The Age of AI in the Life Sciences: Benefits and Biosecurity Considerations

A new Consensus Study Report from the National Academies of Sciences, Engineering, and Medicine is now available: The Age of AI in the Life Sciences: Benefits and Biosecurity Considerations.

A new Consensus Study Report from the National Academies of Sciences, Engineering, and Medicine is now available: The Age of AI in the Life Sciences: Benefits and Biosecurity Considerations. You can read it online here or download the PDF here (free, but registration required).

Figure S-1 from the NAS report: Current capability uplift and limitations of AI-enabled biological tools in two biosecurity risk applications with different levels of design complexity. At present, AI biological models are limited in the capability to accurately model and predict pathogenesis and transmissibility that can be misused to design a virus de novo or modify an infectious agent with the potential for epidemic- or pandemicscale consequences. Future improvements in AI-enabled biological tools and automated laboratories that may either reduce the intensive requirements of experimental validation in building and testing or eliminate the need for testing would represent a significant development in overcoming current bottlenecks and barriers. In contrast, available AI-enabled biological tools are currently capable of designing simple biomolecules such as toxins that may evade security checkpoints, such as nucleic acid synthesis screening.

Here’s the summary:

Artificial intelligence (AI) applications in the life sciences have the potential to enable advances in biological discovery and design at a faster pace and efficiency than is possible with classical experimental approaches alone. At the same time, AI-enabled biological tools developed for beneficial applications could potentially be misused for harmful purposes. Although the creation of biological weapons is not a new concept or risk, the potential for AI-enabled biological tools to affect this risk has raised concerns during the past decade.

This report, as requested by the Department of Defense, assesses how AI-enabled biological tools could uniquely impact biosecurity risk, and how advancements in such tools could also be used to mitigate these risks. The Age of AI in the Life Sciences reviews the capabilities of AI-enabled biological tools and can be used in conjunction with the 2018 National Academies report, Biodefense in the Age of Synthetic Biology, which sets out a framework for identifying the different risk factors associated with synthetic biology capabilities.

And the full table of contents:

• ACRONYMS AND ABBREVIATIONS

• PREFACE

• SUMMARY

• 1 INTRODUCTION

  • The Convergence of AI and Life Sciences

  • Study Scope and Approach

  • Report Organization

• 2 DESIGN-BUILD-TEST-LEARN: IMPACT OF AI ON THE SYNTHETIC BIOLOGY PROCESS

  • Ideation and Design: Large Language Models and Foundation Models

  • Build and Test: Automated Laboratories

  • Learn: Synthetic Data

• 3 AI-ENABLED BIOLOGICAL DESIGN AND THE RISKS OF SYNTHETIC BIOLOGY

  • Addressing Biological Complexity in Design and Engineering

  • Implications for Biosecurity

  • Broader Context for Assessing Biosecurity Risks: The 2018 Framework

• 4 PROMOTING AND PROTECTING AI-ENABLED INNOVATION FOR BIOSECURITY

  • AI-Enabled Infectious Disease Biosurveillance

  • AI-Enabled Biodesign for Countermeasure Development and Emergency Response

  • AI and Biodesign Security

  • Balancing AI-Enabled Responses to Biological Threats and Potential Risks

• 5 IMPORTANCE OF DATA IN AI-ENABLED BIOLOGICAL MODELS

  • Biological Datasets for Training AI Models

  • Infrastructure and Governance

  • The Data Life Cycle and National Repositories

  • Considerations for Building Data Infrastructure

  • Protecting Data Assets for AI-Enabled Biological R&D

  • Data-Driven Vulnerabilities and Mitigations

• APPENDIXES

  • A Mapping the Landscape of AI-Enabled Biological Design

  • B Public Meeting Agendas

  • C Committee Biographies