(The Epoch Times)—Whether it’s driving a car or summarizing a doctor’s appointment, autonomous artificial intelligence (AI) systems can make decisions that cause real harm, rapidly changing the landscape of liability.
Attorneys and AI developers say U.S. laws must keep up with the technology as debate persists over who’s responsible when things go wrong.
Lawmakers are looking to close the accountability gap by shifting burdens and expanding who can be held accountable when autonomous AI systems fail. Unlike non-autonomous AI systems, autonomous models are more likely to be unpredictable.
In the United States, a legal patchwork is slowly forming. In 2024, Colorado passed a law, Consumer Protections for Artificial Intelligence, requiring those deploying “high-risk” AI systems to protect consumers from “reasonably foreseeable risks” starting Feb. 1, 2026.
Since 2023, New York has enforced a law that prohibits employers and employment agencies from using automated employment decision tools unless they have undergone a bias audit within one year of the tool’s use. The results of the audit must be made public.
Presently, there’s no concrete federal legal foundation that demonstrates clear-cut accountability when autonomous AI systems fail, prompting some legal experts to say there must be greater transparency.
“For centuries, legal frameworks for assigning liability have relied on well-established principles designed for a human-centric world,” Pavel Kolmogorov, founder and managing attorney at Kolmogorov Law, told The Epoch Times.
Kolmogorov said that cases of negligence require proof of a breach of “duty of care.” Liability related to products holds manufacturers responsible for defects or design flaws. However, both scenarios assume there’s clear human oversight and relatively static, predictable tools.
“Autonomous AI systems fundamentally disrupt this paradigm,” Kolmogorov said. “Their defining characteristics—complexity, operational autonomy, and the capacity for continuous learning—create profound challenges for applying these traditional legal concepts.”
He also said AI’s “black box” problem, where even developers can’t fully explain the specific reasoning behind an AI’s decision, makes it extraordinarily difficult to pinpoint a specific breach or defect in the traditional sense.
Kolmogorov gave an example of a legal quagmire: “When an autonomous vehicle makes a fatal error, was it due to a flaw in its original code, a limitation in its training data, an unpredictable emergent behavior learned over time, or some combination thereof?”
Autonomy in Action
The idea of AI driven cars running people down in the streets is no longer a sci-fi concept. The landmark 2018 case involving a self-driving Uber vehicle that struck and killed a pedestrian in Tempe, Arizona, was the first recorded fatality involving a fully autonomous vehicle. The human passenger, or “backup” driver, was ultimately charged with negligent homicide.
This was far from an isolated incident. Between 2019 and 2024, there were 3,946 autonomous vehicle accidents, according to the Craft Law Firm. Of these cases, 10 percent caused injury and 2 percent resulted in fatalities.
“Right now, the law still treats autonomous driving systems under traditional negligence and product liability principles,” a representative for Valiente Mott Injury Attorneys told The Epoch Times.
“If a driver is expected to monitor the system and fails to intervene, they can be held responsible for negligence. But if the technology itself is defective or marketed in a misleading way, the manufacturer may face liability. In many cases, fault can be shared. We’re essentially applying old legal standards to new technology until the law catches up.”
The representative added that current laws were written with human drivers in mind.
“As autonomy increases, legislatures and courts will need to define how responsibility is allocated between human operators, manufacturers, and possibly even software developers.”
This ambiguity leads to what Kolmogorov called “responsibility fragmentation.”
“Unlike a simple tool with a single manufacturer and operator, an AI system is the product of a long and complex supply chain,” he said. “When a failure occurs, attributing liability becomes an exercise in untangling a dense web of dependencies, making it difficult for a victim to identify the appropriate defendant.”
This autonomous AI supply chain can include data suppliers, software developers, hardware manufacturers, system integrators, and end users, each contributing to the final product.
Kolmogorov noted that the driver bore the criminal responsibility in the 2018 Uber case, but on the civil end, legal experts said Uber had strong liability exposure that could qualify as negligence and product liability.
“The case exposed the split between criminal versus civil standards. The former requires intent or recklessness, while the latter hinges on design and testing failures,” Kolmogorov said.
Similarly, Tesla’s Autopilot has been tied to multiple crashes, including a 2019 fatality in Florida. This August, a jury found Tesla partially liable, saying its AI system contributed to the accident alongside driver negligence.
