Investigating Responsible AI for Scientific Research: An Empirical Study
- URL: http://arxiv.org/abs/2312.09561v1
- Date: Fri, 15 Dec 2023 06:40:27 GMT
- Title: Investigating Responsible AI for Scientific Research: An Empirical Study
- Authors: Muneera Bano, Didar Zowghi, Pip Shea, Georgina Ibarra
- Abstract summary: The push for Responsible AI (RAI) in such institutions underscores the increasing emphasis on integrating ethical considerations within AI design and development.
This paper aims to assess the awareness and preparedness regarding the ethical risks inherent in AI design and development.
Our results have revealed certain knowledge gaps concerning ethical, responsible, and inclusive AI, with limitations in awareness of the available AI ethics frameworks.
- Score: 4.597781832707524
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Scientific research organizations that are developing and deploying
Artificial Intelligence (AI) systems are at the intersection of technological
progress and ethical considerations. The push for Responsible AI (RAI) in such
institutions underscores the increasing emphasis on integrating ethical
considerations within AI design and development, championing core values like
fairness, accountability, and transparency. For scientific research
organizations, prioritizing these practices is paramount not just for
mitigating biases and ensuring inclusivity, but also for fostering trust in AI
systems among both users and broader stakeholders. In this paper, we explore
the practices at a research organization concerning RAI practices, aiming to
assess the awareness and preparedness regarding the ethical risks inherent in
AI design and development. We have adopted a mixed-method research approach,
utilising a comprehensive survey combined with follow-up in-depth interviews
with selected participants from AI-related projects. Our results have revealed
certain knowledge gaps concerning ethical, responsible, and inclusive AI, with
limitations in awareness of the available AI ethics frameworks. This revealed
an overarching underestimation of the ethical risks that AI technologies can
present, especially when implemented without proper guidelines and governance.
Our findings reveal the need for a holistic and multi-tiered strategy to uplift
capabilities and better support science research teams for responsible,
ethical, and inclusive AI development and deployment.
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