AI and the Future of Law Enforcement: the risks of perfectly enforcing imperfect laws
For as long as there have been laws, there’s been lawbreaking.
And for just as long, much of that lawbreaking has gone unnoticed, undetected, or unenforced.
From small-time tax evasion and regulatory violations to more serious crimes, our legal and enforcement systems have always operated under the assumption that not every infraction will be caught, let alone punished.
But what happens when almost everything is knowable, detectable, and enforceable — all the time?
This is not a hypothetical question. It’s a future that is increasingly within reach.
CEO of FairPlay.
AI-powered enforcement
Advances in artificial intelligence, combined with ubiquitous surveillance, data aggregation, and predictive analytics, are rapidly closing the gap between what people do and what the state or private enforcers (like insurers, employers, and technology platforms) know about it.
AI-powered enforcement has the potential to make rules — from traffic laws to environmental regulations to financial reporting requirements — enforceable at a level no human system ever could.
Today’s enforcement regimes are constrained by human capacity, resource limitations, and the sheer scale of human activity.
There simply aren’t enough police officers, IRS auditors, building inspectors, or compliance officers to monitor every infraction.
Even in the most highly-regulated sectors like banking or healthcare, enforcement operates on a sampling basis — regulators audit a small fraction of cases and rely on whistleblowers or patterns of harm to trigger deeper investigations.
The enforcement gap
This enforcement gap creates space for:
Minor lawbreaking that everyone does, like jaywalking or tax underreporting.
Strategic rule-bending by corporations confident that the cost of non-compliance will be lower than the profit it generates.
Informal economies and workarounds in communities where strict legal compliance is impractical or unaffordable.
In other words, incomplete enforcement isn’t unintentional — it’s a built-in buffer between the idealism of law and the pragmatism of real life: It reflects the gap between the formal rules and the messy reality of how people and businesses actually live and operate.
What AI promises
AI promises to upend this dynamic in several ways:
1. Mass surveillance: Modern AI systems can process vast streams of video, sensor data, social media activity, transaction records, and communications. Unlike human enforcers, AI can integrate all these data sources into coherent profiles, spotting patterns and anomalies in real-time and nearly perfect precision. A future where every movement in public space, every business transaction, and every online interaction is automatically monitored and assessed for legality is increasingly plausible.
2. Predictive and preemptive enforcement: AI doesn’t just detect violations — it can predict them. Machine learning models trained on historical violations can flag likely offenders or anticipate where breaches will occur. This transforms enforcement from a reactive process into a predictive and preventative one. Imagine an AI system that identifies risky businesses or individuals and nudges them toward compliance before violations occur — or simply pre-emptively fines them based on the probability they’ll break the rules.
3. Automated enforcement at scale: AI systems don’t get tired. They can enforce every rule, everywhere, all the time. This could turn what are now low-risk offenses — jaywalking, minor tax errors, small regulatory missteps — into near-certainties for detection and sanction.
4. Privatized enforcement ecosystems: It’s not just governments. Insurance companies, banks, landlords, employers, and platforms could all adopt AI enforcement systems to monitor contractual compliance, workplace behavior, or loan covenants. When combined with always-on monitoring, this creates a web of privately enforced micro-compliance regimes, each with its own penalties and incentives.
The societal implications
If AI makes laws and rules enforceable at near-100% rates, the consequences for society would be profound — and not all positive. These consequences include:
1. The end of informal economies: Many communities, particularly lower-income ones, rely on informal economies that blur the line between legal and illegal activity. From street vending without a permit to off-the-books construction work, these economies function because enforcement is incomplete. Total enforcement would collapse this informal safety net, often without offering viable alternatives.
2. The criminalization of everyday life: Laws are written with the assumption that not all violations will be punished. As a result, many laws are overbroad, technically criminalizing common behavior — but rarely enforced. If AI changes that enforcement probability from 1% to 99%, everyday life could become a minefield of minor violations, each triggering fines, penalties, or worse.
3. Disparities in enforcement scope and targeting: Even with AI, enforcement systems are built by humans — and inherit their biases. Which laws are prioritized for enforcement, and which populations are most heavily monitored, will still reflect political and economic power dynamics. AI could create a veneer of neutrality, while in practice concentrating enforcement on marginalized communities or politically disfavored activities.
4. Compliance as a full-time job: If businesses and individuals are subject to always-on monitoring and hyper-enforcement, staying compliant could become a full-time job. Entire industries of compliance assistants, AI compliance dashboards, and personal legal monitoring services could arise, adding friction and cost to every aspect of life.
5. The death of proportionality: Human enforcers have discretion. They can give warnings, ignore trivial violations, or apply common sense to ambiguous cases. AI enforcers, especially when operating autonomously, are far less likely to exercise that kind of judgment. This could create a legal environment where the letter of the law is enforced with machine precision, but with no regard for context or fairness.
Is this a future we want?
The prospect of AI-enforced legal perfection raises a fundamental question: Is the goal of law to achieve perfect compliance, or to balance order with freedom, fairness, and practicality?
Laws are not sacred truths. They are human creations, shaped by politics, economics, and culture. They evolve as society changes. If AI locks in existing legal regimes and enforces them with mechanical rigor, it could stifle innovation, crush dissent, and make laws less adaptable to social change.
The enforcement gap — the space between law on the books and law in action — is often where society negotiates its real values. Closing that gap with AI could mean the end of that negotiation, replacing it with automated obedience.
There are, of course, benefits to better enforcement — fewer dangerous products on shelves, fewer tax cheats, fewer environmental violations. But the danger lies in forgetting that the purpose of enforcement is not just to punish, but to serve justice — which sometimes means turning a blind eye, showing mercy, or allowing room for ambiguity.
As AI enforcement spreads, we must ask: Are we building a system that serves justice, or one that serves only the law?
Because if AI gives us perfect enforcement of imperfect laws, the result won’t be a more just society — just a more unforgiving one.
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For as long as there have been laws, there’s been lawbreaking. And for just as long, much of that lawbreaking has gone unnoticed, undetected, or unenforced. From small-time tax evasion and regulatory violations to more serious crimes, our legal and enforcement systems have always operated under the assumption that not…
