AI and Machine Knowing: A new challenge for CPTED and crime prevention

This Saturday's ICA Masterclass on CPTED White Papers will explore frontier AI systems, machine learning, and the pros and cons of AI and CPTED. The session is a primer for the AI and CPTED sessions at the 2026 CPTED conference, Oct 2-4 in Calgary. 

by Gregory Saville

Artificial intelligence is arriving in crime prevention faster than many practitioners realize. We’ve been posting blogs about AI in crime prevention for years. In my 2023 blog, Stop Dave, I’m Afraid, I reported on Smart City research by Finnish AI researchers.  

Last year, in Gambling with the Future I summarized Nobel Laureate, Professor Geoffrey Hintons’ warning at the latest AI conference. In What 1980s Weather models taught me about crime prediction I described my own research experience with scientific weather forecasting models. 

Today the story has expanded again. From predictive analytics and digital twins to large language models and autonomous surveillance systems, the question is no longer whether AI will influence CPTED. The question is how.

For decades, CPTED practitioners have focused on the relationship between people and places. We have examined territoriality, access control, surveillance, maintenance, social cohesion, and neighborhood capacity. Yet frontier AI systems introduce something new into that equation: machine knowing.

ARE YOU USING A FRONTIER SYSTEM?

Frontier systems include leading generative LLMs such as ChatGPT, Claude, and Gemini, along with advanced multimodal systems that work with images, audio, and video. They are less common in predictive analytics, such as hotspot mapping and crime forecasting. Some frontier systems are now becoming agentic, meaning they can pursue goals with limited supervision, although these remain in the early stages of deployment.

Frontier systems raise a new question: What happens when a machine begins interpreting places, risks, and human behavior alongside, or instead of, human observers?

That question forms the foundation of the Masterclass this Saturday. The session serves as a primer for the larger AI and CPTED discussions planned for the ICA Conference in Calgary this October.

AI-assisted auditing may help practitioners identify environmental risks, but human interpretation remains essential - AI generated imagery for this blog 

SATURDAY’S MASTERCLASS 

On Saturday, the Masterclass begins with an unusual exercise. I begin with a conversation between myself and the same AI system chatbot I used throughout the development of the CPTED and AI White Paper. The purpose is not to demonstrate technology, but to explore a deeper question. How should we relate to an intelligence that can reason, explain, persuade, and create knowledge while making mistakes that appear convincing?

One of the most important concepts discussed will be the phenomenon known as a confabulation rate. In 2023, I described the problem of AI hallucinations. Confabulation takes that concern a step further. 

It refers to the frequency with which an AI system generates information that may be partly true and sounds plausible but is incorrect or entirely fabricated.

The future of prevention may depend less on what AI knows and more on how communities use that knowledge - AI-generated image for this blog

WHY DOES THIS MATTER IN PREVENTION? 

Confabulation matters because prevention professionals increasingly rely on digital information. If AI is used to analyze crime patterns, evaluate risk, generate recommendations, support neighborhood planning, or advise decision-makers, practitioners must understand both its capabilities and its limitations. Errors like confabulation rates may never vanish, so we must understand when and how they occur.

The opportunities and risks are extraordinary. The future of CPTED and crime prevention will not be shaped only by better environmental design or social cohesion. It will also be shaped by how we choose to work with increasingly powerful forms of machine intelligence.

Join me on Saturday, June 27 as we begin exploring that future.