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Michael Kearns and I wrote a book! Its called "The Ethical Algorithm: The Science of Socially Aware Algorithm Design", and its going to be published by Oxford University Press in the fall. Let me tell you about it! (Thread)
First, its not a textbook: its a "trade book" -- a popular science book. Its intended readership isn't just computer science PhDs, but the educated public broadly. But there should be plenty in it to interest experts, because we cover quite a bit of ground.
The book is about the problems that arise when algorithmic decision making interacts with human beings --- and the emerging science about how to fix them. The topics we cover include privacy, fairness, strategic interactions and gaming, and the scientific reproducibility crisis.
Lots has been written about the problems that can arise, especially related to privacy and fairness. This includes the terrific work of @mathbabedotorg @FrankPasquale @schneierblog @PopTechWorks @safiyanoble @zephoria. And we're not trying to reinvent the wheel. Instead,
The focus of our book is the exciting and embryonic algorithmic science that has grown to address these issues. The privacy chapter develops differential privacy, and its strengths and weaknesses. The fairness chapter covers recent work by the @fatconference community.
The gaming chapter studies how algorithm design can affect the equilibria that emerge from large scale interactions. The reproducibility chapter explores the underlying issues that lead to false discovery, and recent algorithmic advances that hold promise in avoiding them.
We try and set expectations appropriately. We don't pretend that the solutions to complex societal problems can be entirely (or even primarily) algorithmic. But we argue that embedding social values into algorithms will inevitably form an important component of any solution.
Anyhow, I'm excited for it to come out. We are indebted to too many people to name here. Each of the chapters is about a research area I've had the pleasure to work in, and my friends and colleagues have shaped my views about every aspect of what we write about.
The early reviewers helpfully cautioned us against sounding too much like "techno-optimists", putting undue faith in very early science. We took this to heart. The focus is intentionally on the algorithmic science, but hopefully our discussion is appropriately measured.
We are advocating for the scientific process that the work we cover represents, not for the direct adoption of existing methods. It is very early days - but thats what makes the field so exciting --- an excitement that what we hope the book conveys!
Michael gave a talk about the book at Toronto: it was recorded, and you can watch it here:
