A sociotechnical perspective for responsible AI maturity models: Findings from a mixed-method literature review-Reference-Cited by-同舟云学术

A sociotechnical perspective for responsible AI maturity models: Findings from a mixed-method literature review

Published:2023-11 Issue:2 Volume:3 Page:100193
ISSN:2667-0968
Container-title:International Journal of Information Management Data Insights
language:en
Short-container-title:International Journal of Information Management Data Insights

Author:

Akbarighatar Pouria^ORCID,Pappas Ilias,Vassilakopoulou Polyxeni

Publisher

Elsevier BV

Subject

Library and Information Sciences,Industrial and Manufacturing Engineering,Information Systems and Management,Information Systems,Artificial Intelligence,Management Information Systems

Reference105 articles.

1. Collective response to the health crisis among German Twitter users: A structural topic modeling approach;Abramova;International Journal of Information Management Data Insights,2022

2. From AI compliance to competitive advantage,2022

3. Understanding public engagement on Twitter using topic modeling: The 2019 Ridgecrest earthquake case;Ahn;International Journal of Information Management Data Insights,2021

4. Rethinking IT in construction and engineering: Organisational readiness;Alshawi,2007

5. Maturity and readiness models for responsible artificial intelligence (RAI): A systematic literature review;Akbarighatar,2022

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. How artificial intelligence can enable data classification for market sizing - Insights from applications in practice;International Journal of Information Management Data Insights;2024-11

2. A sociotechnical perspective for explicit unfairness mitigation techniques for algorithm fairness;International Journal of Information Management Data Insights;2024-11

3. Aligning Industry Needs and Education: Unlocking the Potential of AI via Skills;2024 Portland International Conference on Management of Engineering and Technology (PICMET);2024-08-04

4. Operationalizing responsible AI principles through responsible AI capabilities;AI and Ethics;2024-07-24

5. Water quality level estimation using IoT sensors and probabilistic machine learning model;Hydrology Research;2024-07-01