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NP21 Applied AI in Police

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Why AI?

AI is revolutionizing the police sector by enhancing predictive policing, automating routine tasks, and improving decision-making processes. Its importance and urgency lie in the increasing demands for public safety, the need for efficient law enforcement operations, and the potential to reduce human biases in policing activities.

For any professional in this sector, this playbook will get you started on this urgent and inevitable journey. Don’t miss out on the AI revolution – download the paper, read and apply.

YOU WILL LEARN:

  1. Predictive policing to forecast crime and deploy resources.
  2. Facial recognition for identifying suspects and finding missing persons.
  3. Natural language processing for monitoring threats on social media.
  4. Automated license plate recognition for tracking vehicles.
  5. Digital evidence analysis for quicker case resolutions.
  6. Real-time surveillance with anomaly detection for public safety.
  7. AI-driven chatbots for efficient public reporting and inquiries.
  8. Sentiment analysis to gauge community sentiments and concerns.
  9. Crime pattern analysis to understand and prevent future crimes.
  10. Training simulations for preparing officers for complex scenarios.

FREE RESOURCES:

SOME FLASHCARDS
(PDF, 24 pages, 10×10) 
This PDF captures the main ideas from the paper. Easily shareable on SoMe for a start of an online conversation about AI in your industry.

CHEAT SHEET
(PDF, 2 pages, A4)
This PDF contains the main ideas from the paper, for your easy reference.

USE CASES
(PDF, 16 pages, 4×3) 
This PDF contains an overview of the 10 main AI use cases for this industry.

To get started with AI, first do this:

  1. Assess Needs and Capabilities: Identify areas where AI can have the most impact and evaluate current technological capabilities.
  2. Develop Ethical Frameworks: Establish guidelines to ensure AI is used responsibly and ethically, respecting privacy and civil liberties.
  3. Pilot Projects: Start with small-scale pilot projects to test AI applications, gather data, and refine approaches before broader implementation.
  4. Explore other resources on nextpaper.me and check out the book “Explain for me AI”.
  5. Please contact us at hello@nextpaper.me for further exploration or inspiration through a talk, workshop or case study. We’d love to help!
Picture of Silvija Seres

Silvija Seres

Mathematician & AI Investor
SILVIJA SERES - Mathematician and AI investor
I have worked with AI for more than 30 years in research, development and strategy. I am very interested in helping companies drive successful digital transformation and AI applications. If you find this interesting, please get in touch on hello@nextpaper.me

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