02949cam a2200313 i 4500 592208821 TxAuBib 20220908120000.0 210915s2022||||||||||||||||||||||||eng|u 2021035121 9780262046954 HRD 29.95 0262046954 HRD 29.95 (OCoLC)1268543396 TxAuBib rda Gigerenzer, Gerd, author. How to stay smart in a smart world [BOOK] : why human intelligence still beats algorithms / Gerd Gigerenzer. London, England : The MIT Press, [2022] xxii, 297 pages : illustrations ; 24 cm. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references (pages 229-284) and index. Is true love just a click away? -- What AI is best at : the stable-world principle -- Machines influence how we think of intelligence -- Are self-driving cars just down the road? -- Common sense AI -- One data point can beat big data -- Transparency -- Sleepwalking into surveillance -- The psychology of getting users hooked -- Safety and self-control -- Fact or fake? Doomsday prophets of technology predict that robots will take over the world, leaving humans behind in the dust. Tech industry boosters think replacing people with software might make the world a better place—while tech industry critics warn darkly about surveillance capitalism. Despite their differing views of the future, they all agree: machines will soon do everything better than humans. In How to Stay Smart in a Smart World, Gerd Gigerenzer shows why that’s not true, and tells us how we can stay in charge in a world populated by algorithms. Machines powered by artificial intelligence are good at some things (playing chess), but not others (life-and-death decisions, or anything involving uncertainty). Gigerenzer explains why algorithms often fail at finding us romantic partners (love is not chess), why self-driving cars fall prey to the Russian Tank Fallacy, and how judges and police rely increasingly on nontransparent “black box” algorithms to predict whether a criminal defendant will reoffend or show up in court. He invokes Black Mirror, considers the privacy paradox (people want privacy, but give their data away), and explains that social media get us hooked by programming intermittent reinforcement in the form of the “like” button. We shouldn’t trust smart technology unconditionally, Gigerenzer tells us, but we shouldn’t fear it unthinkingly, either. Provided by publisher. 20220908. Artificial intelligence Social aspects. Expert systems (Computer science) Safety measures. Expert systems (Computer science) Risk assessment.