How AI-powered policing is endangering the public’s trust in police

How AI-powered policing is endangering the public’s trust in police

Growing concerns about police use of AI could erode the public’s perception of trust in the legal system.

Predictive policing AI is on the rise − making it accountable to the public could curb its harmful effects

AI that anticipates where crimes are likely to occur and who might commit them has a troubling track record. Democratic accountability could shine a light on the technology and how it’s used.

Predictive policing AI is on the rise − making it accountable to the public could curb its harmful effects

AI that anticipates where crimes are likely to occur and who might commit them has a troubling track record. Democratic accountability could shine a light on the technology and how it’s used.

How AI can lead to false arrests and wrongful convictions

Danger arises when law enforcement believes that AI models are retrieving certainties rather than generating likelihoods.

How AI can lead to false arrests and wrongful convictions

Danger arises when law enforcement believes that AI models are retrieving certainties rather than generating likelihoods.

No man’s hand: artificial intelligence does not improve police report writing speed

This study examines the potential of artificial intelligence (AI) to reduce the time police officers spend writing reports, a task that consumes a significant portion of their workday.

On the person-based predictive policing of AI

Ethics and Information Technology -

On the person-based predictive policing of AI

Ethics and Information Technology -

Artificial Intelligence, Predictive Policing, and Risk Assessment for Law Enforcement

There are widespread concerns about the use of artificial intelligence in law enforcement. Predictive policing and risk assessment are salient examples. Worries include the accuracy of forecasts that guide both activities, the prospect of bias, and an apparent lack of operational transparency. Nearly breathless media coverage of artificial intelligence helps shape the narrative. In this review, we address these issues by first unpacking depictions of artificial intelligence. Its use in predictive policing to forecast crimes in time and space is largely an exercise in spatial statistics that in principle can make policing more effective and more surgical. Its use in criminal justice risk assessment to forecast who will commit crimes is largely an exercise in adaptive, nonparametric regression. It can in principle allow law enforcement agencies to better provide for public safety with the least restrictive means necessary, which can mean far less use of incarceration. None of this is mysterious. Nevertheless, concerns about accuracy, fairness, and transparency are real, and there are tradeoffs between them for which there can be no technical fix. You can't have it all. Solutions will be found through political and legislative processes achieving an acceptable balance between competing priorities.

Artificial Intelligence, Predictive Policing, and Risk Assessment for Law Enforcement

There are widespread concerns about the use of artificial intelligence in law enforcement. Predictive policing and risk assessment are salient examples. Worries include the accuracy of forecasts that guide both activities, the prospect of bias, and an apparent lack of operational transparency. Nearly breathless media coverage of artificial intelligence helps shape the narrative. In this review, we address these issues by first unpacking depictions of artificial intelligence. Its use in predictive policing to forecast crimes in time and space is largely an exercise in spatial statistics that in principle can make policing more effective and more surgical. Its use in criminal justice risk assessment to forecast who will commit crimes is largely an exercise in adaptive, nonparametric regression. It can in principle allow law enforcement agencies to better provide for public safety with the least restrictive means necessary, which can mean far less use of incarceration. None of this is mysterious. Nevertheless, concerns about accuracy, fairness, and transparency are real, and there are tradeoffs between them for which there can be no technical fix. You can't have it all. Solutions will be found through political and legislative processes achieving an acceptable balance between competing priorities.

3: Consulting the Record: AI Consistently Fails the Public - AI Now Institute

Amid the excitement over AI’s (speculative, hypothetical) potential, we have lost sight of the sobering reality of its present and recent past. AI is already intermediating critical social infrastructures, materially reshaping our institutions in ways that ratchet up inequality and concentrate power in the hands of the already powerful. It is consistently deployed in ways […]

Artificial intelligence in government: why people feel they lose control

The use of Artificial Intelligence (AI) in public administration is expanding rapidly. While AI promises greater efficiency and responsiveness, its integration into government and administration ra...

People know AI is risky. They just don’t know what to do about it. | TrendLife Blog

New international research from TrendLife reveals a wide gap between AI adoption and awareness of AI-powered threats.

How Shifting Responsibility for AI Harms Undermines Democratic Accountability | TechPolicy.Press

The moralization of individual AI use deflects responsibility away from powerful actors like corporations and governments, Suvradip Maitra and others write.