AI Resources

As a companion piece to our AI primer, Hello, World: Artificial Intelligence and its Use in the Public Sector, this page is an evolving directory of tools and resources that OPSI believes may be useful for civil servants interested in the use of AI in government. If you would like to suggest additions to this list, please add a comment to this page or e-mail us at [email protected].

  • OECD OPSI AI Strategies page: This resource includes a list of 50 different national approaches and strategies for AI, with a specific focus on how they include considerations for the public sector.
  • Data Maturity Framework (University of Chicago): Resource was created by the City of Chicago and helps government agencies better understand their data, how it can be used, and how their data collection and data management may be improved.
  • The AI Hierarchy of Needs: This resource is used in the report, and maps AI requirements to Maslow’s hierarchy of needs. It explains the process of how to go from data collection all the way to deep learning and ‘true’ AI.
  • Machine Learning Glossary:Provides a list of all the important keywords and vocabulary, as well as examples, related to AI
  • Assessing if artificial intelligence is the right solution (UK Government): Provides a tool for understanding whether or not AI is the correct tool for a given problem. It is a straight-forward and easy to use guide that, when used, could help avoid a situation where costly AI development projects are started when they need not be.
  • Ethics & Algorithms Toolkit: A toolkit and framework that allows any agency implementing a new AI project to better understand the ethical considerations/potential impacts that may arise.
  • Guidelines for AI Procurement: An overview about how to organize public procurement related to new AI projects taking into consideration the complex and diverse issues and challenges associated with AI projects.
  • Algorithmic Impact Assessment (Government of Canada): An open source tool that allows for an agency to study and understand better the potential impact of a given algorithm.
  • Aequitas (University of Chicago): A tool that allows for an agency to audit the potential impacts of their new machine learning algorithms. More specifically, this tool focuses on understanding better and finding potential bias.
  • Towards Data Science: One of the top places to go for news related to the newest developments of AI. It provides many new insights into all facets of AI, both technical and non-technical.
  • KDnuggets: Provides many different articles and tutorials related to data science and AI.
  • Kaggle: A place where government agencies can post AI challenges, and solutions can be crowdsourced in a competition type format. It is also a great place for government employees to practice and hone their data science skills.
  • Elements of AI: A free online course that was launched firstly in Finland, but has now spread to numerous other countries. It provides background information on the topic of AI.
  • Google AI – Education: Provides numerous free learning opportunities covering both the technical side of AI, as well as the government and citizen-facing side of AI. There are both reports and courses available to assist any interested stakeholder group.
  • Coursera – Machine Learning: A common place for new students of machine learning to start, it is possible to learn the beginning technical background here.
  • Spinning Up in Deep Reinforcement Learning: A resource provided by the OpenAI group and provides those with more experience in AI to learn and study deep learning.
  • Udemy AI Courses: Low-cost (some free) online courses on a variety of topics.
  • EDUCBA – Data Science Tutorials – Free Data Science tutorial contains information on Data Science Career, Hadoop, Machine Learning, Big Data, Tableau Tutorial, DevOps, Artificial intelligence Interview Questions, Data & Analytics Tools, Data and Analytics Basics, and Head to Head Differences.

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