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The Alignment Problem

Machine Learning and Human Values

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The Alignment Problem

Yazan: Brian Christian
Seslendiren: Brian Christian
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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.

Computer Science History & Culture History & Philosophy Machine Theory & Artificial Intelligence Philosophy Science Technology & Society Düşündürücü
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Great overview of the current machine learning landscape and importantly how we got here. Useful sections on uncertainty and safety with strong concluding remarks on models in general. The map is not the territory.

Don't think machine learning's important? Read on.

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AI is part of our lives now. Read this to understand it. Well written, explains complex topics well.

A must read

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A short history of AI, machine learning, and reinforcement learning. Touches on the philosophical, ethical, psychological, and political aspects of AI. A must-read for anyone on the cutting edge of tech, or with a casual interest in that.

Excellent

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Great book that touches on a lot of concepts and some underlying theory, mixed with examples and philosophy

Better than expected

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well organized summary of current research on Alignment. you don't have to be ML expert to read this book, but some ML knoladge would be definitely helpful.

Very inspiring book

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