Nuclear Deep Fakes
Nuclear power’s deep fake was launched 75 years ago, quite deliberately, using public opinion manipulation tools that were primitive compared to those available today.
The image above is of the “Geiger Counter plant,” KU9 Spiderwort. I have been propagating this strain in my garden from the original clone I obtained from its creator in 1977. It has an uncommon tolerance to heat and cold, reappearing as a perennial despite extremes of minus 25°F in winter and 120°F in summer. This makes it especially well adapted to rapid climate change.
Tradescantia nonukes, var. Ichikawa (1977), also known as Tradescantia x 'KU9', was called "the most excellent test system ever known for low-level radiation" by Japanese geneticist Sadao Ichikawa, part of the team at Brookhaven National Laboratory on Long Island that developed this monitoring system in the late 1960s. Unlike its more common counterparts bred for the beauty of their flowers, this particular cultivar was bred to serve as a natural, biological Geiger counter.
'KU9' has segmented stems with grassy blades and produces blue, three-petaled flowers. When exposed to radiation, the blue cells of the single-cell strand stamen hairs turn pink. The increase in pink cells is proportional to the dose of radiation received, even at extremely low levels. Cell counts can be accurately correlated to Seiverts, a measure of the biological effect of radiation exposure. The KU9 is a hybrid of Tradescantia paludosa and Tradescantia ohiensis. The color change can be observed most efficiently about 12 or 13 days after radiation exposure.
Engineering Fakery
In my posts throughout April, I applied AI engines—Chat GPT, Perplexity, Gemini, CoPilot—to a largely unnoticed report released at the start of the month by the United States Inspector General and to the 2024 US presidential election. The fantastical writing engines drew upon the styles of James Thurber and Mark Twain to make it more fun to read—no more Robbie the Robot or Alexis.
The Government Accountability Office had been asked by Senator Joe Manchin to investigate the vulnerability of the nation’s nuclear reactors to climate change. Manchin, a millionaire Senator whose fortune in West Virginia was built on exploiting the dirtiest form of coal, is neither a strong believer in climate change nor in the future of nuclear power. The subject, however, needed research—Manchin had that right—and as might be expected, the release of the GAO report stirred controversy, although perhaps less than is required.
Private companies own nearly all nuclear power plants in the United States. As of August 2023, the United States had 93 operating commercial nuclear reactors with an average age of about 42 years old, according to the U.S. Energy Information Administration. These reactors are located at 54 nuclear power plants in 28 states. In addition, as of July 2023, there were 21 shutdown plants that have spent nuclear fuel stored onsite in spent fuel pools or in dry casks.
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When a company decides to shut down a nuclear power plant permanently, the facility must be decommissioned by safely removing it from service and reducing residual radioactivity to a level that permits release of the property and termination of the operating license. NRC regulates the decommissioning a nuclear power plant and any spent nuclear fuel that will remain on site.
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Spent nuclear fuel is the fuel that has been removed from commercial nuclear power reactors after it has been used to produce electricity. Spent nuclear fuel is initially stored immersed in pools of water designed to cool and isolate it from the environment. Water circulates in the pools to remove the heat generated from the radioactive decay. Industry practice has been to store the spent nuclear fuel in these pools for at least 5 years or until the fuel has cooled enough to be transferred to dry cask storage. Dry cask storage consists of a steel canister that holds the fuel assemblies, protected by an outer cask made of steel and concrete designed to cool the fuel and provide shielding from its radiation.
—GAO-24-106326: Nuclear Power Plants
The GAO concluded that "NRC actions taken to address risks to nuclear power plants from natural hazards post-Fukushima did not fully consider the effects of climate change.” The NRC replied that the GAO recommendations are consistent with actions that are either underway or under development.
Fakin’ It, Not Makin’ It
What the report revealed was not so much new risks to nuclear energy but rather how easy it has been to manipulate public opinion into ever thinking nuclear power was safe, clean or cheap.
Ukraine’s Zaporizhzhia nuclear power plant was directly targeted by the Russian military drones on 7 April 2024, leading experts to raise the alarm about the risks of attacking hazardous infrastructure assets.
The plant is Europe’s largest, and it became the first operating civil nuclear power plant to come under armed attack on 4 March 2022, soon after the start of Russia’s invasion of Ukraine.
