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History & Culture - The Alignment Problem: Machine Learning and Human Values

Description

Book Synopsis: 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.

Details

Are you ready to dive into the captivating world of AI systems and the urgent need to fix them? Look no further than "The Alignment Problem: Machine Learning and Human Values." This groundbreaking book by Brian Christian will open your eyes to the challenges and risks posed by machine-learning systems in today's society. Join the movement to address ethical concerns and strive for alignment between human values and artificial intelligence.

Discover the alarming reality of how machine-learning systems are shaping our world without always aligning with our intentions. From gender biases in hiring to disparities in judicial decisions, the consequences of misaligned AI systems are becoming increasingly apparent. "The Alignment Problem" offers a gripping exploration of the risks we face as we relinquish control to intelligent machines on various fronts.

Step into the realm of mathematical and computational models that are revolutionizing industries and challenging our reliance on human judgment. Brian Christian's compelling narrative introduces you to the pioneers working to solve the alignment problem before it spirals out of control. Gain insight into the evolving landscape of machine learning and the critical role it plays in our society's future.

Immerse yourself in a powerful reflection on humanity's biases, cultural norms, and the intricate dance between technology and society. "The Alignment Problem" is a thought-provoking journey that sheds light on our inherent blind spots and unspoken assumptions. This interdisciplinary masterpiece will leave you pondering the impact of our decisions and the potential for a brighter, more aligned future.

Take action now and delve into the world of AI ethics with "The Alignment Problem."

Disclosure: I get commissions for purchases made through links in this website