AI, Data and the Law: Can Machines Be Fair?

Law has always evolved alongside technology. The printing press made legal texts more accessible, the telephone allowed lawyers to communicate in real time and the internet opened up new avenues for digital contracts, online dispute resolution and virtual courtrooms. But artificial intelligence is something different. Unlike past innovations that simply made legal work faster or easier, AI has the potential to fundamentally change how the legal system operates. It can analyse vast amounts of legal data, predict case outcomes and even draft legal arguments. In some ways, it is already performing tasks that once required a human lawyer or judge.

This raises a crucial question: should machines be trusted to deliver justice? The efficiency gains AI offers are undeniable - legal services can become cheaper, legal research more precise and routine tasks automated. But the law is not just about efficiency; it is about fairness, ethics and human judgement. Justice is not a mechanical process, nor is it always purely objective. It involves interpretation, emotion and moral reasoning, elements that machines do not possess and fail to understand well. Yet courts and law firms are embracing AI at an accelerating pace. The tension between the need for efficiency and the demand for fairness is at the heart of this transformation and how society navigates this balance will determine whether AI becomes a tool for justice - or a weapon against it.

The Rise of AI in Legal Work and Its Ethical Implications

AI is now embedded in nearly every aspect of legal practice, from corporate law to criminal justice. Machine learning algorithms sift through mountains of case law in seconds, making legal research dramatically faster. AI contract review software can identify risks and inconsistencies with remarkable accuracy. Chatbots provide basic legal guidance to people who might not otherwise be able to afford a lawyer. Even predictive analytics is being used to estimate the probability of a lawsuit's success, guiding decisions about whether to settle or proceed to trial. In many ways, these innovations seem like a clear win for both legal professionals and the general public.

But efficiency is not the same as justice. The legal system has always relied on principles of fairness, precedent and careful interpretation of the law. AI, on the other hand, relies on data- massive datasets that reflect past legal decisions, sentencing patterns and judicial behaviours. And data is not neutral. It reflects the biases of the past, meaning AI can reinforce and even exacerbate historical injustices. The COMPAS software, used in U.S. courts to assess the risk of re-offending, is one of the most well known examples of this problem. Studies found that it disproportionately labeled black defendants as high-risk while predicting lower risk levels for white defendants under similar circumstances. The algorithm did not “intend” to be discriminatory; it simply learned from historical data in which similar biases already existed. But in the legal system, intent does not excuse injustice. When AI is making recommendations on sentencing, bail, or parole, biased predictions can have real-world consequences that deepen systemic inequalities rather than reduce them.

This raises a larger question: can AI ever truly be fair? Fairness is defined as treating every individual equally, AI seems like the perfect tool - it makes decisions based purely on data and statistical analysis, free from emotion or personal prejudice. But fairness is more than mathematical balance. The legal system does not just enforce rules; it interprets them in the context of human lives. A machine can determine that a mother is statistically more likely to lose custody based on past cases, but it cannot understand the emotional, psychological, or social ramifications of separating a child from their parent. An AI might analyse thousands of discrimination lawsuits and predict whether a new case will succeed, but it cannot grasp the lived experiences of the people involved. Law is not just about predicting outcomes - it is about ensuring that those outcomes are just. And that requires something AI lacks: human judgment.

Should the Legal System Have a Place for “Black Box” Thinking?

Even if AI could be made fairer, another problem remains - transparency. AI models, particularly deep learning systems, operate as “black boxes” - they take in data, process it, and produce results, but even their own developers cannot always explain how they reached a specific conclusion.

On the topic of black box thinking…

At the highest levels of chess and poker, game theory and AI driven analysis become essential tools for improvement. Players don’t just study the best moves or optimal betting strategies - they analyse the underlying patterns and reasoning behind AI’s choices. Machine analysis can show us the mathematically best move in any given position or the most profitable decision over millions of poker hands, but true mastery comes from understanding why those moves work.

This is why AI, for now, will always outperform even the greatest human players. Unlike humans, AI doesn’t rely on intuition or experience, it calculates every possibility without bias, learning from millions of scenarios with perfect recall. It doesn’t struggle with fatigue, emotion, or psychological pressure. The most valuable lessons for human players come from interpreting AI’s outputs, not just memorising them.

As long as AI operates as a “black box”, it will always have an edge. Humans seek understanding; AI simply executes. In that difference lies the reasons why machines dominate games of pure strategy.

However, we cannot simplify legal dilemmas into pure mathematical game theory…

In areas like medicine or finance, this opacity is concerning but manageable. In the legal system, it is unacceptable. Every decision in law must be justified and open to scrutiny. If a judge hands down a ruling, they must explain their reasoning. If a lawyer makes a legal argument, they must support it with evidence. AI, however, offers no explanations - only outputs.

This presents a serious challenge to accountability. Who is responsible if an AI system makes a flawed recommendation that leads to an unjust outcome? If an AI-driven sentencing tool suggests a harsher punishment based on hidden biases in the data, is the blame on the judge that followed it, the developers that built it, or the policymakers who approved its use? The law is built on the idea that decisions must have clear reasoning behind them but AI muddies that clarity. For legal professionals to trust AI, its decision-making process must be interpretable and transparent - something that remains a major challenge in current AI development.

Can the Law Keep Up with AI?

Despite the risks, AI’s role in the legal system is expanding rapidly and lawmakers are struggling to keep pace. Some jurisdictions, like the European Union, have implemented strict regulations to control how AI is used in sensitive areas, including legal decision making. The European Union’s AI Act aims to categorise AI systems by risk and impose legal obligations on developers to ensure fairness and transparency. The United States has taken a more decentralised approach, leaving regulation largely in the hands of state governments and private organisations, (which led to the Colorado AI Act).

The challenge is finding a regulatory framework that protects against AI’s dangers without throttling innovation. AI can make legal work more efficient and accessible, but if regulations are too loose, biased and opaque, AI systems could undermine public trust in the legal system. On the other hand, if regulations are too strict, they could slow down beneficial developments that make legal services more affordable and widely available. The best path forward is likely a balance - one that allows AI to assist legal professionals while ensuring it remains accountable to human oversight and ethical principles.

Looking Ahead

AI is not inherently good or bad; it is a tool. Whether it enhances justice or erodes it depends on how it is designed, regulated and used. If AI is to play a role in the legal system, it must be transparent, fair and ultimately just exist to support human judgement. The law is not a set of equations to be solved, it cannot be constructed as a game theory scenario. AI can help lawyers and judges navigate complex interactions but in my opinion it cannot - and should not - replace the human element in Law.

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