All one needs to know about metaverse: A complete survey on technological singularity, virtual ecosystem, and research agenda

LH Lee, T Braud, PY Zhou, L Wang… - … and trends® in …, 2024 - nowpublishers.com
Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We
have created various computer-mediated virtual environments, including social networks …

Towards a science of human-AI decision making: An overview of design space in empirical human-subject studies

V Lai, C Chen, A Smith-Renner, QV Liao… - Proceedings of the 2023 …, 2023 - dl.acm.org
AI systems are adopted in numerous domains due to their increasingly strong predictive
performance. However, in high-stakes domains such as criminal justice and healthcare, full …

A survey on the fairness of recommender systems

Y Wang, W Ma, M Zhang, Y Liu, S Ma - ACM Transactions on …, 2023 - dl.acm.org
Recommender systems are an essential tool to relieve the information overload challenge
and play an important role in people's daily lives. Since recommendations involve …

[PDF][PDF] Ai transparency in the age of llms: A human-centered research roadmap

QV Liao, JW Vaughan - arxiv preprint arxiv:2306.01941, 2023 - assets.pubpub.org
The rise of powerful large language models (LLMs) brings about tremendous opportunities
for innovation but also looming risks for individuals and society at large. We have reached a …

Algorithmic bias: review, synthesis, and future research directions

N Kordzadeh, M Ghasemaghaei - European Journal of Information …, 2022 - Taylor & Francis
As firms are moving towards data-driven decision making, they are facing an emerging
problem, namely, algorithmic bias. Accordingly, algorithmic systems can yield socially …

Algorithmic bias in education

RS Baker, A Hawn - International journal of artificial intelligence in …, 2022 - Springer
In this paper, we review algorithmic bias in education, discussing the causes of that bias and
reviewing the empirical literature on the specific ways that algorithmic bias is known to have …

What do we want from Explainable Artificial Intelligence (XAI)?–A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research

M Langer, D Oster, T Speith, H Hermanns, L Kästner… - Artificial intelligence, 2021 - Elsevier
Abstract Previous research in Explainable Artificial Intelligence (XAI) suggests that a main
aim of explainability approaches is to satisfy specific interests, goals, expectations, needs …

Towards a science of human-ai decision making: a survey of empirical studies

V Lai, C Chen, QV Liao, A Smith-Renner… - arxiv preprint arxiv …, 2021 - arxiv.org
As AI systems demonstrate increasingly strong predictive performance, their adoption has
grown in numerous domains. However, in high-stakes domains such as criminal justice and …

[HTML][HTML] Fairness and explanation in AI-informed decision making

A Angerschmid, J Zhou, K Theuermann… - Machine Learning and …, 2022 - mdpi.com
AI-assisted decision-making that impacts individuals raises critical questions about
transparency and fairness in artificial intelligence (AI). Much research has highlighted the …

Machine learning in mental health: A systematic review of the HCI literature to support the development of effective and implementable ML systems

A Thieme, D Belgrave, G Doherty - ACM Transactions on Computer …, 2020 - dl.acm.org
High prevalence of mental illness and the need for effective mental health care, combined
with recent advances in AI, has led to an increase in explorations of how the field of machine …