— Tom Pashby, New Civil Engineer, April 10, 2024
Artificial intelligence (AI) technology, working as expert guidance and quick access to a broad knowledge base, may resolve most of the complexities. Hence, experts believe that AI can be the expert system for operating a complex technology like the nuclear power plant. Nevertheless, AI deployment in the energy sector can also introduce several risks and challenges, including physical damage to the power plant.
—Karim et al (2023)
The transition to digital systems brings with it new risks and vulnerability to new interconnects of system components, potential operational issues, and vulnerabilities from cyber-attack that must be assessed and addressed.
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There are several reasons why the cyber security of nuclear energy is essential to national security. Adversaries may attempt a cyber-attack on a nuclear power plant to access individual expertise, documented information, technology (hardware and software), and nuclear materials. Their goal may be to use a cyber-attack to create a physical outcome to disrupt power, create a radiological release, or increase the threat of nuclear proliferation. Consequences associated with these risks include political damage, loss of public confidence, coercion of interests, environmental damage, economic damage, and casualties.
—Pickering and Davies (2021)
AI technical challenges include the performance of specific AI systems, complex and unpredictable interactions among AI systems operating in a system of systems, shortcomings in AI training data, poor alignment between AI tools and tasks, and adversarial action against AI systems. These challenges could cause AI to perform unpredictably, increasing nuclear risk.
Human interface challenges include calibrating appropriate human trust in AI, unskilled use of AI by operators, skills degradation, and decision-time compression. All of these challenges degrade the effectiveness of human-machine teaming associated with AI applications.
Risks from leader calculus result from the difficulty of assessing how AI could impact the military balance.
—Center for Naval Analysis (2023)
“My jaw dropped at so much of what I learned, which was not classified but had just been removed or rather sanitized from the public discourse,” she said. “I found myself constantly surprised by the insanity of what I learned, coupled with the fact that it’s all there for the public to know.”
— Borger, J. ‘My jaw dropped,’ The Guardian 31 Mar 24
Nuclear power’s deep fake was launched 75 years ago, quite deliberately, using public opinion manipulation tools that were primitive compared to those available today. But what exists today is primitive in comparison to what will exist in five or ten years.
A recent report from cybersecurity firm SlashNext reveals alarming statistics: since Q4 2022, malicious phishing emails have surged by 1,265%, with credential phishing seeing a 967% spike. Cybercriminals are utilizing generative AI tools such as ChatGPT to craft highly targeted and sophisticated Business Email Compromise (BEC) and phishing messages. The days of poorly composed “Prince of Nigeria” emails in broken English are a thing of the past.
Voices from Beyond the Grave
Billionaire Daniel C. Searle whose wealth came from the pharmaceutical company responsible for Ambien, Metamucil, Dramamine, and the first commercial birth control pill, died in 2007, but his foundation has continued donating millions of dollars to those who advocate against policies to address climate change. The foundation is expected to give another $59 million to those causes in the next 2 years.
As the pace of misinformation picks up, erosion of trusted news sources, polarizing algorithms, and lack of platform accountability are what we see now. What, then, will happen in ten years with the assistance of artificial intelligence and asymmetric cyberwar? I asked Gemini. She replied:
You're right. Here’s what could happen in ten years if these trends continue, amplified by AI and asymmetric cyberwar:
Malicious actors could use AI to target specific populations with misinformation campaigns tailored to their fears and biases. This could exacerbate social divisions and make it difficult to reach a consensus on important issues.
Social media algorithms could become even more adept at keeping people in filter bubbles, where they are only exposed to information that confirms their existing beliefs.
The spread of deepfakes and other synthetic media could further erode trust in traditional news sources. People may become unsure of what to believe, even when they see something with their own eyes.
Foreign adversaries could use AI to launch cyberattacks that disrupt news websites and social media platforms, further sowing confusion and distrust.
There will likely be erosion of cybersecurity and potential for kinetic attacks.
This raises the risk of not just information warfare but potential for causing physical destruction and disruption.
Given what we know about 2016 US presidential election interference by state or non-state hacker groups, it does seem reasonable that:
A large number of state and non-state actors would like to see the United States and its allies' power greatly diminished.
Ruthless imperial cruelty displayed by the US in Cuba, Vietnam, Iraq, Afghanistan, Libya, Syria, Panama and Venezuela has made many countries more nervous about single-power hegemony.
Overt backing of the genocide in Gaza (and most recently vetoing recognition of the State of Palestine by the UN) pushed many previous supporters or neutral players to quietly switch camps. There is a great store of global resentment against the USA now.
