r/AIDangers

By @ tktollefson

The judge spotted it by eye, and the plaintiff has now lost the right to file anything electronically.

Matthew Elliott, representing himself in Connecticut, hid instructions in tiny white text telling any AI model reviewing his July 24 motion to agree with it. Text extraction pulls every character out of a PDF regardless of color, so invisible lines carry full weight.

The court does not use AI to review records, so nothing read it. The August 6 decision requires all his future filings on paper.

AI has now designed viruses that did not exist before.

Scientists have used AI models trained on the genetic information of about 2 million bacteriophages to design new viral genomes. In the laboratory, 16 of these AI-designed viruses proved viable, and a combination of them successfully killed strains of E. coli that were resistant to naturally occurring bacteriophages.

The potential benefit is enormous: AI could help design highly targeted bacteriophages to fight antibiotic-resistant infections and potentially transform phage therapy.

But the same breakthrough raises an uncomfortable question: if AI can design useful viruses, could it eventually design harmful ones?

The researchers deliberately excluded viruses that infect humans, animals and plants from their training data. Experts also point out that designing a completely new dangerous pathogen is currently far more difficult than modifying an existing pathogen.

Nevertheless, the technology has crossed an important threshold: AI can now generate genetic instructions that can be turned into functioning viruses.

The concern is therefore not that a dangerous virus has been created today, but that our ability to design biology may be advancing faster than our systems for governing it.

Experts argue that safety cannot depend on regulating AI models alone. It will require multiple layers—responsible AI development, research oversight, screening of synthetic DNA, and strong laboratory biosafety and biosecurity.

The question is no longer only what AI can create. It is whether humanity can develop the wisdom and safeguards to decide what should never be created.

Acharya Prashant often warns that knowledge without self-knowledge is potentially dangerous.

This deveopment raises that very question.

AI has now been used to design viruses that did not previously exist. The technology itself is neither good nor evil. It can potentially help us develop new ways of fighting antibiotic-resistant infections. But the same capability, placed in the hands of an ego driven by power, profit, fear, competition or domination, can be directed towards very different ends.

The danger, therefore, may not lie in the tool itself, but in the consciousness of the one who wields it.

As our technological power grows, our capacity to create—and consequently to destroy—grows with it. But if inner understanding does not grow at the same pace, knowledge can become an extraordinarily powerful servant of an ignorant ego.

Perhaps the real question is not merely:

“What can we create?”

but:

“Who is the one creating, and what does he want to do with his creation?”

Without self-knowledge, greater knowledge may simply give the ego greater instruments to fulfil its agenda.

The more powerful the tool, the more dangerous the unconscious user.

https://www.theguardian.com/science/2026/aug/06/safety-fears-as-scientists-make-first-viruses-designed-by-ai?CMP=share\_btn\_url

https://www.science.org/doi/10.1126/science.aec2657

H.R.9925, the FRONTIER Act, establishes federal oversight of frontier artificial intelligence models exceeding a high compute threshold. Introduced July 23, 2026 by Rep. Jay Obernolte (R-CA) with bipartisan cosponsors including Rep. Lori Trahan (D-MA), it requires transparency frameworks, independent audits, and incident reporting for large frontier developers under the Department of Commerce.

The bill interfaces with existing state rules through targeted preemption. It bars states from imposing new substantive obligations on developers specifically for frontier AI risk transparency, third-party verification, and incident reporting. Carve-outs preserve generally applicable laws, deployment rules, and protections for minors.

For states this means limited ability to expand development-side requirements on the largest models. The right in tension is state authority over emerging technology risks. Similar federal preemption efforts have appeared in prior AI drafts.

At scale the measure centralizes catastrophic-risk rules while leaving deployment regulation largely to states. Verify the introduced text and committee referrals. Independent review of the preemption section remains essential before any further action.

Sources

H.R.9925 - 119th Congress (2025-2026): FRONTIER Act

https://www.congress.gov/bill/119th-congress/house-bill/9925

Official bill page confirming introduction date, sponsor Rep. Jay Obernolte, bipartisan cosponsors, and referral to Energy and Commerce and Science committees.

Text - H.R.9925 - 119th Congress (2025-2026): FRONTIER Act

https://www.congress.gov/bill/119th-congress/house-bill/9925/text/ih

Full introduced text containing the precise preemption language in Section 9 limiting state obligations on frontier AI transparency, audits, and incident reporting, plus listed carve-outs.

The FRONTIER Act Explained: What H.R. 9925 Means for Frontier AI Regulation

https://statt.com/blog/frontier-act-federal-ai-regulation-2026/

Details the bipartisan sponsorship, compute threshold for frontier models, and scoped preemption of state development-side rules.

Congress' AI Bill Could Override State AI Laws

https://www.forbes.com/sites/lanceeliot/2026/07/27/federal-ai-laws-that-aim-to-overrule-state-ai-laws-are-getting-on-the-nerves-of-state-lawmakers/

Analyzes Section 9 preemption and its potential interaction with existing state frontier safety statutes such as California’s SB 53.

Where State AI Legislation Stands Half Way Into 2026

https://techpolicy.press/where-state-ai-legislation-stands-half-way-into-2026

Documents that states had enacted 109 AI laws by July 1, 2026, providing context for the volume of measures potentially affected by targeted federal preemption.