How to Stay Smart in a Smart World

Why Human Intelligence Still Beats Algorithms

De: Gerd Gigerenzer

Narrado por: Joel Richards

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. How to Stay Smart in a Smart World 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). Gerd 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.

©2022 Gerd Gigerenzer (P)2022 Tantor

thinking critically in the modern age

Gigerenzer lucidly explains the weaknesses in the promise of AGI as well as provides a manual for educating oneself in the intracacies of determining truth from false interpretations of facts. If this were adapted for younger users it could serve as a useful series of critical thinking lessons or a course for today's youth.

I hoped for more…

Very few recommendations on how to “stay smart” (a couple nice ones in the final pages..)

I enjoyed the first third or so but it felt like the book went a little off the rails in the middle; giving very light coverage to some AI and probability topics that are better covered in other books.

Probably still worth most people’s time - if for nothing else than the final chapters coverage of how to be a more critical reader.

I Paid for This Nonsense

The author believes that men and women have exactly the same interests and priorities, so any discrepancy in their representation at the highest levels of the technology industry can ONLY be the result of systematic discrimination. Not even a nod towards any other cause for the disparity.

If a writer is so blinkered, why take on trust anything he or she says about anything?