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The promise and peril of AI tools for Ja’s justice system
Columns
By Hodine Williams  
February 20, 2025

The promise and peril of AI tools for Ja’s justice system

Imagine a Jamaican court system in which cases move swiftly, judges make informed decisions quickly, and fewer people are stuck in pretrial detention for years.

Some would say it sounds like a dream for a system often criticised for being slow and overburdened, right? But what if artificial intelligence (AI) could help make this a reality? Tools like COMPAS (Correctional Offender Management Profiling for Alternative Sanctions) — used in places like the United States to assess the risk of reoffending — are already showing how AI can streamline judicial processes. But before we get too excited, let’s ask the hard questions: Can AI really make Jamaica’s justice system more efficient? And at what cost?

 

The Problem: A System in Need of Fixing

Jamaica’s courts are no stranger to criticisms regarding inefficiency. Case backlogs are a nightmare, with some trials taking years to resolve. Prisons are overcrowded, and a staggering number of detainees are awaiting trial rather than serving sentences. The sentencing process is not without criticism either. Judges often face the daunting task of determining appropriate sentences with limited time and resources, and even so — criticisms are still heralded.

Take, for example, under the old Firearms Act, the case of two men convicted of illegal possession of a firearm (one in Kingston and the other in Montego Bay). One received a five-year sentence, while the other got a $400,000 fine. Both had similar criminal histories, ages, and community ties, but the judge’s workload and subjective interpretation of the facts led to wildly different outcomes. This lack of standardisation undermines public trust and creates unjust outcomes.

Could AI help to fix this? Tools like COMPAS, which uses algorithms to assess a defendant’s risk of reoffending, could provide judges with data-driven insights to guide their decisions. But is this a step towards efficiency — or a step away from justice?

 

Speed, Accuracy, and Resource Allocation

AI tools like COMPAS offer some undeniable advantages. For starters, they can process vast amounts of data in seconds. Imagine a tool that analyses an accused’s criminal history, employment status, and social ties almost instantly, providing judges with a risk score to inform decisions on bail or sentencing. This potentially could drastically reduce the time it takes to decide who gets bail and who doesn’t, freeing up judicial resources for more complex cases, especially if those making a bail application are required to submit information prior to the bail hearing.

Efficiency isn’t just about speed — it’s also about resource allocation. When treating with parole, if AI can help identify low-risk defendants who can safely be released, it could ease the strain on correctional facilities. Fewer people in pretrial detention means lower costs for the Government — money that could be redirected to critical areas like health care or education.

And let’s not forget the judges. Overworked and overwhelmed, they often must make split-second decisions with arguable limited information in the grand scheme of things. AI could act as a decision-support tool, providing data-driven insights that help judges prioritise cases and make more informed rulings. The result? Faster case resolutions and a more streamlined judicial process.

 

Bias, Transparency And Fairness

But here’s the catch, efficiency shouldn’t come at the expense of fairness. AI tools like COMPAS have faced significant criticism. In the US, for example, Black defendants are often assigned higher risk scores than White defendants, even when their criminal histories are similar. Why? Because the algorithms are trained on historical data that reflects systemic racism.

Then there’s the issue of transparency. COMPAS and many other AI tools are “black boxes”— meaning, even their creators can’t always explain how they arrive at their conclusions. Imagine being denied bail because an algorithm says you’re high-risk, but no one can tell you why. How can you challenge a decision you don’t understand? Efficiency is great, but not if it undermines trust in the justice system.

If Jamaica were to adopt similar tools, could we end up with a system that’s fast but unfair? It’s a valid question, and one that demands careful consideration. What works for Jamaica is that Jamaica is a society with a Black majority.

 

AI in Forensics — A game changer

AI’s potential isn’t limited to sentencing and bail decisions. It could also revolutionise forensic analysis, particularly in ballistic investigations. When a bullet or cartridge case is recovered from a crime scene, it carries unique markings left by the firearm used. These markings, like fingerprints for guns, can be analysed to identify the weapon.

Traditionally, forensic experts manually compare these marks against known samples. AI can automate this by analysing high-resolution images of the evidence and comparing them against a local database of ballistic records. This would allow investigators to quickly determine if a firearm has been used in previous crimes, even if the gun itself hasn’t been recovered. The US has been a pioneer in using AI for ballistic analysis. The National Integrated Ballistic Information Network (NIBIN) uses automated systems to compare ballistic evidence, such as cartridge casings and bullets, from crime scenes.

For example, if a spent casing is found at a crime scene, AI could scan the local database and identify matches with other cases in which the same firearm was used. This could reveal connections between seemingly unrelated crimes, providing investigators with critical leads. In some cases, a firearm might be linked to multiple crimes, but only one has a named suspect. AI could bridge this gap, helping law enforcement tie the suspect to other incidents and build a stronger case.

Beyond solving individual cases, AI could also assist in resolving cold cases by re-examining old evidence and identifying matches with newer cases. For instance, a gun used in a recent crime might be linked to an unsolved case from years ago, providing new avenues for investigation.

 

What Jamaica Can Do Differently

Jamaica doesn’t have to reinvent the wheel. Other countries have already experimented with AI in their justice systems, and their experiences offer valuable lessons. In the US, COMPAS has faced lawsuits and public backlash over its biased predictions. In the UK, AI tools like the Offender Assessment System (OASys) have been criticised for lacking transparency and accountability. Meanwhile, Australia’s Risk-Needs-Responsivity (RNR) model integrates risk assessment with rehabilitative tactics, ensuring offenders receive individualised interventions based on their needs.

So how can Jamaica harness the power of AI to boost efficiency without sacrificing fairness? Here’s a roadmap:

• Start small — Pilot AI tools in specific areas, like in traffic courts or for minor offences to test their accuracy and fairness.

• Prioritise transparency — Use open-source algorithms that allow judges, lawyers, and defendants to understand how risk scores are calculated.

• Keep people in the loop — AI should assist, not replace, judges. Training is essential to ensure AI is seen as a tool, not a final authority.

• Address data gaps — AI is only as good as the data it’s trained on. Jamaica will need to assess and, if necessary, invest in improving its data collection and management systems.

• Engage stakeholders — Build trust by involving judges, lawyers (public and private), defendants, and the public in discussions about AI’s role in the justice system.

• Create legal safeguards — Develop clear laws and regulations to govern AI use, addressing issues like data privacy and algorithmic accountability.

 

Can Efficiency and Justice Coexist?

The fact is, AI is here to stay. At the end of the day, the question isn’t just whether AI can make the justice system faster — it’s whether it can do so without compromising fairness, thus causing significant prejudice to accused or convicted people. Can a machine truly balance efficiency with the need for nuanced, human-centred justice?

The answer isn’t as simple as we have seen in other jurisdictions. AI has the potential to be a powerful tool for boosting efficiency, but only if it’s used responsibly. Jamaica has a unique opportunity to lead in the region and to show how AI can be integrated into the justice system in a way that is both efficient and fair. But this will require careful planning, robust safeguards, and a commitment to putting people first.

Efficiency is important, but it should never come at the cost of fairness. So to answer my own question: Can AI make Jamaica’s justice system more efficient? Absolutely. But only if we’re willing to ask the hard questions, learn from the mistakes of others, and ensure that technology serves justice — not the other way around.

 

hodine.williams@gmail.com

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