Where Responsible AI meets Reality

Type: Article

Publication Date: 2021-04-13

Citations: 131

DOI: https://doi.org/10.1145/3449081

Abstract

Large and ever-evolving technology companies continue to invest more time and resources to incorporate responsible Artificial Intelligence (AI) into production-ready systems to increase algorithmic accountability. This paper examines and seeks to offer a framework for analyzing how organizational culture and structure impact the effectiveness of responsible AI initiatives in practice. We present the results of semi-structured qualitative interviews with practitioners working in industry, investigating common challenges, ethical tensions, and effective enablers for responsible AI initiatives. Focusing on major companies developing or utilizing AI, we have mapped what organizational structures currently support or hinder responsible AI initiatives, what aspirational future processes and structures would best enable effective initiatives, and what key elements comprise the transition from current work practices to the aspirational future.

Locations

  • Proceedings of the ACM on Human-Computer Interaction - View
  • arXiv (Cornell University) - View - PDF
  • DataCite API - View

Similar Works

Action Title Year Authors
+ Towards a Roadmap on Software Engineering for Responsible AI 2022 Qinghua Lu
Liming Zhu
Xiwei Xu
Jon Whittle
Zhenchang Xing
+ Towards a roadmap on software engineering for responsible AI 2022 Qinghua Lu
Liming Zhu
Xiwei Xu
Jon Whittle
Zhenchang Xing
+ PDF Chat A Rapid Review of Responsible AI frameworks: How to guide the development of ethical AI 2023 Vita Santa Barletta
Danilo Caivano
D Gigante
Azzurra Ragone
+ PDF Chat Strategies for Increasing Corporate Responsible AI Prioritization 2024 Angelina Wang
Teresa Datta
John P. Dickerson
+ PDF Chat Strategies for Increasing Corporate Responsible AI Prioritization 2024 Angelina Wang
Teresa Datta
John P. Dickerson
+ PDF Chat Responsible AI in the Software Industry: A Practitioner-Centered Perspective 2024 Mihai Leca
Mariana Donato
Ronnie de Souza Santos
+ PDF Chat POLARIS: A framework to guide the development of Trustworthy AI systems 2024 MarĂ­a Teresa Baldassarre
D Gigante
Marcos Kalinowski
Azzurra Ragone
+ PDF Chat Responsible Artificial Intelligence: A Structured Literature Review 2024 Sabrina Goellner
Marina Tropmann-Frick
Boštjan Brumen
+ Investigating Responsible AI for Scientific Research: An Empirical Study 2023 Muneera Bano
Didar Zowghi
Pip Shea
Georgina Ibarra
+ PDF Chat Towards Implementing Responsible AI 2022 Conrad Sanderson
Qinghua Lu
David Douglas
Xiwei Xu
Liming Zhu
Jon Whittle
+ Towards Implementing Responsible AI 2022 Conrad Sanderson
Qinghua Lu
David C. Douglas
Xiwei Xu
Liming Zhu
Jon Whittle
+ Responsible-AI-by-Design: a Pattern Collection for Designing Responsible AI Systems 2022 Qinghua Lu
Liming Zhu
Xiwei Xu
Jon Whittle
+ PDF Chat When Industry meets Trustworthy AI: A Systematic Review of AI for Industry 5.0 2024 Eduardo Vyhmeister
Gabriel G. Castañé
+ A Brief Overview of AI Governance for Responsible Machine Learning Systems 2022 Navdeep Gill
Abhishek Mathur
Marcos V. Conde
+ Responsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and Engineering 2022 Qinghua Lu
Liming Zhu
Xiwei Xu
Jon Whittle
Didar Zowghi
Aurelie Jacquet
+ Responsible AI Governance: A Systematic Literature Review 2024 Amna Batool
Didar Zowghi
Muneera Bano
+ The Role of Cooperation in Responsible AI Development 2019 Amanda Askell
Miles Brundage
Gillian K. Hadfield
+ PDF Chat RAI Guidelines: Method for Generating Responsible AI Guidelines Grounded in Regulations and Usable by (Non-)Technical Roles 2024 Marios Constantinides
Edyta P. Bogucka
Daniele Quercia
Susanna Kallio
Mohammad Tahaei
+ Putting AI Ethics into Practice: The Hourglass Model of Organizational AI Governance 2022 Matti Mäntymäki
Matti Minkkinen
Teemu Birkstedt
Mika Viljanen
+ Resolving Ethics Trade-offs in Implementing Responsible AI 2024 Conrad Sanderson
Emma Schleiger
David C. Douglas
Petra Kuhnert
Qinghua Lu

