AI in Courts: A Double-Edged Sword for Justice

Advanced | July 24, 2025

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The Promise of AI in Legal Systems

Streamlining Operations and Boosting Efficiency

The integration of Artificial Intelligence (AI) into court systems is moving quickly. It plays a big role in the current AI ethics in court debate. Many are talking about its promise. For example, The Epoch Times recently reported on large AI investments. An open letter to the U.S. Supreme Court proposed using “Recursive AI” to help reduce case backlogs. Globally, the trend is clear. A UNESCO survey found that 44% of judicial professionals in 96 countries already use AI tools like ChatGPT for work. AI helps streamline document review, support legal research, analyze contracts, and even assist judges. India’s SUPACE platform is one example.

Expanding Access to Justice

Supporters believe AI can make legal work faster and more accurate. By speeding up case review and sorting through documents quickly, AI can help reduce court delays. This might improve access to justice by making legal help easier to reach for more people. That could be a game-changer for busy or overwhelmed courts.

The Perils: Ethical Dilemmas and Challenges

AI Ethics in Court: Bias, Transparency, and Accountability

While AI offers benefits, it also creates serious ethical problems. One major concern is bias in AI systems. These systems are trained on past data—and that data can reflect real-world prejudices about race, gender, or income. For example, COMPAS, a tool used to predict repeat offenders, has been shown to unfairly label minority defendants as high-risk. This raises fairness concerns.

It gets worse when the systems are “black boxes.” That means their decision-making process is hidden. Lawyers and clients can’t see how results are made—especially in serious cases like sentencing. This lack of transparency can break trust.

Preserving Judicial Integrity

There’s also the issue of accountability. Who is responsible when AI makes a mistake? Some worry that overusing AI could reduce human control in court decisions. This could threaten judicial independence and shift too much power to algorithms. Groups like the European Commission for the Efficiency of Justice (CEPEJ) say that ethics, human rights, and user control must always come first.

Legal professionals also need to protect sensitive information. Using open AI tools might expose private data. That data could be used to train future models, putting privacy at risk.

Reliability and Competence

Another danger is that AI models sometimes “hallucinate.” This means they make up false information. That’s a major problem in the courtroom, where accuracy matters most. Since you can’t cross-examine a machine, using faulty information could cause serious harm.

Judges and lawyers must become tech-savvy. They need to understand how AI works and what its limits are. This includes being aware of bias, hallucinations, and other risks. Only then can they decide when and how to use AI properly in court.

Vocabulary

judicial (adjective): Relating to a court of law or to judges.
*Example: “The judicial system is undergoing significant changes with the adoption of new technologies.”
streamlining (verb): Making an organization or system more efficient by simplifying working methods.
*Example: “AI tools are helping to streamline document review processes in many law firms.”
proponents (noun): People who support an idea or action.
*Example: “Proponents of AI in justice highlight its potential to reduce case backlogs.”
recidivism (noun): The tendency of a convicted criminal to commit another crime.
*Example: “Some AI systems assess recidivism risk, but concerns about bias persist.”
embedded (adjective): Fixed firmly within something else.
*Example: “Bias can be embedded in AI if it’s trained on flawed data.”
prejudices (noun): Unfair beliefs that are not based on facts.
*Example: “Training data may contain historical prejudices.”
contentious (adjective): Likely to cause an argument.
*Example: “Responsibility for AI errors is a contentious issue.”
displace (verb): To take over the role of someone or something.
*Example: “Some fear AI could displace human judgment in courts.”
cognizant (adjective): Being aware or informed.
*Example: “Legal professionals must be cognizant of data risks when using AI.”
hallucinate (verb): (In AI) To produce false or misleading information.
*Example: “AI models can hallucinate, creating responses that are not true.”

Discussion Questions (About the Article)

What is one major benefit of AI in courts, and one major challenge?
How widely is AI being used in court systems around the world?
Why is the “black box” problem in AI especially dangerous in court cases?
What ethical values are promoted by CEPEJ?
Why is tech competence important for judges and lawyers today?

Discussion Questions (About the Topic)

Do you believe AI’s benefits in courts outweigh its risks? Why or why not?
How could hidden algorithms affect trust in legal systems?
What steps can we take to stop AI from repeating biased decisions?
If AI causes harm in court, who should be held accountable?
Can you think of other issues with using AI in legal settings?

Related Idiom

A double-edged sword
Meaning: Something that brings both benefits and problems.
Example: “AI can make courts faster, but it’s a double-edged sword because of bias and trust concerns.”

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This article was inspired by: July 15, 2025 – The Epoch Times