REFERENCES
- Boiko, D. A., R. MacKnight, and G. Gomes. 2023. Emergent autonomous scientific research capabilities of large language models. arXiv preprint arXiv:2304.05332.
- Bran, A. M., S. Cox, A. D. White, and P. Schwaller. 2023. ChemCrow: Augmenting large-language models with chemistry tools. arXiv preprint arXiv:2304.05376.
- Jumper, J.,. R. Evans, A. Pritzel, T. Green, M. Figurnov, O. Ronneberger, K. Tunyasuvunakool, R. Bates, A. Žídek, A. Potapenko, et al. 2021. Highly accurate protein structure prediction with AlphaFold. Nature 596 (7873):583–9. doi:10.1038/s41586-021-03819-2.
- Madani, A., B. Krause, E. R. Greene, S. Subramanian, B. P. Mohr, J. M. Holton, J. L. Olmos, C. Xiong, Z. Z. Sun, R. Socher, et al. 2023. Large language models generate functional protein sequences across diverse families. Nature Biotechnology 41 (8):1099–106. doi:10.1038/s41587-022-01618-2.
- Meechan, P. J., and J. Potts. 2020. “Biosafety in microbiological and biomedical laboratories.” August 3, 2023. https://www.cdc.gov/labs/pdf/SF__19_308133-A_BMBL6_00-BOOK-WEB-final-3.pdf.
- Sandbrink, J. B. 2023. Artificial intelligence and biological misuse: Differentiating risks of language models and biological design tools. arXiv preprint arXiv:2306.13952.
- Soice, E. H., R. Rocha, K. Cordova, M. Specter, and K. M. Esvelt. 2023. Can large language models democratize access to dual-use biotechnology?. arXiv preprint arXiv:2306.03809.
- Urbina, F., F. Lentzos, C. Invernizzi, and S. Ekins. 2022. Dual use of artificial-intelligence-powered drug discovery. Nature Machine Intelligence 4 (3):189–91. doi:10.1038/s42256-022-00465-9.
- Zhou, J., Y. Zhang, Q. Luo, A. G. Parker, and M. D. Choudhury. 2023. Synthetic lies: Understanding ai-generated misinformation and evaluating algorithmic and human solutions. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1–20.