Launching Actionable AI Ethics!
Forthcoming book to be published by Manning Publications that will help you transform theory into practice for your research and work in AI development and deployment!
A really warm welcome to Actionable AI Ethics by me, Abhishek Gupta!
Purpose of this newsletter:
I firmly believe in the power of serendipity and the community - we all bring with us our lived experiences that has the potential to create meaningful change that is rooted in real-world impact rather than hypothetical scenarios. This newsletter will be my effort at being transparent with my audience in sharing the development journey of this book. Along this road, you will find:
Morsels of useful tools, techniques, and frameworks that are heavily biased towards action
Discussions on the evolving landscape of AI ethics in practice and community-driven insights that will help us shape together the conversation and express our needs in creating artefacts that will make our research and work easier in implementing AI ethics in practice.
This is meant to be a participatory space, we, together as a community, have the power to break away from technological fatalism and co-create responsible AI systems that adhere to the norms and values that make us who we are. Please use the comment space with each of these posts as a way of surfacing some of the toughest challenges that create a barrier in implementing AI ethics in practice and let us work together to lower and remove those barriers!
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Additionally, if you believe that your colleagues, friends, community, and your network could benefit from operationalizing some of the work in responsible AI, please share this with them:
Keep reading below to find more information about the book …
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.
The main ideas communicated in this book are:
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.
You don’t need to be a researcher specialized in the field of AI ethics to apply advances in this field to your work.
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.
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