Welcome to Actionable AI Ethics

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Why Actionable AI Ethics?

Here is a presentation titled Why Actionable AI Ethics? that will explain the rationale behind why this is needed now!

Aim of the book

The aim of the book is to guide everyday practitioners to apply principles and guidelines in the domain of AI ethics to the AI development and deployment lifecycle, translating high-level, abstract ideas into concrete and measurable techniques with minimal friction to meet the goal of building ethical, safe, and inclusive AI systems that are aligned with the values of their organization. The uniqueness of the book is that it surfaces the signal from the noise that surrounds the fragmented tooling and framework landscape in AI ethics.

The book is meant to serve as an ageless text for readers to return to when wrestling with the domain of AI ethics and they are looking for practical guidance. While some tools may fade over a long time horizon, the core principles and their practical foundations as expressed in this book will continue to serve them long into the future, allowing them to easily integrate any new tools that arise.

Primary message of the book

The primary message that the book articulates is that barriers to adoption of these principles, especially when research and development in the domain of AI ethics isn’t their primary job function, shouldn’t discourage them from integrating these ideas into their workflow. An actionable guide that creates an intermediate bridge between the principles and the tools and techniques available in the AI ethics domain will allow seamless integration giving organizations the opportunity to evoke a high degree of trust from their customers in the products and services that they build.

Learning journey of the book

Learning begins by orienting the reader in the most frequently encountered areas of concern in the domain of AI ethics. This is linked to emerging legislations, regulations, and other guidelines being published allowing the reader to make an immediate connection with some of the compliance and other requirements that the organization might ask of them in their roles. This is followed by a bridge segment that starts to put together the context and foundations for linking these ideas to the AI development and deployment lifecycle so that the reader builds up intelligence on how to think about these ideas more concretely, seeing how this relates to diverse stakeholders who are a part of the product and service design, development, and deployment. The journey then makes its final leg into the applied tools and techniques that equip the reader to concretely operationalize the bridge in their work. By utilizing a DAM (detect, address, and monitor) framework, the reader is guided in practically, and with minimal friction, integrating this framework in their everyday workflows to maximize adoption within the organization.

Main ideas communicated in the book

  1. AI Ethics is not a domain that only consists of abstract ideas but has many tangible tools and techniques which when linked together through a bridge can lead to an organization building ethical, safe, and inclusive AI systems.

  2. You don’t need to be a researcher specialized in the field of AI ethics to apply advances in this field to your work.

  3. AI ethics is not a burdensome add-on to the workflow of the developer, when done through the framework prescribed in the book, it leads to building better and more effective products and services that meet the needs of more customers and users.

Newsletter for the book

To stay up-to-date on the content of the book and learn more about AI Ethics, please sign up here: Actionable AI Ethics

You can also learn more about the AI Ethics domain in general from the other newsletter that is authored by Abhishek Gupta for the Montreal AI Ethics Institute here.

More about the author

Abhishek Gupta is the founder of Montreal AI Ethics Institute and a Machine Learning Engineer at Microsoft where he serves on the CSE Responsible AI Board. He is representing Canada for the International Visitor Leaders Program (IVLP) administered by the US State Department as an expert on the future of work.

He additionally serves on the AI Advisory Board for Dawson College and is an Associate Member of the LF AI Foundation at the Linux Foundation. Abhishek is also a Global Shaper with the World Economic Forum and a member of the Banff Forum. He is a Faculty Associate at the Frankfurt Big Data Lab at the Goethe University, an AI Ethics Mentor for Acorn Aspirations and an AI Ethics Expert at Ethical Intelligence Co. He is the Responsible AI Lead for the Data Advisory Council at the Northwest Commission on Colleges and Universities. He is a guest lecturer at the McGill University School of Continuing Studies for the Data Science in Business Decisions course on the special topic of AI Ethics. He is a Subject Matter Expert in AI Ethics for the Certified Ethical Emerging Technologies group at CertNexus. He is also a course creator and instructor for the Coursera Certified Ethical Emerging Technologist course. He’s the Founding Editorial Board Member at the Springer Nature AI and Ethics Journal.

His research focuses on applied technical and policy methods to address ethical, safety and inclusivity concerns in using AI in different domains. He has built the largest community driven, public consultation group on AI Ethics in the world that has made significant contributions to the Montreal Declaration for Responsible AI, the G7 AI Summit, AHRC and WEF Responsible Innovation framework, PIPEDA amendments for AI impacts, Scotland’s national AI strategy and the European Commission Trustworthy AI Guidelines. His work on public competence building in AI Ethics has been recognized by governments from North America, Europe, Asia, and Oceania. More information on his work can be found on his website.

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