Ethics-based AI auditing: A systematic literature review on conceptualizations of ethical principles and knowledge contributions to stakeholders
J Laine, M Minkkinen, M Mäntymäki - Information & Management, 2024 - Elsevier
This systematic literature review synthesizes the conceptualizations of ethical principles in AI
auditing literature and the knowledge contributions to the stakeholders of AI auditing. We …
auditing literature and the knowledge contributions to the stakeholders of AI auditing. We …
A critical survey on fairness benefits of XAI
In this critical survey, we analyze typical claims on the relationship between explainable AI
(XAI) and fairness to disentangle the multidimensional relationship between these two …
(XAI) and fairness to disentangle the multidimensional relationship between these two …
Through the fairness lens: Experimental analysis and evaluation of entity matching
Entity matching (EM) is a challenging problem studied by different communities for over half
a century. Algorithmic fairness has also become a timely topic to address machine bias and …
a century. Algorithmic fairness has also become a timely topic to address machine bias and …
Fairness-aware range queries for selecting unbiased data
We are being constantly judged by automated decision systems that have been widely
criticised for being discriminatory and unfair. Since an algorithm is only as good as the data …
criticised for being discriminatory and unfair. Since an algorithm is only as good as the data …
A novel approach for assessing fairness in deployed machine learning algorithms
Fairness in machine learning (ML) emerges as a critical concern as AI systems increasingly
influence diverse aspects of society, from healthcare decisions to legal judgments. Many …
influence diverse aspects of society, from healthcare decisions to legal judgments. Many …
Maximizing fair content spread via edge suggestion in social networks
Content spread inequity is a potential unfairness issue in online social networks, disparately
impacting minority groups. In this paper, we view friendship suggestion, a common feature in …
impacting minority groups. In this paper, we view friendship suggestion, a common feature in …
Seldonian toolkit: Building software with safe and fair machine learning
We present the Seldonian Toolkit, which enables software engineers to integrate provably
safe and fair machine learning algorithms into their systems. Software systems that use data …
safe and fair machine learning algorithms into their systems. Software systems that use data …
A Critical Survey on Fairness Benefits of Explainable AI
In this critical survey, we analyze typical claims on the relationship between explainable AI
(XAI) and fairness to disentangle the multidimensional relationship between these two …
(XAI) and fairness to disentangle the multidimensional relationship between these two …
Saturn: An Optimized Data System for Large Model Deep Learning Workloads
K Nagrecha, A Kumar - arXiv preprint arXiv:2309.01226, 2023 - arxiv.org
Large language models such as GPT-3 & ChatGPT have transformed deep learning (DL),
powering applications that have captured the public's imagination. These models are rapidly …
powering applications that have captured the public's imagination. These models are rapidly …
Fairkit, fairkit, on the wall, who's the fairest of them all? Supporting fairness-related decision-making
Modern software relies heavily on data and machine learning, and affects decisions that
shape our world. Unfortunately, recent studies have shown that because of biases in data …
shape our world. Unfortunately, recent studies have shown that because of biases in data …