When the justice relies on an algorithm
Imagine that you face a legal case and discover that a part of the decision will be taken by an algorithm. Science fiction? Not really. In many countries, the tools of artificial intelligence are already employed in the judicial system to evaluate the dangerousness of a defendant, suggest convictions or analyze thousands of cases in a few seconds. But it is natural to ask: an algorithm can be truly impartial?
What is justice algorithmic
The term justice algorithmic it refers to the use of automatic or semi-automatic support legal decisions, legal or administrative provisions. These tools are processing large amounts of data, learn from past examples and to generate recommendations.
The goal is to make decisions faster, consistent, and evidence-based. But behind this promise is hiding a truth that is more complex: algorithms are not neutral. Are created by human beings, trained on human data, and inevitably influenced by bias in human.
Artificial intelligence and impartiality: an oxymoron?
The idea that the AI is impartial comes from its mathematical nature: it has no emotions, he feels no sympathy or prejudice. But what makes the difference is the type of data on which it is trained. If the historical data contain disparities (e.g. more arrests among some of the minorities), the algorithm will tend to replicate and strengthen these imbalances.
An emblematic case is COMPASa system used in the United States to predict the likelihood of recurrence. An investigation of Something revealed that the system sovrastimava the risk to people african americanswhile not having direct access to the variable “race”.
👉 Something – Machine Bias
In our article Ethics of Artificial Intelligence: why it concerns us allwe have already seen how technology can amplify existing discrimination if it is not designed with care and responsibility.
When the AI enters the court
In addition to the american case, even in Europe, there is discussion on the use of AI in the justice system. The The council of Europe he has published a Ethical charter on the use of artificial intelligence in judicial systemsthat emphasizes the importance of:
– transparency,
– spiegabilità,
– the observance of the fundamental rights.
In some countries, the AI is already used to analyze legal contracts, suggest previous relevant or support the preparation of documents. But there is a fundamental difference between assistance and replacement of the court.
Article AI and the Future of Democracy: Algorithms and Electoral Processes to show how in the context of the political delegation to THE poses similar challenges: who is controlling who?
Concrete examples and dilemmas from real
– Estoniathe AI is proven to resolve civil disputes minor, under the supervision of a judge.
– Canada, the system Minority Report it was shelved after criticism on the predictive use in the judicial context.
– Italy, studies are underway on the use of AI for the organization of judicial work, not to decide the sentences.
The node is the most difficult to resolve is this: a TO the may issue a “right” decision without knowing what is justice?
👉 European Ethical Charter on the use of AI in judicial systems
Frequently asked questions (FAQ)
The algorithms are always being influenced by bias?
Yes, in a direct or indirect way. The data from which they learn, reflect the real world, which is made of inequalities. Need a careful design to reduce these biases.
The artificial intelligence can replace a judge?
No, and not should do it. The AI can be a support tool, but the responsibility for the moral and legal remains human.
Can we rely on the AI in the legal field?
It depends on how it is designed, tested and supervised. Trust must be earned through transparency, accountability and democratic control.
Conclusion: impartial for real?
The AI can make the justice system more efficient, but only if it is used with awareness, clear rules, and human control constant. True justice is never only a matter of calculation, but of values, context and humanity.
It is not enough to say that an algorithm is neutral: you need to ask yourself those who have trained, with what data, for what purpose. Only in this way can we build a justice algorithmic not only “automatic”, but also fair.