Ai In The Wild

Examining the potential benefits and risks of using artificial intelligence to advance global sustainability. Drones with night vision are tracking elephant and rhino poachers in African wildlife parks and sanctuaries; smart submersibles are saving coral from carnivorous starfish on Australia's Great Barrier Reef; recycled cell phones alert Brazilian forest rangers to the sound of illegal logging. The tools of artificial intelligence are being increasingly deployed in the battle for global sustainability. And yet, warns Peter Dauvergne, we should be cautious in declaring AI the planet's savior. In AI in the Wild, Dauvergne avoids the AI industry-powered hype and offers a critical view, exploring both the potential benefits and risks of using artificial intelligence to advance global sustainability.

As heard on NPR's "Science Friday," discover the book recommended by Malcolm Gladwell, Susan Cain, Daniel Pink, and Adam Grant: an "accessible, informative, and hilarious" introduction to the weird and wonderful world of artificial intelligence (Ryan North). "You look like a thing and I love you" is one of the best pickup lines ever . . . according to an artificial intelligence trained by scientist Janelle Shane, creator of the popular blog AI Weirdness. She creates silly AIs that learn how to name paint colors, create the best recipes, and even flirt (badly) with humans—all to understand the technology that governs so much of our daily lives. We rely on AI every day for recommendations, for translations, and to put cat ears on our selfie videos. We also trust AI with matters of life and death, on the road and in our hospitals. But how smart is AI really... and how does it solve problems, understand humans, and even drive self-driving cars? Shane delivers the answers to every AI question you've ever asked, and some you definitely haven't. Like, how can a computer design the perfect sandwich? What does robot-generated Harry Potter fan-fiction look like? And is the world's best Halloween costume really "Vampire Hog Bride"? In this smart, often hilarious introduction to the most interesting science of our time, Shane shows how these programs learn, fail, and adapt—and how they reflect the best and worst of humanity. You Look Like a Thing and I Love You is the perfect book for anyone curious about what the robots in our lives are thinking. "I can't think of a better way to learn about artificial intelligence, and I've never had so much fun along the way." —Adam Grant, New York Times bestselling author of Originals

Explains how artificial intelligence methods can be used to aid conservation of wildlife, forests, coral reefs, rivers, and other natural resources.

Rules for building formal models that use fast-and-frugal heuristics, extending the psychological study of classification to the real world of uncertainty. This book focuses on classification--allocating objects into categories--"in the wild," in real-world situations and far from the certainty of the lab. In the wild, unlike in typical psychological experiments, the future is not knowable and uncertainty cannot be meaningfully reduced to probability. Connecting the science of heuristics with machine learning, the book shows how to create formal models using classification rules that are simple, fast, and transparent and that can be as accurate as mathematically sophisticated algorithms developed for machine learning.

A guide to understanding the inner workings and outer limits of technology and why we should never assume that computers always get it right. In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally—hiring, driving, paying bills, even choosing romantic partners—that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology. With this book, she offers a guide to understanding the inner workings and outer limits of technology—and issues a warning that we should never assume that computers always get things right. Making a case against technochauvinism—the belief that technology is always the solution—Broussard argues that it's just not true that social problems would inevitably retreat before a digitally enabled Utopia. To prove her point, she undertakes a series of adventures in computer programming. She goes for an alarming ride in a driverless car, concluding “the cyborg future is not coming any time soon”; uses artificial intelligence to investigate why students can't pass standardized tests; deploys machine learning to predict which passengers survived the Titanic disaster; and attempts to repair the U.S. campaign finance system by building AI software. If we understand the limits of what we can do with technology, Broussard tells us, we can make better choices about what we should do with it to make the world better for everyone.

LODESTAR AWARD WINNER FOR BEST YOUNG ADULT BOOK From Hugo and Locus Award-winning author Naomi Kritzer, Catfishing on CatNet is a thought-provoking near future YA thriller that could not be more timely as it explores issues of online privacy, artificial intelligence, and the power and perils of social networks. A New York Times Book Review Editors’ Choice/Staff Pick A Kirkus Reviews Best Book A Junior Library Guild Selection An Edgar Award Winner for Best Young Adult Novel A Minnesota Book Award Winner for Best Young Adult Novel An Andre Norton Nebula Award Finalist An ITW Thriller Award for Best YA Novel Nominee A Lodestar Award Winner for Best Young Adult Book “A pure delight...that’s as tender and funny as it is gripping and fast-paced. This book is perfect. From the believable teenage voices to the shockingly effective thriller plot, it swings effortlessly from charming humor to visceral terror, grounding it all in beautiful friendships, budding romance, and radical acceptance.” —The New York Times Because her mom is always on the move, Steph hasn’t lived anyplace longer than six months. Her only constant is an online community called CatNet—a social media site where users upload cat pictures—a place she knows she is welcome. What Steph doesn’t know is that the admin of the site, CheshireCat, is a sentient A.I. When a threat from Steph’s past catches up to her and ChesireCat’s existence is discovered by outsiders, it’s up to Steph and her friends, both online and IRL, to save her. “Alongside the uplifting message about inclusivity, diversity, and found family—characters of various ethnicities identify as gay, bisexual, nonbinary, asexual, and still exploring—Kritzer’s take on a benevolent AI is both whimsical and poignant. An entertaining, heart-filled exploration of today’s online existence and privacy concerns.” —Publishers Weekly, starred review At the Publisher's request, this title is being sold without Digital Rights Management Software (DRM) applied.

From a New York Times bestselling author and Caldecott-honor winning artist comes an exuberant illustrated story about playing dress up, having fun, and feeling free. The boy loves to be naked. He romps around his house naked and wild and free. Until he romps into his parents' closet and is inspired to get dressed. First he tries on his dad's clothes, but they don't fit well. Then he tries on his mom's clothes, and wow! The boy looks great. He looks through his mom's jewelry and makeup and tries that on, too. When he's discovered by his mother and father, the whole family (including the dog!) get in on the fun, and they all get dressed together. This charming and humorous story was inspired by bestselling and award-winning author Peter Brown's own childhood, and highlights nontraditional gender roles and self-expression.

An argument that—despite dramatic advances in the field—artificial intelligence is nowhere near developing systems that are genuinely intelligent. In this provocative book, Brian Cantwell Smith argues that artificial intelligence is nowhere near developing systems that are genuinely intelligent. Second wave AI, machine learning, even visions of third-wave AI: none will lead to human-level intelligence and judgment, which have been honed over millennia. Recent advances in AI may be of epochal significance, but human intelligence is of a different order than even the most powerful calculative ability enabled by new computational capacities. Smith calls this AI ability “reckoning,” and argues that it does not lead to full human judgment—dispassionate, deliberative thought grounded in ethical commitment and responsible action. Taking judgment as the ultimate goal of intelligence, Smith examines the history of AI from its first-wave origins (“good old-fashioned AI,” or GOFAI) to such celebrated second-wave approaches as machine learning, paying particular attention to recent advances that have led to excitement, anxiety, and debate. He considers each AI technology's underlying assumptions, the conceptions of intelligence targeted at each stage, and the successes achieved so far. Smith unpacks the notion of intelligence itself—what sort humans have, and what sort AI aims at. Smith worries that, impressed by AI's reckoning prowess, we will shift our expectations of human intelligence. What we should do, he argues, is learn to use AI for the reckoning tasks at which it excels while we strengthen our commitment to judgment, ethics, and the world.