Enabling Ethical AI- A Socio-Technical Perspective
The term ethics is widely used, explored, and debated in the context of developing Artificial Intelligence (AI) based software systems. In recent years, numerous incidents have raised the profile of ethical issues in AI development and led to public concerns about the proliferation of technology.
But what do we know about the views and experiences of those who develop these systems– the AI practitioners?
We conducted a grounded theory literature review (GTLR) of 38 primary empirical studies that included AI practitioners’ views on ethics in AI and analysed them to derive five categories: practitioner awareness, perception, need, challenge, and approach.
These are underpinned by multiple codes and concepts that we explain with evidence from the included studies. We present a taxonomy of ethics in AI from practitioners’ viewpoints to assist AI practitioners in identifying and understanding the different aspects of AI ethics.
The taxonomy provides a landscape view of the key aspects that concern AI practitioners when it comes to ethics in AI. We also share an agenda for future research studies and recommendations for practitioners, managers, and organisations to help in their efforts to better consider and implement ethics in AI.
We are interested in investigating the views and understanding of AI practitioners about ethics in AI. The main objectives of our study include but are not limited to:
- Investigating industry perspectives on the aspects of AI ethics
- Raising awareness of AI ethics among AI practitioners
- Investigating AI practitioners’ perspectives and experiences in developing a fair AI/ML.
We are conducting research with teams involved in AI development, such as AI developers, scientists, practitioners, and experts, to gain insight into their views on AI ethics. Our goal is to design techniques and tools that will promote the integration of ethics into AI development and trial these with partner organisations.
Publications:
- “What Would You do? An Ethical AI Quiz". Authors: Wei Teo, Ze Teoh, Abang Arabi, Morad Aboushadi, Khairenn Lai, Zhe Ng, Aastha Pant, Rashina Hoda, Chakkrit Tantithamthavorn, and Burak Turhan
Accepted at International Conference on Software Engineering (ICSE)- Demo Track, Jan 2023 - Pant, A., Hoda, R., Spiegler, S. V., Tantithamthavorn, C., & Turhan, B. (2024). Ethics in the age of AI: an analysis of ai practitioners’ awareness and challenges. ACM Transactions on Software Engineering and Methodology, 33(3), 1-35.
- Pant, A., Hoda, R., Tantithamthavorn, C., & Turhan, B. (2024). Ethics in AI through the practitioner’s view: a grounded theory literature review. Empirical Software Engineering, 29(3), 67.
- Pant, A., Spiegler, S., Hoda, R., Yoon, J., Yusuf, N., Er, T., & Hu, S. (2024, April). Teaching Software Ethics to Future Software Engineers. In Proceedings of the 46th International Conference on Software Engineering: Software Engineering Education and Training (pp. 391-401).
Project resources:
- Tool development: Interactive Ethical AI Quiz: https://interactive-ai-ethics-quiz.herokuapp.com/
- Demo video of the Interactive Ethical Ai quiz: https://zenodo.org/record/7601169#.ZAlAr-xBxhE
- Project summary
Project Team
Prof Rashina Hoda, Aastha Pant (PhD Candidate), Dr Chakkrit Tantithamthavorn, Dr Simone Spiegler, Adj/Prof Burak Turhan
Taxonomy of ethics in AI from practitioners’ viewpoints
