For over a decade, computer scientist Randy Goebel and his colleagues in Japan have been using a tried-and-true method from his field to advance artificial intelligence in the world of law: a yearly competition.

Drawing on example legal cases taken from the Japanese bar exam, contestants must use an AI system that can retrieve statutes relevant to the cases, and, more crucially, make a decision: did the defendants in the cases break the law, or not?

It’s this yes/no answer that AI struggles with the most, says Goebel—and it raises questions of whether AI systems can be ethically and effectively deployed by lawyers, judges and other legal professionals who face giant dockets and narrow time windows to deliver justice.

The contest has provided the foundation for a new paper in which Goebel and his co-authors outline the types of reasoning AI must use to “think” like lawyers and judges, and describe a framework for imbuing large language models (LLMs) with legal reasoning.

The paper is published in the journal Computer Law & Security Review.

“The mandate is to understand legal reasoning, but the passion and the value to society is to improve judicial decision-making,” Goebel says.

The need for these kinds of tools has been especially critical since the Supreme Court of Canada’s Jordan decision, Goebel says. That decision shortened the length of time prosecutors have to bring a case to trial, and it has resulted in cases as severe as sexual assault and fraud being thrown out of court.

“It’s a very good motivation to say, ‘Let’s enable the judicial system to be faster, more effective and more efficient,'” Goebel says.

Making machines ‘think’ like lawyers

The paper highlights three types of reasoning AI tools must possess to think like legal professionals: case-based, rule-based and abductive reasoning.

Some AI systems, such as LLMs, have proven adept at case-based reasoning, which requires legal experts to examine previous court cases and determine how laws were applied in the past to draw parallels to the current case in question.

Rule-based reasoning, which involves applying written laws to unique legal cases, can also be completed to some extent by AI tools.

But where AI tools struggle the most is with abductive reasoning, a type of logical inference that involves stringing together a plausible series of events that could explain, for example, why a defendant is not guilty of a crime. (Did the man with the knife in his hand stab the victim? Or did a gust of wind blow the knife into his hand?)

“Not surprisingly, abductive reasoning can’t be done by modern large language models, because they don’t reason,” Goebel says. “They’re like your friend who has read every page of Encyclopedia Britannica, who has an opinion on everything but knows nothing about how the logic fits together.”

Combined with their tendency to “hallucinate,” or invent “facts” wholesale, generic LLMs applied to the legal field are at best unreliable and, at worst, potentially career-ending for lawyers.

The important challenge for AI scientists is whether they can develop a reasoning framework that works in conjunction with generic LLMs to focus on accuracy and contextual relevance in legal reasoning, Goebel says.

No one-size-fits-all AI tool

When will we have AI tools that can cut the work of lawyers and judges in half? Perhaps not any time soon.

Goebel says a key takeaway from the competition, and one that is also outlined in the paper, is that using computer programs to aid legal decision-making is relatively new, and there is still a lot of work to be done.

Goebel foresees many separate AI tools employed for different types of legal tasks, rather than a single “godlike” LLM.

Claims made by some in the AI industry that humanity is on the cusp of creating an AI tool that can render “perfect” judicial decisions and legal arguments are absurd, Goebel says.

“Every judge I’ve spoken to has acknowledged there is no such thing as perfect judgment,” he says. “The question is really, ‘How do we determine whether the current technologies provide more value than harm?'”

President Donald Trump and the Republican Party have spent the better part of the president’s second term radically reshaping the federal government. But in recent weeks, the GOP has set its sights on taking another run at an old target: the US census.

Since the first Trump administration, the right has sought to add a question to the census that captures a respondent’s immigration status and to exclude noncitizens from the tallies that determine how seats in Congress are distributed. In 2019, the Supreme Court struck down an attempt by the first Trump administration to add a citizenship question to the census.

