Don't fear AI-driven "biosurveillance," experts say

Yes, but: The experts Axios spoke to at the AI Expo for National Competitiveness agreed that "biosurveillance" is a label that will repel people. They hope to reframe it as "biosafety" or "bio transparency."

How it works: Collecting better biological data, and running it through AI, "might be the difference between managing a really small outbreak" and "letting it spread and become a much bigger problem," Stephanie Batalis, a Georgetown Center for Security and Emerging Technology fellow, told Axios.

• Governments in poorer countries may need financial support and other incentives to participate in a global system for data sharing and other monitoring of biological threats, Casandra Philipson, director of bioinformatics at Ginkgo Biosecurity, told Axios.
• Even then, information may only be useful if more efforts are made to standardize data, and then train bigger AI models on that data,
• "The challenge is to set up a system that is clear, transparent," Hirsh Jain, head of public health and SVP at Palantir Technologies, told Axios.
• Since biosurveillance "may be happening already" — covertly by adversarial governments — "we want to make sure it's happening above board" and in a way that benefits society, Jain said.

Catch up quick: Biotechnology has rapidly evolved in recent decades, and today researchers are racing to develop AI models for biology to speed up drug discovery.

• Experts Axios spoke to from the Biden administration, the private sector and academia agreed that AI needs to be leveraged to boost defenses against bio attacks and pandemics.

China's urgent efforts to catch up to the U.S. on AI and biotechnology are a particular cause for concern. "All of the most severe risks, as far as man-made biological agents are concerned, are related to China," Bill Drexel, a Sino-American specialist at the Center for a New American Security, told Axios.

• "There's a very long history of China having top-down pushes to leapfrog other countries' technologies that end in tragedy," Drexel said.

Case in point: Aside from the debate about COVID-19's origins, "in 2019 China had the largest major lab leak in history, aerosolized varicella," aka chickenpox, which infected nearly 12,000 people, and in 2004 "one Beijing lab had four SARS outbreaks in two months."

• Meanwhile, "the largest and most sophisticated gene synthesis company not part of the international gene synthesis consortium is also in China," Drexel said.

COVID-19 responses taught us how to take globally coordinated decisions in response to bio threats.

• "CDC, DoD, HHS, the states, the pharma industry, and a whole host of private operators and [foreign] partners all needed to be able to operate off of the same data and make decisions extremely quickly," Jain said.
• But as concern about the pandemic eventually faded, so did funding and motivation to install permanent global systems for monitoring biological threats.
• President Biden's AI Executive Order identifies several biosecurity risks, and includes requirements for closer scrutiny of AI models trained on biological data compared to more general-purpose models.

Reality check: AI can find patterns in large data sets, but collecting good biological data is a challenge, in part because of lack of trust in the governments and large companies that typically handle such biological samples and personal data.

• Some governments may also be reluctant to share data about bio threats, fearing reactions like the plummeting tourism South Africa experienced after it declared a new COVID-19 variant had been identified in the country in November 2021.

What we're watching: The Department of Defense has well-established systems for sharing sensitive intelligence with partner nations, but "there's nothing similar for biological data," Jain said.