Court system on'brink of collapse', former senior judge warns The court system is on the brink of collapse as the backlogs for trials reach unprecedented levels, the head of a major review has said. Sir Brian Leveson, a senior retired judge, warned ministers, the police and others that there could not be a pick and mix response to solving the crisis. Last year, in the first stage of the review, Sir Brian called for the right to a jury trial to be scaled back and many intermediate crimes to be dealt with by a judge alone. His second and final report has recommended 130 efficiency changes, from technical measures to allowing prison vans to use bus lanes to hit court appearance deadlines. Sir Brian's two reports were commissioned by ministers as part of an attempt to reverse the backlogs that had reached record levels before Labour came into power, but have continued to worsen since then.

Artificial intelligence (AI) is advancing quickly and is being adopted in most industries. Using AI to draft an email message or check your grammar is typically not a cause for concern, but using it to make decisions that affect people's lives is another matter. When constitutional rights are involved, as in the justice system, transparency is paramount. During the Biden-Harris administration, Executive Order 14110 directed agencies to develop guidelines for acceptable uses and regulation of AI. Some of these uses, like summarizing and notetaking, will occur across the government.

Tracking devices inserted under offenders' skin, robots assigned to contain prisoners and driverless vehicles used to transport them were among the measures proposed by technology companies to ministers who are gathering ideas to tackle the crisis in the UK justice system. The proposals were made at a meeting of more than two dozen tech companies in London last month, chaired by the justice secretary, Shabana Mahmood, minutes seen by the Guardian show. Amid an acute shortage of prison places and probation officers under severe strain, ministers told the companies they wanted ideas for using wearable technologies, behaviour monitoring and geolocation to create a "prison outside of prison". Those present included representatives of Google, Amazon, Microsoft and Palantir, which works closely with the US military and has contracts with the NHS. IBM and the private prison operator Serco also attended alongside tagging and biometric companies, according to a response to a freedom of information request.

Judges in England and Wales will be able to use the AI chatbot to help write their legal rulings, the Telegraph reports. This is despite ChatGPT being prone to making up bogus cases, and the tool even admitting that it'can make mistakes' on its landing page. ChatGPT, already described by one British judge as'jolly useful', is increasingly infiltrating the legal industry, leading to concern among some experts. The Judicial Office's new official guidance, issued to thousands of judges, points out that AI can be used for summarising large amounts of text or in administrative tasks. These qualify as basic work tasks, but more salient parts of the process – such as conducting legal research or undertaking legal analysis – must not be offloaded to chatbots, the guidance claims.

Manila, Philippines – Leila de Lima was released from detention last month into what the former Philippines senator calls "a whole new world". In 2016, then-President Rodrigo Duterte promised to "destroy" de Lima, one of the loudest critics of his deadly drug war. The president's supporters began targeting the first-term senator and former human rights commissioner – ridiculing her for an alleged romantic affair with her driver, and accusing her of involvement in drug trafficking. In February 2017, she was arrested on drug charges she denies and that international observers have said are politically motivated. "I had this deep sense of disbelief," de Lima told Al Jazeera. "I never thought that Mr Duterte would go to that extent, that length, of jailing me. I thought it would just be daily vilification, personal attacks, attacks against my womanhood."

Justice systems around the world are using artificial intelligence (AI) to assess people with criminal convictions. These AI technologies rely on machine learning algorithms and their key purpose is to predict the risk of reoffending. They influence decisions made by the courts and prisons and by parole and probation officers. This kind of tech has been an intrinsic part of the UK justice system since 2001. That was the year a risk assessment tool, known as Oasys (Offender Assessment System), was introduced and began taking over certain tasks from probation officers. Yet in over two decades, scientists outside the government have not been permitted access to the data behind Oasys to independently analyse its workings and assess its accuracy – for example, whether the decisions it influences lead to fewer offences or reconvictions. Lack of transparency affects AI systems generally. Their complex decision-making processes can evolve into a black box – too obscure to unravel without advanced technical knowledge. Proponents believe that AI algorithms are more objective scientific tools because they are standardised and this helps to reduce human bias in assessments and decision making. This, supporters claim, makes them useful for public protection. But critics say that a lack of access to the data, as well as other crucial information required for independent evaluation, raises serious questions of accountability and transparency.

San Francisco's board of supervisors recently voted to let their police deploy robots equipped with lethal explosives – before backtracking several weeks later. In America, the vote sparked a fierce debate on the militarisation of the police, but it raises fundamental questions for us all about the role of robots and AI in fighting crime, how policing decisions are made and, indeed, the very purpose of our criminal justice systems. In the UK, officers operate under the principle of "policing by consent" rather than by force. But according to the 2020 Crime Survey for England and Wales, public confidence in the police has fallen from 62% in 2017 to 55%. One recent poll asked Londoners if the Met was institutionally sexist and racist.

The system for granting asylum in the U.S. has long been a political point of contention. Democrats and Republicans debate how liberal or restrictive its rules should be, but evidence suggests that the fate of some asylum seekers may be less influenced by the rules than by something far more arbitrary: the judge they're assigned. A 2007 study titled "Refugee Roulette" found that one judge granted asylum to only 5 percent of Colombian applicants, whereas another--working in the same building and applying the same rules--granted it to 88 percent. Asylum is by no means the only part of our legal system where such discrepancies arise. In a landmark 1974 study, 50 judges were given an identical set of facts about a hypothetical heroin dealer.

A judge in Colombia has caused a stir by admitting he used the artificial intelligence tool ChatGPT when deciding whether an autistic child's insurance should cover all of the costs of his medical treatment. He also used precedent from previous rulings to support his decision. Juan Manuel Padilla, a judge in the Caribbean city of Cartagena, concluded that the entirety child's medical expenses and transport costs should be paid by his medical plan as his parents could not afford them. While the judgment itself did not cause much fuss, the inclusion of Padilla's conversations with ChatGPT in the ruling has been more contentious. Among Padilla's inquiries with the chatbot, the legal documents show Padilla asked ChatGPT the precise legal matter at hand: "Is an autistic minor exonerated from paying fees for their therapies?"

The judiciary has historically been conservative in its use of Artificial Intelligence, but recent advances in machine learning have prompted scholars to reconsider such use in tasks like sentence prediction. This paper investigates by experimentation the potential use of explainable artificial intelligence for predicting imprisonment sentences in assault cases in New Zealand's courts. We propose a proof-of-concept explainable model and verify in practice that it is fit for purpose, with predicted sentences accurate to within one year. We further analyse the model to understand the most influential phrases in sentence length prediction. We conclude the paper with an evaluative discussion of the future benefits and risks of different ways of using such an AI model in New Zealand's courts.