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^*, 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

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

4 Citations (Scopus)

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.

Original language	English
Journal	Digital Discovery
Volume	2
Issue number	6
Pages (from-to)	1644-1659
Number of pages	16
ISSN	2635-098X
DOIs	https://doi.org/10.1039/d3dd00143a
Publication status	Published - 16 Oct 2023

Bibliographical note

We are grateful to our peers for their gracious and varied contributions to this work. In particular we would like to thank Tantum Collinsfor his insights around the ethics of AI.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1039/d3dd00143aLicence: CC BY 4.0

Open Access articleFinal published version, 599 KBLicence: CC BY 4.0

https://arxiv.org/pdf/2304.11120.pdfLicence: CC BY 4.0

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Maffettone, P. M., Friederich, P., Baird, S. G., Blaiszik, B., Brown, K. A., Campbell, S. I., Cohen, O. A., Davis, R. L., Foster, I. T., Haghmoradi, N., Hereld, M., Joress, H., Jung, N., Kwon, H-K., Pizzuto, G., Rintamaki, J., Steinmann, C., Torresi, L., & Sun, S. (2023). What is missing in autonomous discovery: Open challenges for the community. Digital Discovery, 2(6), 1644-1659. Advance online publication. https://doi.org/10.1039/d3dd00143a

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title = "What is missing in autonomous discovery: Open challenges for the community",

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.",

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

note = "We are grateful to our peers for their gracious and varied contributions to this work. In particular we would like to thank Tantum Collinsfor his insights around the ethics of AI.",

year = "2023",

month = oct,

day = "16",

doi = "10.1039/d3dd00143a",

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Maffettone, PM, Friederich, P, Baird, SG, Blaiszik, B, Brown, KA, Campbell, SI, Cohen, OA, Davis, RL, Foster, IT, Haghmoradi, N, Hereld, M, Joress, H, Jung, N, Kwon, H-K, Pizzuto, G, Rintamaki, J, Steinmann, C, Torresi, L & Sun, S 2023, 'What is missing in autonomous discovery: Open challenges for the community', Digital Discovery, vol. 2, no. 6, pp. 1644-1659. https://doi.org/10.1039/d3dd00143a

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AU - Rintamaki, Jacob

AU - Steinmann, Casper

AU - Torresi, Luca

AU - Sun, Shijing

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AB - 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.

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

Abstract

Bibliographical note

UN SDGs

Access to Document

AUB Link

Other files and links

Fingerprint

Designing Molecules for Ease of Chemical Synthesis

Accelerate Conference

Accelerate Conference

Cite this

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

Abstract

Bibliographical note

UN SDGs

Access to Document

AUB Link

Other files and links

Fingerprint

Projects

Designing Molecules for Ease of Chemical Synthesis

Activities

Accelerate Conference

Accelerate Conference

Cite this