Ai in Law and Justice
Chapter 1: What is the main topic discussed in this episode?
Welcome back to AI Squared, where two minds explore one intelligent future. I'm Ayush.
And I'm Michael. Last episode, we explored AI and the environment, how it's helping us fight climate change while also raising its own environmental challenges. Today, we shift gears into something equally impactful, AI in law and justice.
From predictive policing to algorithmic sentencing to AI-driven legal research, artificial intelligence is creeping into courtrooms and justice systems around the world.
The big question is, can machines ever be truly fair? Or will they just replicate the biases already baked into our legal system?
Let's start with the basics. AI is being used as a legal assistant, helping lawyers sift through thousands of pages of case law, drafting contracts, and even generating arguments.
Tools like Casetext's Co-Counsel Harvey AI or other law-specific Large Language Models, or LLMs, are already being piloted in firms. They save time, cut costs, and even make legal resources more accessible to clients who otherwise might be shut out.
Imagine a small-town lawyer without access to a giant research staff. AI can level the playing field by giving them the same instant case law search power as a massive corporate law firm.
But there's risk. When AI generates a flawed argument or references a hallucinating court case, that doesn't actually exist, and yes, that has happened, who's responsible? The lawyer, the developer, or the AI itself?
It's a huge liability question. Courts in the US have already fined lawyers for submitting AI-generated legal briefs that cited fake cases. And remember, these tools need oversight, not blind trust.
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Chapter 2: What are the key applications of AI in law and justice?
Still, if done right, AI can massively democratize access to justice. For people who can't afford traditional legal help, an AI system could mean the difference between having a defense and facing the system alone. One of the most controversial uses of AI in justice is predictive policing. Algorithms analyze crime data to predict where future crimes might happen.
The idea sounds promising. Prevent crime before it happens. Allocate police resources more efficiently. Reduce response times. Cities like Chicago, Los Angeles, and London have experimented with this technology.
But here's the problem. The data itself is biased.
Chapter 3: Can AI truly ensure fairness in the legal system?
If one neighborhood has historically been over-policed, then of course the data will show higher crime rates there, leading to even more policing in the same area. It's basically a feedback loop.
That means predictive policing can reinforce racial and socioeconomic biases, unfairly targeting minority and lower-income communities. And because the system is opaque, citizens don't know why they're being surveilled.
Some cities have banned predictive policing altogether after public outcry. Others are pushing for transparency, requiring algorithmic audits and public reporting on how these predictions are actually made.
The takeaway? Predictive policing is less about predicting crime and more about predicting where the police will go next. That's a dangerous distortion of justice.
Now let's talk about sentencing. Some courts use algorithms like COMPAS to recommend bail, parole, or prison sentences based on risk scores. On paper, it sounds like an objective system, remove human bias and rely on data. But in practice, these tools have shown glaring issues.
Investigation revealed COMPAS gave higher risk of reoffending scores to black defendants than white defendants under similar circumstances. That means the algorithm wasn't neutral. It amplified existing systemic biases.
Even worse, defendants often can't even appeal to their scores because the algorithm is proprietary. It's a black box. Imagine being sentenced to more prison time because of an algorithm you're not even allowed to question.
It raises the core question. Should algorithms influence decisions about human freedom at all? Or should they only be used as advisory tools, not as final say?
Because justice isn't just about statistics, it's about compassion, mercy, and understanding context, things no algorithm can replicate. Some countries are testing AI judges for small claims or routine disputes. Estonia has piloted the AI system to handle minor financial cases.
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