Autonomous AI systems with the ability to cause harm aren’t limited to self driving cars. Mostly autonomous “agentic” AI models are being integrated into nearly every sector of the United States, from health care to manufacturing, logistics, software, and the military.
Avoiding Hazards
Researchers at IBM have called 2025 the year of the AI agent. At a glance, agentic AI includes mostly autonomous systems that can act independently to achieve goals with minimal human oversight.
Some AI experts, including David Talby, CEO of John Snow Labs and chief technology officer at Pacific AI, believe AI agents can have quality of life impacts as models advance and become increasingly independent of human involvement.
“Health care stands out as one of the most demanding domains. Unlike consumer applications or even some enterprise use cases, AI in health care directly impacts people’s lives and well-being,” he told The Epoch Times.
Talby said many autonomous AI systems already exist in health care, including digital health applications that interact directly with patients, clinical decision support systems, and visit summarization tools that work alongside doctors.
“These systems can independently process complex medical data, draft clinical notes, or guide patients in self-care, but it’s important this is always under a human-in-the-loop framework of accountability,” he said. “While parts of the workflow are fully automated, human oversight is still needed in health care and beyond.”
Talby added that errors can have profound consequences and accountability must extend past accuracy metrics. Issues such as bias in medical datasets, robustness under real-world variability, and adherence to ethical standards all demand what he called “rigorous governance.”
“In health care, our top concerns extend beyond model accuracy. We must ensure that AI systems are not only effective but also safe, transparent, and compliant with regulations,” Talby said.
Kolmogorov said “physicians face dual risks” as AI diagnostic tools become more accurate in health care. They face “negligence for not using validated AI and negligence for over-relying on flawed recommendations.”
He said patients should be informed when AI is used. “And data representativeness is crucial to avoid bias.”
This year, AI developers from Hugging Face, a machine learning company, published research that advocated against deploying fully autonomous AI agents. The article stated, “Risks to people increase with the autonomy of a system: The more control a user cedes to an AI agent, the more risks to people arise.”
In July, the White House unveiled its AI Action Plan, which outlined infrastructure building, investment, and defense initiatives. However, this plan does not address the legal gray areas that remain as autonomous AI continues expanding its reach.
European lawmakers face similar challenges and currently treat AI as a product under its Product Liability Directive, which extends liability to post-sale changes, such as model updates or new machine-learned behaviors.
“I regularly advise clients in emerging tech and mobility sectors on AI autonomy risk,” Kolmogorov said. “The focus is on mitigating exposure before a failure becomes a legal crisis.”
Bypass Big Tech Censors
Two Storms, One Harvest
Every food crisis in living memory has been a one-shock event. The 2008 price spike was a commodity bubble. The 2020 shortages were a logistics failure. The 2022 grain scare was a war on one exporter’s ports. Each time, the system bent, adjusted, and recovered, and each time the experts assured us afterward that global markets are simply too big and too diversified to fail.
What nobody in Washington seems eager to discuss is that 2026 is shaping up to be something the modern food system has never actually faced. Two independent shocks, one climatic and one geopolitical, are converging on the same harvest cycle at the same time. Not sequentially. Simultaneously.
Start with the weather. The Pacific Ocean is currently building toward what forecasters now openly call a record event. NOAA’s Climate Prediction Center puts the odds of at least a strong El Niño near 88 percent, with roughly two in three odds it reaches “very strong” status, the tier reserved for perhaps three or four events in the entire satellite era. Every major global model now projects a median peak in Super El Niño territory, and most of them project it exceeding the 2015-16 event, which until now held the modern record. Sea surface anomalies were already brushing the super threshold in mid-July, months before these events normally peak. The atmosphere has already shifted into El Niño mode, and the event is forecast to crest in late fall and early winter.
This is not about “climate change.” It’s about the standard cycles of weather, and the cycle we’re currently in is one that has likely devastated societies in the past. We’re better prepared as a society today, but not all Americans are equally prepared.
Serious households have started doing the quiet math on their own. Grocery bills tell part of the story, and the forecast maps tell the rest, which is why long-term food storage has moved from fringe hobby to mainstream line item in the family budget, with established suppliers like Heaven’s Harvest seeing demand from people who five years ago would have rolled their eyes at the idea. That instinct is not paranoia. It is pattern recognition, and the pattern is worth walking through carefully.
