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.
- New South Wales (NSW) Emerging Technology Guide: AI: Provides an overview of different aspects of AI, including, but not limited to: definitions, background information, risks, ethics benefits, and strategies
- Data.gov’s Primer on Machine Readability for Online Documents and Data: Provides background information about key terms necessary for the implementation of AI. It covers especially all the key terminology needed to understand better data.
- OECD Recommendation of the Council on Artificial Intelligence: This resource puts forth the OECD’s instrument on AI. The recommendation was adopted by the OECD in 2019.
- Artificial Intelligence in Society (OECD): Draws on insights from leading experts in the field of AI to tackle concrete and hard questions related to the introduction and implementation of AI in the public sector.
- A guide to using artificial intelligence in the public sector (UK Government): Provides the UK Government’s what exactly is AI, and how it may be used in the public sector.
- Artificial Intelligence: A European Perspective: Presents the European Union’s approach and understanding towards AI. It covers all dimensions associated with AI including the economic, political, legal, educational, and societal. For anyone interested in gaining a more comprehensive understanding of AI, this would be a great resource.
- AI Index 2019 Annual Report (Human-Centered AI Institute, Stanford University): Tracks, collates, distills, and visualizes data relating to artificial intelligence. Includes a link to a Google Drive with interesting data sets used for the report.
- G20 Ministerial Statement on Trade and Digital Economy: G20 ministerial statement on the usage of AI. It explores the different risks and benefits associated with AI, and outlines the goals and paths forward for future widespread introduction of AI.
- Embracing Innovation in Government: Global Trends 2019 (OECD): Explores the different ways in which governments around the world are embracing disruptive technologies in the public sector. It covers both the different technological use cases, as well as policy related aspects.
- Data Ethics Framework (UK Government): Provides an overview of the UK’s framework/approach to the ethical usage, regulation, and implementation of AI.
- Understanding Artificial Intelligence Ethics and Safety (The Alan Turing Institute): Covers how to implement and use ethical best practices throughout the entire AI process, from design to implementation.
- Ethics Guidelines for Trustworthy AI (European Union): Represents the results of a high level EU meeting and aims to advance the implementation of trustworthy-AI. It provides a framework for how to ensure that AI is created and used in an ethical and trustworthy manner.
- 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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