Harnessing data to transform justice systems

Court cases generate vast amounts of data. Historically, this information has been recorded on paper to document the decision-making process. With electronic case management, virtual courtrooms, and e-filing, massive databases are now created. Despite its potential to improve the administration of justice, this data is largely underutilized. Imagine if judiciaries could harness this data to reduce backlogs, detect hidden biases, or develop Artificial Intelligence (AI) tools to expand access to justice. This possibility is now within reach. In our recent article, “The Data Revolution in Justice”, we propose a three-step framework to unlock the potential of judicial data.

1. Measurement and Diagnostics: Benchmarking Justice

“What gets measured, gets done”—yet measurement has traditionally been lacking in justice systems. Despite detailed case-level data, many courts don’t use this data to inform decision-making. At a minimum, courts should consolidate data into performance reports and automate the process of consolidation. Beyond that, tracking indicators like case inflow, time to disposition, and case clearance can help allocate resources and identify where delays occur.

The applications of this data are numerous. Some countries use it to assign cases to judges based on workload and case weights, ensuring that some judges are not overburdened while others remain underutilized. Others use it to reward high-performing courts (e.g., Serbia), or to inform citizens of their prospective outcomes in mediation compared to court (e.g., Mexico). Furthermore, combined with legal needs surveys, data can also diagnose which regions or demographics lack access to justice and why—thus targeting legal aid where needed most.

2. Experimentation: Testing Innovative Approaches

Data doesn’t just help measure and diagnose issues—it can also test solutions. Just like tech companies use A/B testing to refine products, judiciaries could test interventions to learn effective ways to improve citizens’ experiences and streamline processes. While there has been an increase in empirical studies and randomized controlled trials (RCTs) across disciplines, the legal sector has been particularly slow in the adoption of RCTs to evaluate and improve policies.

Nonetheless, recent years have seen progress in this area. As an example, in Kenya, we partnered with the Judiciary to create a personalized feedback form that identified the primary causes of court delays for each court. Sharing this information with judges and Court User Committees prevented about 20,000 adjournments nationwide, significantly speeding up court processes. This and other examples underscore how data can develop cost-effective solutions while also learning what works to improve court performance and litigants’ experience.

3. Machine Learning and AI: Leveraging Frontier Technology

One promising avenue for data-driven justice is machine learning and AI, which are starting to reshape the legal system. In Brazil, where nearly 80 million lawsuits are pending, an AI tool called VICTOR filters Supreme Court appeals in seconds, replacing a task that once took a human 40 minutes. AI tools have also been used to predict recidivism risk. In the United States, researchers developed an algorithm to predict a defendant’s likelihood to reoffend or flee, posing that such tools could potentially reduce crime by up to 25% without increasing jailing rates.

Recent developments in Large Language Models (LLMs) have multiplied AI’s potential to support justice systems. LLMs can analyze vast repositories of judicial opinions, synthesize legal information, and even draft personalized claims and contracts. GenAI also helps expand access to justice for low-income citizens by offering translation, curating legal information, and guiding them through complex legal issues.

Looking forward: A robust data ecosystem for better justice

For the promise of data to be realized, justice systems should develop a secure, interoperable network linking court records, prosecutor files, legal aid data and surveys—among other data sources. This requires planning ahead and making an initial investment in data infrastructure with long-term benefits. Furthermore, effective integration requires collaboration among legal professionals, technologists, and policymakers. Thus, investment in human capital, including recruitment and training, will be essential.

Embracing data-driven tools also presents new challenges such as widening the digital divide, perpetuating biases, and exposing privacy and cybersecurity risks. To secure benefits while safeguarding fairness and security, countries must implement robust data governance, maintain oversight, test innovations, and ensure transparency.

In conclusion, data can modernize justice systems by identifying inefficiencies, uncovering biases, testing solutions, and enhancing decision-making through AI. Proactively adopting data-driven reforms helps courts avoid the costs of inaction: backlogs, a widening justice gap, and declining public trust. In an era of rapid technological change and evolving societal challenges, data is a crucial ally for governments and judiciaries to enhance the quality of justice for all.