Artificial intelligence (AI) has taken the world by storm, becoming a marketing buzzword and hotly commented subject in the press. Over the last few years there have been several important milestones in AI, in particular in terms of image, pattern and speech recognition, language comprehension and autonomous vehicles. Advancements such as these have prompted the healthcare, automotive, financial, communications and many more industries to adopt AI in pursuit of its transformative potential. How can AI benefit law enforcement and why might this be dangerous? Law enforcement is an information-based activity.

No one should trust Artificial Intelligence (AI). Trust is a relationship between peers in which the trusting party, while not knowing for certain what the trusted party will do, believes any promises being made. AI is a set of system development techniques that allow machines to compute actions or knowledge from a set of data. Only other software development techniques can be peers with AI, and since these do not "trust", no one actually can trust AI. More importantly, no human should need to trust an AI system, because it is both possible and desirable to engineer AI for accountability. We do not need to trust an AI system, we can know how likely it is to perform the task assigned, and only that task.

Inc. shut down a project it had been developing for four years, a recruitment tool driven by machine learning. The concept was a simple and appealing one: at its core, the project aimed to develop an algorithm that would sort incoming job applications to isolate the short list for managers to use in making their final selections. Anyone who has been involved in such a process knows that isolating the top five or ten resumés from dozens of applicants is a time-consuming job. Any process that brings logic and speed to this stage of the recruitment chain can only be a good thing. But algorithms are only as good as the data used to drive them, and in the Amazon case the machine "learning" was based on patterns in applications submitted to the firm in the previous ten years.