Re-thinking data strategy and integration for artificial intelligence: concepts, opportunities, and challenges
The use of artificial intelligence (AI) is becoming more prevalent across industries such as
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of …
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of …
Trustworthy artificial intelligence: a review
Artificial intelligence (AI) and algorithmic decision making are having a profound impact on
our daily lives. These systems are vastly used in different high-stakes applications like …
our daily lives. These systems are vastly used in different high-stakes applications like …
Should chatgpt be biased? challenges and risks of bias in large language models
E Ferrara - arxiv preprint arxiv:2304.03738, 2023 - arxiv.org
As the capabilities of generative language models continue to advance, the implications of
biases ingrained within these models have garnered increasing attention from researchers …
biases ingrained within these models have garnered increasing attention from researchers …
Six human-centered artificial intelligence grand challenges
Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the
human condition in ways that are not yet well understood. Negative unintended …
human condition in ways that are not yet well understood. Negative unintended …
[HTML][HTML] How can we manage biases in artificial intelligence systems–A systematic literature review
PS Varsha - International Journal of Information Management Data …, 2023 - Elsevier
Artificial intelligence is similar to human intelligence, and robots in organisations always
perform human tasks. However, AI encounters a variety of biases during its operational …
perform human tasks. However, AI encounters a variety of biases during its operational …
[KÖNYV][B] Towards a standard for identifying and managing bias in artificial intelligence
R Schwartz, R Schwartz, A Vassilev, K Greene… - 2022 - dwt.com
As individuals and communities interact in and with an environment that is increasingly
virtual, they are often vulnerable to the commodification of their digital footprint. Concepts …
virtual, they are often vulnerable to the commodification of their digital footprint. Concepts …
Weak-to-strong generalization: Eliciting strong capabilities with weak supervision
Widely used alignment techniques, such as reinforcement learning from human feedback
(RLHF), rely on the ability of humans to supervise model behavior-for example, to evaluate …
(RLHF), rely on the ability of humans to supervise model behavior-for example, to evaluate …
[HTML][HTML] Addressing bias in big data and AI for health care: A call for open science
Artificial intelligence (AI) has an astonishing potential in assisting clinical decision making
and revolutionizing the field of health care. A major open challenge that AI will need to …
and revolutionizing the field of health care. A major open challenge that AI will need to …
Bias mitigation for machine learning classifiers: A comprehensive survey
This article provides a comprehensive survey of bias mitigation methods for achieving
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …
Data collection and quality challenges in deep learning: A data-centric ai perspective
Data-centric AI is at the center of a fundamental shift in software engineering where machine
learning becomes the new software, powered by big data and computing infrastructure …
learning becomes the new software, powered by big data and computing infrastructure …