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Reid Blackman - Ethical Machines: Your Concise Guide to Totally Unbiased, Transparent, and Respectful AI

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Reid Blackman Ethical Machines: Your Concise Guide to Totally Unbiased, Transparent, and Respectful AI
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What will you do when your AI misbehaves?

The promise of artificial intelligence is automated decision-making at scale, but that means AI also automates risk at scale. Are you prepared for that risk?

Already, many companies have suffered real damage when their algorithms led to discriminatory, privacy-invading, and even deadly outcomes. Self-driving cars have hit pedestrians; HR algorithms have precluded women from job searches; mortgage systems have denied loans to qualified minorities. And often the companies who deployed the AI couldnt explain why the black box made the decision it did.

In this environment, AI ethics isnt merely an academic curiosity, its a business necessity. In Ethical Machines, Reid Blackman gives you all you need to understand AI ethics as a risk management challenge. Hell help you build, procure, and deploy AI in a way thats not only ethical but also safe in terms of your organizations reputation, regulatory compliance, and legal standingand do it at scale.

And dont worrythe books purpose is to get work done, not to ponder deep and existential questions about ethics and technology. Blackmans clear and accessible writing helps make a complex and often misunderstood concept like ethics easy to grasp. Most importantly, Blackman makes ethics actionable by tackling the big three ethical risks with AIbias, explainability, and privacyand tells you what to do (and what not to do) to mitigate them.

With practical approaches to everything from writing a strong statement of AI ethics principles to creating teams that effectively evaluate ethical risks, Ethical Machines is the one guide you need to ensure your AI advances your companys objectives instead of undermining them.

Reid Blackman: author's other books


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Contents
Guide
ACKNOWLEDGMENTS

This book lives at the endor hopefully, the middleof a journey I didnt see coming and didnt know I was preparing to make. Ive taken too many steps to recount them all here, and Ive been enabled to take the trip by more people than I can remember. But some stand out.

Brad Cokelet and Guha Krishnamurthi took the time to read the entirety of this manuscript and provided invaluable feedback. I hereby acknowledge that, to the extent these pages contain any misleading or just plain false statements, they are the appropriate objects of blame.

Alex Grzankowski and Eric Vogelstein. I asked both to read the manuscript and they refused. One must acknowledge their abject failure at friendship. Two other people made the commitment but didnt read it, though I have to acknowledge that Im not nearly close enough with them to facetiously call them out by name. My only regret in life is that they probably wont read this either, and so neither guilt nor shame shall visit them.

Blair Beyda, Brent Weisenberg, Eric Corriel, Eric Siwy, David Palmer, and Jared Dietch are all wonderful people and have had an enormous positive impact on my life. One must acknowledge, however, their relatively minimal impact on this book.

My grandparents Rita and Herb Diamond (aka Gee-Gee and Poppy) were simultaneously possessed of a great intensity and lightness of heart. Theyd stare you down and call bullshit, and in the next breath, theyd crack a joke. They were curious. They pushed the envelope. They looked at things differently. They were irreverent. My editor, the wonderful Scott Berinato, spoke frequently about my voice in this book. But its not my voice. Its Gee-Gee and Poppys. They, and they alone, are to credit for my desire to dig deep into an issue and to blame for my lack of professionalism.

My parentsRandi and Brad Blackmaninstilled in me an entirely unreasonable degree of confidence that forbids me from thinking I cant do something, like getting a PhD in philosophy, landing a job afterward in a terrible market, and starting and growing, of all things, an ethics consultancy. Their continual belief in me and their borderline maniacal love has been, and will always be, the ground I stand on.

On our first international trip together, when we were still dating, my wife and I rented a car in a relatively obscure city in Peru. After colliding with a motorcycle carrying two people and being placed in a police car, the officer asked if I had been drinking. Leah (aka Tootz), who was in the back seat, immediately became infuriated. No, nunca! she exclaimed. Eight years later, when I decided to leave academia and start a business, she earned the income without which I wouldnt have had the ramp I needed to build it. And if she didnt take care of our two young children on the weekends that I worked on this book, you wouldnt be reading these words right now. In all things, if I can move forward, its only because she has my back.

