The moral psychology of Artificial Intelligence

JF Bonnefon, I Rahwan, A Shariff - Annual review of psychology, 2024 - annualreviews.org
Moral psychology was shaped around three categories of agents and patients: humans,
other animals, and supernatural beings. Rapid progress in artificial intelligence has …

Fairness perceptions of artificial intelligence: A review and path forward

D Narayanan, M Nagpal, J McGuire… - … Journal of Human …, 2024 - Taylor & Francis
A key insight from research on organizational justice is that fairness is in the eye of the
beholder. With increasing discussions–especially among computer scientists and …

Perceived algorithmic fairness: An empirical study of transparency and anthropomorphism in algorithmic recruiting

J Ochmann, L Michels, V Tiefenbeck… - Information Systems …, 2024 - Wiley Online Library
Despite constant efforts of organisations to ensure a fair and transparent personnel selection
process, hiring is still characterised by systematic inequality. The potential of algorithms to …

Synthetic data in biomedicine via generative artificial intelligence

B van Breugel, T Liu, D Oglic… - Nature Reviews …, 2024 - nature.com
The creation and application of data in biomedicine and healthcare often face privacy
constraints, bias, distributional shifts, underrepresentation of certain groups and data …

Mitigating test-time bias for fair image retrieval

F Kong, S Yuan, W Hao… - Advances in Neural …, 2024 - proceedings.neurips.cc
We address the challenge of generating fair and unbiased image retrieval results given
neutral textual queries (with no explicit gender or race connotations), while maintaining the …

Beyond privacy: Navigating the opportunities and challenges of synthetic data

B van Breugel, M van der Schaar - arXiv preprint arXiv:2304.03722, 2023 - arxiv.org
Generating synthetic data through generative models is gaining interest in the ML
community and beyond. In the past, synthetic data was often regarded as a means to private …

The role of domain expertise in trusting and following explainable AI decision support systems

S Bayer, H Gimpel, M Markgraf - Journal of Decision Systems, 2022 - Taylor & Francis
Although the roots of artificial intelligence (AI) stretch back some years, it currently flourishes
in research and practice. However, AI deals with trust issues. One possible solution …

Measuring non-expert comprehension of machine learning fairness metrics

D Saha, C Schumann, D Mcelfresh… - International …, 2020 - proceedings.mlr.press
Bias in machine learning has manifested injustice in several areas, such as medicine, hiring,
and criminal justice. In response, computer scientists have developed myriad definitions of …

Towards responsible AI: A design space exploration of human-centered artificial intelligence user interfaces to investigate fairness

Y Nakao, L Strappelli, S Stumpf, A Naseer… - … Journal of Human …, 2023 - Taylor & Francis
With Artificial intelligence (AI) to aid or automate decision-making advancing rapidly, a
particular concern is its fairness. In order to create reliable, safe and trustworthy systems …

The use of responsible artificial intelligence techniques in the context of loan approval processes

E Purificato, F Lorenzo, F Fallucchi… - International Journal of …, 2023 - Taylor & Francis
Despite the existing skepticism about the use of automatic systems in contexts where human
knowledge and experience are considered indispensable (eg, the granting of a mortgage …