Sowing chaos in the US tripartite government system, while threatening international stability, is much more damaging to the US internally. After surviving 4 years of Trump, those with socio-cyberwar capability may find the risk of global destabilization an acceptable tradeoff for US destabilization and ruin. The US has long demonstrated its ability to internally destabilize democracies, so we know the strategy works.
The average USAnian has been persuaded that both Russia and China are equal threats—destabilizing the dollar, saber rattling, imposing undemocratic systems on neighbors, and stealing secrets. But although Russia would benefit from a more chaotic world order—as an exporter of vital raw materials whose prices soar whenever the global economy is in trouble—China would not. China depends on the trade of manufactured goods, which depends on global stability, especially stability within the US. It benefits China most to have a even-keeled trading partner with moderate, but tempered, political wrangling.
Russia actually benefits from global instability and tension because whenever that happens the prices of commodities, particularly oil, go up. So it almost has a structural reason to be a spoiler, whereas the Chinese are the opposite. They are a low-resource economy and they depend on global capital, global investment, global markets and they have benefitted enormously from that process.
—Fareed Zakaria, Freakonomics Radio # 583
It was very easy for me, with a few prompts, to depict multiple realistic meltdown scenarios for nuclear power plants afflicted by climate change. Gemini, Perplexity, and Chat GPT are not perfect or hallucination-free, but neither are most of the bloggers on Substack or WordPress.
Or, for that matter, the correspondents at most mainstream news outlets.
Holding the Tiger by the Tail
“Several years ago, Amazon set an ambitious goal to reach net-zero carbon by 2040—ten years ahead of the Paris Agreement. As part of that goal, we’re on a path to power our operations with 100 percent renewable energy by 2025—five years ahead of our original 2030 target,” an Amazon spokesperson said.
That was before Amazon Web Services started building AI gigafarms. A normal data center needs 32 megawatts of power. An AI data center needs 80 megawatts, at least. AWS just purchased a 1200-acre, 960-megawatt data center in Pennsylvania that adjoins an existing 2500-megawatt nuclear plant on the Susquehanna River. While AWS will immediately acquire 38% of the plant’s output, in five years that demand could triple.
In the strange circularity of this power grab, nuclear power needs AI to protect it from AI cyberattacks, while AI data centers need nuclear power to propel expansion. As AI proliferates, so too does nuclear power, and vice-versa.
What could possibly go wrong?
References
Center for Naval Analysis, AI and Nuclear Operations: Identifying and Mitigating Risks, IMM-2023-U-034812-FINAL (2023)
Hashmi, Shahrukh K., et al. "Radiation hazards of the Ukraine nuclear power plants: how can international blood and marrow stem cell transplant societies help?." Annals of Hematology 103.4 (2024): 1121-1129.
Familoni, B.T., 2024. Cybersecurity challenges in the age of AI: theoretical approaches and practical solutions. Computer Science & IT Research Journal, 5(3), pp.703-724.
Jureńczyk, Ł., 2022. The Risk of Russia Using Nuclear Weapons Due to the War in Ukraine from the American Perspective. Środkowoeuropejskie Studia Polityczne, (4), pp.49-64.
Karim, R. and Muhammad-Sukki, F., 2023. Artificial intelligence (AI) in the nuclear power plants: who is liable when AI fails to perform. In The Handbook of Energy Policy (pp. 587-607). Singapore: Springer Nature Singapore.
Ma, Z. et al., U.S. Nuclear Industry Survey on Artificial Intelligence and Machine Learning in Operating Nuclear Plants, U.S. Nuclear Regulatory Commission (2023)
Pickering, S.Y. and Davies, P.B., 2021. Cyber security of nuclear power plants: US and global perspectives. Georgetown Journal of International Affairs.
Przybylak, J., 2024. Nuclear power plants in war zones: Lessons learned from the war in Ukraine. Security and Defence Quarterly, 46(2).
Rathnayake, D. 2024. Cybersecurity in the Age of AI: Exploring AI-Generated Cyber Attacks, Forta Tripwire.
Sethi, M., 2022. Nuclear Overtones in the Russia-Ukraine War. Arms Control Today, 52(5), pp.12-15.
Sokolski, H.D., 2022. Present Danger: Nuclear Power Plants in War. The US Army War College Quarterly: Parameters, 52(4), p.8.
Vicente, A., Sinovets, P. and Theron, J. eds., 2023. Russia's War on Ukraine: The Implications for the Global Nuclear Order. Springer.
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