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

Phillip M. Maffettone; Pascal Friederich; Sterling G. Baird; Ben Blaiszik; Keith A. Brown; Stuart I. Campbell; Orion A. Cohen; Rebecca L. Davis; Ian T. Foster; Navid Haghmoradi; Mark Hereld; Howie Joress; Nicole Jung; Ha-Kyung Kwon; Gabriella Pizzuto; Jacob Rintamaki; Casper Steinmann; Luca Torresi; Shijing Sun

doi:10.1039/D3DD00143A

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

Phillip M. Maffettone,

*^ab Pascal Friederich,

*^ip Sterling G. Baird,^c Ben Blaiszik,

^de Keith A. Brown,

^f Stuart I. Campbell,

^a Orion A. Cohen,^g Rebecca L. Davis,

^h Ian T. Foster,^de Navid Haghmoradi,

ⁱ Mark Hereld,

^de Howie Joress,^j Nicole Jung,^k Ha-Kyung Kwon,

^l Gabriella Pizzuto,

^m Jacob Rintamaki,ⁿ Casper Steinmann,

^o Luca Torresi^p and Shijing Sun^lq

Author affiliations

* Corresponding authors

^a National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
E-mail: pmaffetto@bnl.gov, pascal.friederich@kit.edu

^b BigHat Biosciences, San Mateo, CA 94403, USA

^c University of Utah, Salt Lake City, UT 84108, USA

^d University of Chicago, Chicago, IL 60637, USA

^e Argonne National Laboratory, Lemont, IL 60439, USA

^f Boston University, Boston, MA 02215, USA

^g Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA

^h University of Manitoba, Winnipeg, Manitoba R3T 2N2, Canada

ⁱ Karlsruhe Institute of Technology, Institute of Nanotechnology, Hermann-von-Helmholtz-Platz 1, Eggenstein-Leopoldshafen, Germany

^j Materials Measurement Science Divison, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA

^k Karlsruhe Institute of Technology, Institute of Biological and Chemical Systems, Hermann-von-Helmholtz-Platz 1, Eggenstein-Leopoldshafen, Germany

^l Toyota Research Institute, Los Altos, CA 94022, USA

^m University of Liverpool, Liverpool, UK

ⁿ Stanford University, Stanford, CA, USA

^o Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark

^p Karlsruhe Institute of Technology, Institute of Theoretical Informatics, Engler-Bunte-Ring 8, Karlsruhe, Germany

^q University of Washington, Seattle, WA, USA

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.

This article is part of the themed collection: Accelerate Conference 2022

Digital Discovery

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

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