ABOUT THE AUTHOR

REID BLACKMAN, P H D, is the CEO and founder of Virtue, where he works with companies to integrate ethical risk mitigation into the development and deployment of artificial intelligence and other emerging technologies. Reid was a founding member of Ernst & Youngs Artificial Intelligence Advisory Board, and he volunteers time to the nonprofit Government Blockchain Association, where he is the Chief Ethics Officer.

Prior to founding Virtue, Reid was a professor of philosophy at Colgate University and the University of North Carolina, Chapel Hill. He also founded a fireworks wholesaling company and was a flying trapeze instructor. He received his BA from Cornell University, his MA from Northwestern University, and his PhD from the University of Texas, Austin.

He has contributed to Harvard Business Review and TechCrunch , his work was profiled in the Wall Street Journal , and he speaks at events and businesses around the world.

CONCLUSION
Two Surprises

If you told me you were going to a conference on AI ethics, and that at a cocktail reception, you walked up to a group of attendees already discussing the topic, I could confidently tell you what was about to happen.

First, youre going to hear a lot of familiar phrases and buzzwords. Youll hear Accountability. Transparency. Explainability. Fairness. Surveillance. Governance. Trustworthy. Responsible. Stakeholders. Framework. Someones going to say black box at some point.

Then, therell be hand-wringing over the threats posed by AI gone wild. Biased data sets! Unexplainable algorithms! Invasions of privacy! Self-driving cars killing people!

Finally, the group will land on a healthy skepticism. You cant really define AI ethics, you might hear. And You cant plan for everything. Of course, also, Its just peoples own personal view of whats right and wrong. Or, more practically, Look, how do you even operationalize ethical principles? One person is going to say something about KPIs.

At the end of all this, there will be shrugs. Thats because, for the most part, people are raising issues, the underpinnings of which are not (well) understood, and then, after theyve put together a conference in which they sling buzzwords back and forth at each other, they declare AI ethics essential, of course, but also really, really difficult.

But not you. Having gotten to this point in the book, you can see those underpinnings. You see whats at issue, from both a business and an ethical perspective. And now that you understand it, you understand that AI ethics isnt so difficult after all.

If a colleague tells you, We need to say something about AI ethics, you know what a meaningful document looks like and whats superficial PR.

If your colleague tells you, This AI ethics is for the AI folks. Its technical. Tell them to get on it, you know how impoverished an understanding that is.

Maybe a company comes to you and says, We have your solution for responsible AI or, less ambitiously, We have your solution for bias in AI. That piece of software, you now see, cant solve all those problems by itself.

You know that and so much more about, for example, the role of people in creating appropriate metrics for fairness. And about when you need to know what the AIs are doing and when it doesnt matter so much. You know there are levels of privacy, and its not just about anonymity. You know how to build real AI ethics statements, and that just saying you value AI ethics doesnt mean your employees will take AI ethics seriously. You know you need Structure to make that happen. Most of all, you know software alone can neither handle the substantive ethical issues nor effect the kind of organizational change you need to systematically and comprehensively identify and mitigate AIs ethical risks. In short, provided the software can do its job, you see the ecosystem in which the software needs to get embedded.

You see the AI ethics landscape. Now, you can navigate it.

And now that youre here, Im going to let you in on a secret. Two, actually.

The first secret is that theres another book in this book. Pretend are a single book and delete the word AI whenever I said AI ethics. What youll get, with some minor tweaks here and there, is a book on how to articulate and operationalize the ethical values of your organization. I dont care if youre developing AI, putting microchips in peoples hands, or just selling bottled coffee: the way to create, scale, and maintain an ethically sound organization is already contained in those pages. If your aim is not only to create ethically sound AI, but to create an organization that takes ethical standards seriously, go back and reread those chapters with that in mind.

The second secret is that this book is about AI ethics, but its not only about AI ethics. Its about the value of ethical inquiry. Its about the power and importance of philosophical investigation.

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