What is missing in autonomous discovery: Open challenges for the community

TL;DR

This paper discusses the current state, challenges, and future opportunities of self-driving labs, emphasizing community efforts to address barriers and foster responsible growth in autonomous scientific discovery.

Contribution

It provides a community perspective on open challenges, opportunities, and a future vision for self-driving labs, integrating insights from academia, government, and industry.

Findings

Current solutions in technology and infrastructure

Advances in AI and knowledge generation

Focus on education and workforce development

Abstract

Self-driving labs (SDLs) leverage combinations of artificial intelligence, automation, and advanced computing to accelerate scientific discovery. The promise of this field has given rise to a rich community of passionate scientists, engineers, and social scientists, as evidenced by the development of the Acceleration Consortium and recent Accelerate Conference. Despite its strengths, this rapidly developing field presents numerous opportunities for growth, challenges to overcome, and potential risks of which to remain aware. This community perspective builds on a discourse instantiated during the first Accelerate Conference, and looks to the future of self-driving labs with a tempered optimism. Incorporating input from academia, government, and industry, we briefly describe the current status of self-driving labs, then turn our attention to barriers, opportunities, and a vision for what is possible. Our field is delivering solutions in technology and infrastructure, artificial intelligence and knowledge generation, and education and workforce development. In the spirit of community, we intend for this work to foster discussion and drive best practices as our field grows.