Editor’s Note: Heaven’s Harvest IS a sponsor, but the warnings of this article are real and would be written even if we didn’t have a survival food sponsor. With that said, those who take advantage of what they offer can use promo code “Patriot” for 15% off.
The Fertilizer Clock Is Already Running
While the Pacific warms, the second shock has been unfolding in the Strait of Hormuz. The conflict with Iran turned the world’s most important energy chokepoint into a contested waterway, and the consequences reach far beyond the gas pump. Roughly a third of global fertilizer trade moves through Hormuz, and the disruption sent urea prices up 86 percent year over year by March, with a 53 percent jump in a single month.
The World Bank projects energy prices rising about 24 percent in 2026 and fertilizer about 31 percent. By its own accounting, fertilizer prices ran 35 percent higher in the first five months of this year than the same period last year.
Here is the mechanism the nightly news will not explain. Fertilizer is not a grocery item. It is a time-delayed input. The nitrogen a farmer in Iowa or Punjab could not afford to apply this spring does not show up as a problem this spring. It shows up as a thinner harvest six to twelve months later.
The World Bank’s own food security brief concedes that the effects of reduced applications earlier this season “are likely to become visible only later in harvest outcomes.” Translate that from institutional language into plain English and it means this. The damage is already done, it is already in the ground, and we are simply waiting for it to arrive on the shelf.
Now check the calendar. Six to twelve months from the spring planting season lands us squarely in late 2026 and early 2027. Which is precisely when the strongest El Niño in the instrumental record is forecast to peak, bringing its signature droughts to Southeast Asia, Australia, southern Africa, northern Brazil, and South Asia, the very regions that grow the world’s rice, sugar, and oilseeds.
The World Bank warns openly that a strong El Niño “could disrupt multiple crop belts simultaneously” on top of the conflict-driven input costs. Their baseline projection assumes the Middle East disruptions ease by autumn. What in the last two years of Middle East history suggests that assumption is safe?
The System Has No Slack Left
The comfortable answer is that global markets always adjust. But adjustment requires slack, and the slack is gone. Global cereal production is expected to decline from last year’s records even before El Niño does its work. The UN World Food Programme, hardly a den of right-wing preppers, is calling this the most significant disruption to its supply chains since Covid and the invasion of Ukraine, and its supply chain director put the stakes bluntly.
Today’s supply chain challenges are tomorrow’s hunger crisis.
There is also a political dimension that markets cannot price. When food gets scarce, governments do not behave like economists. They behave like politicians. Export bans, hoarding mandates, and panic buying at the national level turned the modest rice shortfall of 2008 into a global crisis, and analysts are already warning that import-dependent nations are the first dominoes.
The 2015-16 Super El Niño, a far weaker event than what is now forecast, threw tens of millions into food stress across Africa and Asia. This one is projected to be stronger, and it arrives with fertilizer already rationed by price and shipping lanes already contested by missiles.
What Joseph Knew
Scripture does not treat preparation for lean years as faithlessness. It treats it as wisdom delivered in advance to those willing to act on it.
Behold, there come seven years of great plenty throughout all the land of Egypt: And there shall arise after them seven years of famine; and all the plenty shall be forgotten in the land of Egypt.
Joseph did not respond to that warning with a hashtag or a committee. He stored grain during the years of abundance, and when the famine came, Egypt stood while its neighbors begged. The lesson is not that famine is certain. It is that the time to prepare is precisely when preparation still looks optional.
Nobody who filled a pantry in a year of plenty has ever regretted it, and nobody standing in an empty aisle has ever been glad he waited for certainty.
None of this calls for panic, and panic is the enemy of sound judgment anyway. It calls for the same unglamorous prudence our grandparents considered ordinary. Keep some cash margin, know your local growers, and put real food in deep storage while it is cheap and available, because the entire arc of this story is that cheap and available is a closing window.
Families looking for a straightforward place to start can visit Heaven’s Harvest and use promo code Patriot for 15 percent off long-term storable food. The forecasts may yet soften, the strait may yet reopen, and we should pray they do. But hope is a fine thing to hold and a foolish thing to eat.
