The Alignment Problem: Machine Learning and Human Values, reviewed

//The Alignment Problem: Machine Learning and Human Values, reviewed

The Alignment Problem: Machine Learning and Human Values, reviewed

The Alignment Problem

We look at this topical book which addresses the many challenges of using AI to produce accurate, safe and informative results. Written by Brian Christian you can see more on his website here.

The Alignment Problem: Machine Learning and Human Values, reviewed

This is a complex but fascinating area. As we look to AI more and more to solve some of our deeper and more complex problems, this can also throw up many questions and potentially lethal outcomes if we are not careful. This is all long before we come anywhere near a general AI either. Christian accurately explains and exemplifies why, if we do not really carefully define the questions that we ask our AI programs to solve, we may well be whistling in the dark in terms of their ability to come up with meaningful solutions.

Sometimes AI based work has created some really impressive solutions, and Christian does well at communicating these results. However he also explains well about many times, especially if the AI is using a black box algorithm, ie, one where we don’t know how it comes up with the results, then there are some serious risks inherent in this approach. This book is a deep dive into the world of machine learning, but it is written well, and very much accessible, and perhaps even aimed at the general reader.

We found the book well written, understandable, and super important in terms of raising important issues and questions that we need to be considering and planning for, well before we simply let AI / machine learning based programs loose on wider areas of our lives. Read this book!

More about the book

A jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them.

Today’s “machine-learning” systems, trained by data, are so effective that we’ve invited them to see and hear for us—and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem.

Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole—and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands.

The mathematical and computational models driving these changes range in complexity from something that can fit on a spreadsheet to a complex system that might credibly be called “artificial intelligence.” They are steadily replacing both human judgment and explicitly programmed software.

In best-selling author Brian Christian’s riveting account, we meet the alignment problem’s “first-responders,” and learn their ambitious plan to solve it before our hands are completely off the wheel. In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Readers encounter a discipline finding its legs amid exhilarating and sometimes terrifying progress. Whether they?and we?succeed or fail in solving the alignment problem will be a defining human story.

The Alignment Problem offers an unflinching reckoning with humanity’s biases and blind spots, our own unstated assumptions and often contradictory goals. A dazzlingly interdisciplinary work, it takes a hard look not only at our technology but at our culture?and finds a story by turns harrowing and hopeful.

More about Brian Christian

Brian Christian is the author of The Most Human Human, which was named a Wall Street Journal bestseller, a New York Times Editors’ Choice, and a New Yorker favorite book of the year. He is the author, with Tom Griffiths, of Algorithms to Live By, a #1 Audible bestseller, Amazon best science book of the year and MIT Technology Review best book of the year.

His third book, The Alignment Problem, has just been published.

Christian’s writing has been translated into nineteen languages, and has appeared in The New Yorker, The Atlantic, Wired, The Wall Street Journal, The Guardian, The Paris Review, and in scientific journals such as Cognitive Science. Christian has been featured on The Daily Show with Jon Stewart, Radiolab, and The Charlie Rose Show, and has lectured at Google, Facebook, Microsoft, the Santa Fe Institute, and the London School of Economics. His work has won several awards, including fellowships at Yaddo and the MacDowell Colony, publication in Best American Science & Nature Writing, and an award from the Academy of American Poets.

Born in Wilmington, Delaware, Christian holds degrees in philosophy, computer science, and poetry from Brown University and the University of Washington. A Visiting Scholar at the University of California, Berkeley, he lives in San Francisco.

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By | 2021-08-22T16:21:52+00:00 August 22nd, 2021|Technology|Comments Off on The Alignment Problem: Machine Learning and Human Values, reviewed