Position: We Need Responsible, Application-Driven (RAD) AI Research
By: Sarah Hartman , Cheng Soon Ong , Julia Powles and more
Potential Business Impact:
AI helps solve real problems by working with people.
This position paper argues that achieving meaningful scientific and societal advances with artificial intelligence (AI) requires a responsible, application-driven approach (RAD) to AI research. As AI is increasingly integrated into society, AI researchers must engage with the specific contexts where AI is being applied. This includes being responsive to ethical and legal considerations, technical and societal constraints, and public discourse. We present the case for RAD-AI to drive research through a three-staged approach: (1) building transdisciplinary teams and people-centred studies; (2) addressing context-specific methods, ethical commitments, assumptions, and metrics; and (3) testing and sustaining efficacy through staged testbeds and a community of practice. We present a vision for the future of application-driven AI research to unlock new value through technically feasible methods that are adaptive to the contextual needs and values of the communities they ultimately serve.
Similar Papers
Barbarians at the Gate: How AI is Upending Systems Research
Artificial Intelligence
AI finds faster computer programs than people.
Framework, Standards, Applications and Best practices of Responsible AI : A Comprehensive Survey
Computers and Society
Makes AI fair and safe for everyone.
Let the Barbarians In: How AI Can Accelerate Systems Performance Research
Software Engineering
AI finds better computer system designs.