

The Hidden Inconsistencies Introduced by Predictive Algorithms in Judicial Decision Making. - Travis Greene; Galit Shmueli; Jan Fell; Ching-Fu Lin; Mark L. Shope; Han-Wei Liu (CoRR, 2020)

Seeing Humans in the Data: Ethical Blind Spots of Taiwan Academic Researchers in the Era of Behavioral Big Data. - Jan Fell; Galit Shmueli; Travis Greene; Jyun-Cheng Wang; Soumya Ray; Shu-Yuan Wu (HICSS, 2021)

Barriers to academic data science research in the new realm of algorithmic behaviour modification by digital platforms. - Travis Greene; David Martens; Galit Shmueli (Nat. Mach. Intell., 2022)

A Biocentric Perspective on HCI Design Research Involving Plants. - Jan Fell; Pei-Yi Kuo; Travis Greene; Jyun-Cheng Wang (ACM Trans. Comput. Hum. Interact., 2022)

Monetizing Explainable AI: A Double-edged Sword. - Travis Greene; Sofie Goethals; David Martens; Galit Shmueli (CoRR, 2023)

Taking the Person Seriously: Ethically Aware IS Research in the Era of Reinforcement Learning-Based Personalization. - Travis Greene; Galit Shmueli; Soumya Ray (J. Assoc. Inf. Syst., 2023)

Atomist or holist? A diagnosis and vision for more productive interdisciplinary AI ethics dialogue. - Travis Greene; Amit Dhurandhar; Galit Shmueli (Patterns, 2023)

Beware of "Explanations" of AI. - David Martens; Galit Shmueli; Theodoros Evgeniou; Kevin Bauer; Christian Janiesch; Stefan Feuerriegel; Sebastian Gabel; Sofie Goethals; Travis Greene; Nadja Klein; Mathias Kraus; Niklas Kühl 001; et al. (CoRR, 2025)

From What Ifs to Insights: Counterfactuals in Causal Inference vs. Explainable AI. - Galit Shmueli; David Martens; Jaewon Yoo; Travis Greene (CoRR, 2025)