In our second presentation on AI for the series, Professor Melissa Hamilton, Professor of Law and Criminal Justice, University of Surrey explores the evolving landscape of AI in policing, and focusses on three aspects:

facial recognition,
algorithmic risk assessment,
robotics.

Facial recognition can assist in locating missing individuals and improve the speed and accuracy of criminal investigations.

Algorithmic risk assessment tools can automate and streamline the assessment process, leading to faster decision-making and more objective assessments.

Robotics can expand police resources, provide information to the public, and be used for real-time alert systems.

All of which help to improve public confidence, guidelines, regulations, transparency, fairness, inclusivity, and accountability are essential.

Keywords
AI in policing, facial recognition, algorithmic risk assessment, robotics, public safety, efficiency, privacy concerns, transparency, fairness, inclusivity, accountability

Takeaways
Facial recognition technology can improve the speed and accuracy of criminal investigations.
Algorithmic risk assessment tools can automate and streamline the assessment process in law enforcement.
Robotics can expand police resources and be used for real-time alert systems.
Guidelines, regulations, transparency, fairness, inclusivity, and accountability are important for building public confidence in the use of AI in law enforcement.

Sound Bites
"Fascinated to see what kind of potential benefits AI technologies can bring to law enforcement processes."
"Increasing the size of available datasets can improve the accuracy and expand the scope and abilities of facial recognition technologies."
"Algorithmic risk assessment tools can automate and streamline the assessment process, enabling faster decision-making and potentially better resource allocation."

Chapters
00:00 - Introduction
01:17 - Facial Recognition
04:09 - Algorithmic Risk Assessment
09:17 - Robotics in Policing
12:14 - Building Public Confidence


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