The judicial system in Los Angeles is embarking on a significant technological experiment, piloting an artificial intelligence tool named "Learned Hand" designed to streamline administrative tasks for judges and allow them to concentrate on the core judicial functions requiring nuanced legal analysis and discretion. This initiative, spearheaded by the Los Angeles Superior Court, represents a proactive approach to addressing the mounting pressures of increasing caseloads that are straining court resources globally. The program aims to test the efficacy of AI in assisting judges without compromising the integrity or independence of judicial decision-making, a paramount concern in the legal arena.
The Growing Crisis of Judicial Caseloads
Courts worldwide are grappling with an unprecedented surge in legal disputes. Factors contributing to this burgeoning crisis include an increasingly litigious society, greater accessibility to legal recourse, and, paradoxically, the very advancements in technology that can facilitate the filing of legal documents. A report published in February 2026 by the national law firm Fisher Phillips highlighted this trend, noting a substantial 49% increase in filings over the preceding year, escalating from approximately 4,100 to 6,400. This influx places immense pressure on judicial officers, who are often tasked with extensive administrative duties that detract from their primary responsibilities of interpreting laws, weighing evidence, and delivering justice.
"We’re at a place in society where courts are under tremendous strain," stated Shlomo Klapper, founder and CEO of Learned Hand, in an interview with Decrypt. "Their caseloads go up, but no help is coming." Klapper further elaborated on the dual nature of technological advancement, observing that while AI can contribute to increased filings, it also presents an opportunity to alleviate the workload. "Advances in artificial intelligence are massively dropping the cost of litigation," he remarked, underscoring the potential for AI to become a tool for efficiency within the very system it is helping to inundate.
Learned Hand: A New Paradigm for Judicial Support
Learned Hand, founded in 2024, is an AI system specifically engineered to address the administrative burdens faced by judicial officers. Named in homage to the esteemed federal judge Learned Hand, the platform is designed to be a purpose-built AI solution for the courts, aiming to automate what Klapper describes as "drudge work." The tool assists by summarizing lengthy legal filings, meticulously organizing evidence presented in cases, and generating draft rulings for civil proceedings.
The pilot program within the Los Angeles Superior Court grants a select group of judicial officers access to Learned Hand’s AI capabilities. This controlled deployment allows for a comprehensive evaluation of the system’s performance across the entire lifecycle of a case, from the initial intake of documents to the drafting of potential judicial decisions. Klapper, who brings a unique background as a former judicial law clerk for the U.S. Court of Appeals and as a deployment strategist with Palantir, emphasizes that the core objective is to free up judges’ time. "The goal is to reduce time spent on administrative tasks so judges can focus on the parts of a case that require legal analysis and discretion," he explained.
Ensuring Reliability: The Challenge of AI in Legal Practice
A critical challenge in developing AI for legal applications, particularly for judicial support, lies not merely in generating text but in ensuring the absolute accuracy and reliability of that output. The legal field demands an exceptionally high standard of precision, where even minor inaccuracies can have significant repercussions. Klapper acknowledged this complexity, stating, "Most of the expense of our large language model is in the verification, not the generation. Generation is easy. Anyone can generate something, but how do you make sure that it’s really reliable?"
The specter of "AI hallucinations"—instances where AI generates plausible but factually incorrect or fabricated information—has already cast a shadow over high-profile legal proceedings. In 2023, the defense team for Prakazrel "Pras" Michel, a member of the hip-hop group The Fugees, alleged that an AI-assisted closing argument contained frivolous claims and overlooked critical weaknesses in the prosecution’s case. In another notable incident the same year, a federal judge mandated that lawyers representing former Trump attorney Michael Cohen provide printed copies of cited cases after the court was unable to verify their existence, suggesting potential AI-generated citations.
Learned Hand’s design incorporates specific strategies to mitigate these risks. The system operates on a carefully curated and narrowed pool of source material, eschewing broad internet access or arbitrary datasets. Instead, it draws exclusively from a defined set of authoritative legal materials. This controlled approach aims to prevent the AI from reflecting biases inherent in broader training data, such as advice found on less formal platforms like Reddit. Furthermore, Learned Hand employs a modular approach, breaking down complex tasks into discrete steps, with each step assigned to specialized AI models designed for specific functions. This decomposition enhances control and facilitates verification.
A Measured Approach to Technological Integration
The partnership between Learned Hand and the Los Angeles Superior Court is characterized by a commitment to cautious evaluation and transparency. Presiding Judge Sergio C. Tapia II articulated the court’s stance in a public statement, emphasizing the careful assessment of emerging technologies. "With this partnership, we are carefully evaluating emerging technologies to determine how they may support judicial officers in working more efficiently and effectively," Judge Tapia stated.
Crucially, Judge Tapia underscored the non-negotiable principle of judicial independence. "Let me be clear—while this tool may enhance the way judicial officers review and engage with case files and information, it will not replace, or in any way compromise, the sanctity, independence, and impartiality of judicial decision-making," he asserted. This statement reinforces that the AI is intended as a supplementary tool, an assistant to the judge, rather than a substitute for human judgment.
The user interface of Learned Hand is designed for accessibility, requiring no specialized technical expertise from judges. Klapper described the system as "point and click," eliminating the need for complex prompting. This user-friendly design ensures that the technology can be readily integrated into the existing workflows of judicial officers without imposing an additional learning curve.
The Future of Judicial Workflows
The implications of successfully integrating AI into judicial workflows are far-reaching. By automating routine tasks such as document summarization and evidence organization, AI can significantly reduce the time judges spend on administrative duties. Klapper contends that this shift will enable judges to "spend more time on judge work and less time on drudge work," allowing them to dedicate their intellectual capital to complex legal reasoning, case strategy, and the critical delivery of justice.
However, the adoption of such technologies necessitates a culture of vigilance. Klapper’s cautionary advice, "Don’t trust, verify," serves as a guiding principle. He stresses that judges should not accept AI outputs at face value and that both the tools and the companies developing them must demonstrate their reliability through rigorous testing and transparent performance metrics. The onus is on the technology to prove its worth and earn the trust of the judiciary.
The pilot program in Los Angeles represents a pivotal moment in the ongoing dialogue about the role of artificial intelligence in the legal profession. As caseloads continue to rise and the demands on judicial systems intensify, innovative solutions like Learned Hand may offer a viable path forward, provided they are developed and implemented with an unwavering commitment to accuracy, transparency, and the preservation of judicial integrity. The success of this pilot could set a precedent for how other courts worldwide confront similar challenges, potentially reshaping the future of legal administration and the practice of justice.