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In How To Think About AI, Richard Susskind draws on his experience of working on AI since the early 1980s. For Susskind, balancing the benefits and threats of artificial intelligence is the defining challenge of our age. He explores the history of AI and possible scenarios for its future. His views on AI are not always conventional. He positions ChatGPT and generative AI as no more than the latest chapter in the ongoing story of AI and claims we are still at the foothills of developments.

Shannon Vallor makes a wide-ranging, prophetic, and philosophical case for what AI could be: a way to reclaim our human potential for moral and intellectual growth, rather than lose ourselves in mirrors of the past. Rejecting prophecies of doom, she encourages us to pursue technology that helps us recover our sense of the possible, and with it the confidence and courage to repair a broken world. Vallor calls us to rethink what AI is and can be, and what we want to be with it.

A gripping journey of discovery, The Catalyst moves from the early experiments that first hinted at RNA's spectacular powers, to Cech's own paradigm-shifting finding that it can catalyze cellular reactions, to the cutting-edge biotechnologies poised to reshape our health.

Microfluidics is the field of science that studies fluids constrained to spaces that are smaller than one millimeter wide, and by extension, the engineering field which builds devices that exploit the unique properties of fluids at these scales. Author Albert Folch explores this micro science which has inspired engineers to build devices such as engines, spray cans, ballpoint pens, inkjet and 3D printers, pregnancy and Covid tests, glucometers, asthma nebulizers, kidney dialysis machines, and DNA analyzers.

Researchers, developers, business leaders, policy makers, and others are expanding the technology-centered scope of artificial intelligence (AI) to include human-centered AI (HCAI) ways of thinking. This expansion from an algorithm-focused view to embrace a human-centered perspective can shape the future of technology to better serve human needs. The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities.

Technology is our new life partner. No longer confined to the sidelines, new interactive technologies like AI therapists, avatar friends, and robot assistants are ready to transform technology's role from basic tools of convenience to intimate elements of our social and emotional lives.

Throughout history, technological revolutions have been driven by the invention of machines. But today, the power of the technology transforming our world lies in an intangible and impenetrable cosmos of software: algorithmic code. So symbiotic has our relationship with this code become that we barely notice it anymore. We can't see it, are not even sure how to think about it, and yet we do almost nothing that doesn't depend on it. In a world increasingly governed by technologies that so few can comprehend, who—or what—controls the future?

Chat-GPT, humanoid robotics, and self-driving cars are just a few of the things that are changing our everyday lives. The rapid advancement of AI is eroding one by one all the cornerstones considered unique of human nature: language, consciousness, creativity, and moral responsibility. The book argues that the revolution we are facing is driven by Alan Turing's "vision". This vision rests on the idea that intelligence is not an intrinsic property of human beings, but is a way in which matter is functionally organized and an attribute we are naturally inclined to ascribe to certain entities.

In Harnessing Disruption, Sarah E. Kreps—a national security expert and military veteran—offers a fresh, clear-eyed framework for understanding the social and political dynamics that shape technological change. From nuclear weapons to AI, cryptocurrency, and social media, breakthrough...

After many years during which it languished in relative obscurity, in remote classrooms of computer science departments and in small prototype projects for tech companies, artificial intelligence (AI) is now a searingly hot topic across the media. Yet much of the public discussion is so feverish that an understanding of the basic scientific and engineering elements of the field is easily lost, often resulting in exaggerated claims, as well as dangerously neglected threats.