Works That Cite This (44)

Action Title Year Authors
+ Seamful XAI: Operationalizing Seamful Design in Explainable AI 2022 Upol Ehsan
Q. Vera Liao
Samir Passi
Mark Riedl
Hal Daumé
+ FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines 2023 Matthew L Barker
Emma Kallina
Dhananjay Ashok
Katherine M. Collins
Ashley Casovan
Adrian Weller
Ameet Talwalkar
Valerie Chen
Umang Bhatt
+ PDF Chat Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethics 2023 Richmond Y. Wong
Michael Madaio
Nick Merrill
+ Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction 2023 Renee Shelby
Shalaleh Rismani
Kathryn Henne
AJung Moon
Negar Rostamzadeh
P. O. Nicholas
N'Mah Yilla-Akbari
Jess Gallegos
Andrew Smart
Emilio GarcĂ­a GarcĂ­a
+ PDF Chat Trustworthy AI: From Principles to Practices 2022 Bo Li
Peng Qi
Liu Bo
Shuai Di
Jingen Liu
Jiquan Pei
Jinfeng Yi
Bowen Zhou
+ Towards a Non-Ideal Methodological Framework for Responsible ML 2024 Ramaravind Kommiya Mothilal
Shion Guha
Syed Ishtiaque Ahmed
+ Model Compression in Practice: Lessons Learned from Practitioners Creating On-device Machine Learning Experiences 2024 Fred Hohman
Mary Beth Kery
Donghao Ren
Dominik Moritz
+ PDF Chat German AI Start-Ups and “AI Ethics”: Using A Social Practice Lens for Assessing and Implementing Socio-Technical Innovation 2022 Mona Sloane
Janina Zakrzewski
+ PDF Chat Inherent Limitations of AI Fairness 2024 Maarten Buyl
Tijl De Bie
+ PDF Chat RAI Guidelines: Method for Generating Responsible AI Guidelines Grounded in Regulations and Usable by (Non-)Technical Roles 2024 Marios Constantinides
Edyta P. Bogucka
Daniele Quercia
Susanna Kallio
Mohammad Tahaei

Works Cited by This (11)

Action Title Year Authors
+ Linking Artificial Intelligence Principles 2018 Yi Zeng
Enmeng Lu
Cunqing Huangfu
+ Linking Artificial Intelligence Principles 2018 Yi Zeng
Enmeng Lu
Cunqing Huangfu
+ PDF Chat The global landscape of AI ethics guidelines 2019 Anna Jobin
Marcello Ienca
Effy Vayena
+ PDF Chat Defining AI in Policy versus Practice 2020 P. M. Krafft
Meg Young
Michael Katell
Karen Huang
Ghislain Bugingo
+ PDF Chat Algorithmic Fairness from a Non-ideal Perspective 2020 Sina Fazelpour
Zachary C. Lipton
+ PDF Chat Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims 2020 Miles Brundage
Shahar Avin
Jasmine Wang
Haydn Belfield
Gretchen Krueger
Gillian K. Hadfield
Heidy Khlaaf
Jingying Yang
Helen Toner
Ruth Fong
+ Diversity and Inclusion Metrics in Subset Selection 2020 Margaret Mitchell
Dylan Baker
Nyalleng Moorosi
Emily Denton
Ben Hutchinson
Alex Hanna
Timnit Gebru
Jamie Morgenstern
+ PDF Chat Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? 2019 Kenneth Holstein
Jennifer Wortman Vaughan
Hal Daumé
Miro DudĂ­k
Hanna Wallach
+ PDF Chat Model Cards for Model Reporting 2019 Margaret Mitchell
Simone Wu
Andrew Zaldivar
Parker Barnes
Lucy Vasserman
Ben Hutchinson
Elena Spitzer
Inioluwa Deborah Raji
Timnit Gebru
+ Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims 2020 Miles Brundage
Shahar Avin
Jasmine Wang
Haydn Belfield
Gretchen Krueger
Gillian K. Hadfield
Heidy Khlaaf
Jingying Yang
Helen Toner
Ruth Fong