AI and Synthetic Biology Are Critical to Future U.S. Competitiveness
On Jan. 11, 2020, Chinese authorities shared the genetic sequence of the virus that causes COVID-19 for the first time. By Jan. 13, the biotechnology firm Moderna had used this information to finalize the design of its vaccine.
This miracle of modern science — shortening to a matter of hours a process that had previously taken months or years — was not a stroke of luck. It was enabled by significant advancements in AI and machine learning, investments in these technologies by industry, and a research base built by decades of U.S. government funding in life sciences and biotechnology. AI is transforming the biotechnology sector, and the U.S. government should take bold steps now to realize the important influence AI will have on the sector’s overall potential, and ensure the United States leads the coming biotechnology revolution.
Biology is now programmable. Dramatic decreases in the cost of DNA sequencing and synthesis over the past few decades have provided scientists with the ability to read the code of life, and technologies such as the CRISPR gene editing tool have given scientists the ability to alter it. However, scientists’ ability to read and write DNA has until now been constrained by their relative ignorance about what genetic data drives which physical outcomes. AI is finally giving them the ability to understand it.
Biology is complex — in humans alone, trillions of cells interact with and instruct each other. The knowledge we have about cells and the interactions between them has been acquired using relatively inefficient and slow processes. Traditionally, knowledge of biology is gathered using empiricism or discovery, including the scientific method. There is a lot of trial and error — and it’s a slog.
The potential for AI to provide insights from large biological data sets is transforming the field of biology. Improved methods of reading biological data, including sequences and quantities of DNA, RNA, and proteins, enable the collection and storage of large quantities of information about some of the smallest biological structures and functional units. Advanced computational techniques such as self-training AI programs have the potential to analyze this information to rapidly find subtle and unique patterns and biological functionality in ways that human trial and error cannot. Essentially, AI will help humans make better sense of how biology works.
Better knowledge ushers in biological simulation and prediction, facilitating a design, build, and test model for developing products based on biology that is repeatable, less expensive, more precise, and faster than ever. By giving us better models of cells and larger biological systems, AI introduces the opportunity to test different biological outcomes before construction, moving the product development process from experimentation to engineering. Furthermore, as scientists improve their understanding of how biology fundamentally works, they can use this knowledge to build new products with specific functionality. As computing power increases, we can expect greater advancements in synthetic biology and a range of products based on biology.
Advances in biotechnology over the next 10 years are estimated to have a direct economic impact of up to $4 trillion per year. Combined with synthetic biology techniques, AI will enable the production of exotic materials, from more sustainable and animal-free meat, to cleaner fuels, to synthetic organs. Biotechnology could also help make our supply chains more resilient by enabling us to produce raw materials domestically for textiles, alternatives to petroleum-based products, and a range of other consumer goods such as household products and electronics, rather than sourcing them internationally. It could also create environmentally friendly fertilizers, improve the readiness of our military, and help create solutions to monitor for biological threats.
Given these trends, the National Security Commission on Artificial Intelligence, which I co-chair, identified biotechnology as one of seven emerging technologies that will be critical to future national competitiveness. At the same time, it also recognized that there is a dark side to biotechnology, labeling AI-enabled biotech threats such as precisely engineered pathogens as one of the five most significant AI-related threats to the United States.
While the United States is the current leader in biotechnology, China is aggressively chasing U.S. leadership and is investing heavily in science and technology research and development more broadly. In 2018, China ranked second in the world in R&D spending, with an estimated $463 billion — nearly 84 percent of total U.S. public and private spending on R&D that year. China has launched the world’s largest precision medicine initiative and is constructing one of the world’s biggest genetic databases. BGI Group, the Chinese de facto national champion in genomics, has become an industry leader in genetic sequencing and research. BGI may be serving, wittingly or unwittingly, as a global collection mechanism for Chinese government genetic databases, and Chinese diplomats have urged world governments and individual U.S. states to purchase BGI-built COVID-19 testing kits, empowering BGI (and by extension the Chinese government) to analyze and retain the entire genome of every person it tests for COVID-19. Additionally, BGI has simultaneously pursued research into topics that run afoul of bioethical norms in many countries, such as the genetic basis for human intelligence.
Should the United States lose leadership to China in biotechnology innovation or manufacturing, it risks becoming dependent on China for key materials and products that will define the future economy — a scenario that carries clear national security risks.
The U.S. government ought to view its AI and biotechnology strategies as mutually reinforcing, with each requiring sustained government focus and commitment. In the National Security Commission on Artificial Intelligence’s Final Report to Congress, it specifically called for the United States not only to raise the profile of biosecurity and biotechnology issues inside the U.S. government, but also to invest in the key biotechnology R&D platforms that will be essential for future national competitiveness. We recommend transforming GenBank, the leading U.S. genetic database, into a world-class biobank to facilitate new levels of AI-enabled analysis of genetic data. And we urge the government to actively support the development of an advanced biotechnology manufacturing ecosystem in the United States to increase the resiliency of our biotech supply chains.
The U.S. government should adopt the commission’s recommendations by developing and incorporating synthetic biology into the U.S. national security and defense toolkit. These steps will help guide the conversation around a variety of topics, including attracting investment, maintaining U.S. competitiveness, educating the next generation of bioengineers, managing biological risks, and integrating new biological applications into the defense industrial base.
The coming biotechnology revolution will be driven by AI and has the potential not only to facilitate dramatic improvements in energy and environmental sustainability, raw materials sourcing, supply chain resilience, food production, military readiness, biodefense, and human health, but also to create new threats and alter geopolitical power structures. The United States should recognize the interconnected nature of these technologies and mobilize while the biotechnology revolution is still young and U.S. leadership is still in hand.
Bob Work is the co-chair of the National Security Commission on Artificial Intelligence, an independent commission established to make recommendations to the president and Congress on how to advance AI to meet the national security and defense needs of the United States. He is the former deputy secretary of defense and former under secretary of the Navy.