What happens when AI begins to design viruses?
The Stanford experiment does not show that AI can casually manufacture dangerous human viruses; it shows that computers are beginning to move from analysing biological information towards proposing biological designs that scientists can physically build. This requires appropriate governance and safeguards
When artificial intelligence (AI) begins to design viruses, it can help determine the genetic makeup of bacteriophages, which are viruses that infect bacteria. Researchers at Stanford University and the Arc Institute utilized AI to generate complete genomes of bacteriophages and physically synthesized and tested 285 AI-designed designs in the laboratory. Out of these, 16 produced functioning phages that could overcome bacterial resistance that defeated the original virus.
However, it is important to note that AI has not created viruses from scratch; humans have been synthesizing viral genomes and intentionally modifying viruses for decades. The new element is that AI is entering the design stage of biology. This development brings both promising opportunities and significant concerns.
Bacteriophages, or "bacteria eaters," have been known for over a century and are abundant in nature. In 1977, ΦX174 was the first complete DNA genome to be sequenced. Scientists have since learned to read, write, and even modify viral genomes. Previously, researchers searched nature and phage libraries for suitable phages or modified existing viruses. However, AI has the potential to design phages needed for specific treatments.
The immediate application of AI-designed viruses may be phage therapy, which could become more effective in treating antibiotic-resistant bacteria. The Stanford-Arc experiment demonstrated that AI-designed phages could overcome resistance in E. coli strains against which the original ΦX174 failed. This development is particularly significant for clinicians facing antibiotic resistance.
Moreover, AI can also aid in designing vaccine antigens, antibodies, therapeutic proteins, and viral vectors for delivering genetic treatments. In the long run, AI could optimize oncolytic viruses that target cancer cells.
While the AI-designed phage ΦX174 is a simple bacteriophage, the potential biosecurity concern lies in AI's capability to amplify the effectiveness of well-equipped laboratories in designing biological systems. The question is not whether an untrained individual can use AI to generate a pandemic virus, but whether AI can make a knowledgeable and well-equipped laboratory substantially more effective in designing biological systems.
Written by urgent.news from The Hindu Health's reporting — not their text. Machine-written — it may contain errors, so check the original before relying on it.
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