But now, a little-known algorithmic process called “differential privacy,” created to keep census data from being used to identify individual respondents, has become the right’s latest focus. WIRED spoke to six experts about the GOP’s ongoing effort to falsely allege that a system created to protect people’s privacy has made the data from the 2020 census inaccurate.

If successful, the campaign to get rid of differential privacy could not only radically change the kind of data made available, but could put the data of every person living in the US at risk. The campaign could also discourage immigrants from participating in the census entirely.

The Census Bureau regularly publishes anonymized data so that policymakers and researchers can use it. That data is also sensitive: Conducted every 10 years, the census counts every person living in the United States, citizen and noncitizen alike. The data includes detailed information like the race, sex, and age, as well the languages they speak, their home address, economic status, and the number of people living in a house. This data is used for allocating the federal funds that support public services like schools and hospitals, as well as for how a state’s population is divided up and represented in Congress. The more people in a state, the more Congressional representation—and more votes in the Electoral College.

As computers got increasingly sophisticated and data more abundant and accessible, census employees and researchers realized the data published by the Census Bureau could be reverse engineered to identify individual people. According to Title XIII of the US Code, it is illegal for census workers to publish any data that would identify individual people, their homes, or businesses. A a government employee revealing this kind of information could be punished with thousands of dollars in fines or even a possible prison sentence.

For individuals, this could mean, for instance, someone could use census data without differential privacy to identify transgender youth, according to research from the University of Washington.

The USS Gerald R. Ford, the US Navy’s most advanced aircraft carrier, is heading to the Caribbean Sea as part of a Pentagon strategy it says is meant to strengthen the fight against drug trafficking in South America.

The news was confirmed late last week by Sean Parnell, assistant secretary of defense for public affairs, through his social networks. In his message, he explained that the deployment of the Gerald R. Ford “will strengthen the United States’ ability to detect, monitor and dismantle illicit actors and activities that compromise the security and prosperity of US territory, as well as our stability in the Western Hemisphere.” Until now, only combat vessels and aircraft had been mobilized in the area.

Since last month, President Donald Trump’s administration has maintained a campaign in Caribbean waters aimed at combating drug trafficking, arguing that the activity of various criminal organizations puts the security of the American people at risk. In recent weeks, the US armed forces have targeted several vessels and accused their operators of transporting drugs, a situation that has increased US diplomatic tensions with nations such as Venezuela and Colombia.

The dispatch of the Ford represents an escalation of Washington’s military activity in the region, which, according to specialists, could further increase hostilities.

The Ford has been described as the most advanced and expensive in the world. Its construction had an estimated value of $13 billion, according to military industry press. It is the first of a new generation of aircraft carriers destined to replace the Nimitz class, which since the 1970s has been the mainstay of the US fleet.

The site Naval Technology explains that the Ford class comprises nuclear-powered aircraft carriers, developed by the Newport News Shipbuilding division of Huntington Ingalls Industries for the US Navy as part of the CVN-21 Aircraft Carrier Program.

Bring in the Big Guns

Compared to the Nimitz class, the USS Gerald R. Ford incorporates 23 new or improved systems that optimize transportation, communication, tracking, operational performance, weight tolerance and stability functions, among other aspects.

The ship displaces nearly 100,000 tons, is 333 meters long and 40.8 meters wide, and has a flight deck 78 meters wide. One of its main innovations is its advanced nuclear propulsion system, which improves power generation and distribution by 150 percent over its predecessors. This system, developed by Northrop Grumman, is composed of two reactors, four shafts, and a zonal electrical distribution system, allowing it to sail for up to 20 years without refueling.

The ship operates with the Electromagnetic Aircraft Launch System, considered its greatest innovation. This mechanism replaces the traditional steam catapults with a linear electromagnetic accelerator motor, which improves control in the acceleration of manned and unmanned aircraft. In practice, it allows vehicles to be launched at higher speeds, with heavier weaponry or more fuel, extending their range, coverage, and lethality.