This paper summarizes key findings and explores opportunities for emerging generative AI tools in biotechnology applications.
ChatGPT and related emerging machine learning-based artificial intelligence (AI) tools have provoked a classic but unusually rapid hype cycle of public interest and doubt in the potential for AI to enable and/or disrupt a variety of economically significant labor roles. The unusual step of providing open public access for people to try these new tools has led to a great deal of speculation—and experimentation—about how such tools might create opportunities and risks.
MITRE hosted a technical exchange meeting (TEM) titled, "Opportunities for generative AI in biotechnology" in June 2023 in McLean, Virginia, with representatives from academia, industry, and government. The TEM focused on the potential for such emerging tools to impact progress in biotechnology based on their abilities to compose novel content, to engage in meaningful and informative dialogue with a human, and to explain ideas. While the impacts overall are unclear, recent progress suggests the potential for substantial disruption in biotechnology, both of positive value (major advances, for example in biomanufacturing and pharmaceutical development) and negative value (risks and dangers, for example in the development of chem-bioweapons capabilities, or sudden destabilization in economic competitiveness and self-sufficiency of the U.S. and its allies).
This paper summarizes key findings, and explores opportunities for emerging generative AI tools in biotechnology applications, including:
- Predictive design of useful biological systems that scale from molecules to organisms,
- Trustworthy and explainable results of AI outputs, including exposed chains of reasoning and references to scientific source literature or other forms of evidence,
- Exploratory mapping and tracking of trends in knowledge in the biotechnology field, and
- Development of conversational AI research assistant software.