
The Alignment Problem reveals how AI systems can drift from human values, earning praise from Microsoft CEO Satya Nadella and NYT recognition as the #1 AI book. What happens when machines misunderstand our intentions? Brian Christian offers a crucial roadmap for our algorithmic future.
Sinta o livro através da voz do autor
Transforme conhecimento em insights envolventes e ricos em exemplos
Capture ideias-chave em um instante para aprendizado rápido
Aproveite o livro de uma forma divertida e envolvente
What happens when you teach a computer to read the entire internet? In 2013, Google unveiled word2vec, a system that could perform mathematical magic with language-add "China" to "river" and get "Yangtze," or subtract "France" from "Paris" and add "Italy" to get "Rome." It seemed like pure intelligence distilled into numbers. But when researchers tried "doctor minus man plus woman," they got "nurse." Try "computer programmer minus man plus woman" and you'd get "homemaker." The system hadn't just learned language-it had absorbed every gender bias embedded in millions of human-written texts. This wasn't a bug. It was a mirror. The problem runs deeper than words. In 2015, a Black web developer named Jacky Alcine opened Google Photos to find his pictures automatically labeled "gorillas." Google's solution? Simply remove the gorilla category entirely-even actual gorillas couldn't be tagged years later. Meanwhile, employment screening tools were discovered ranking the name "Jared" as a top qualification. Photography itself carries this legacy-for decades, Kodak calibrated film using "Shirley cards" featuring White models, making cameras literally incapable of photographing Black skin properly. The motivation to fix this came not from civil rights concerns but from furniture makers complaining about poor wood grain representation. When Joy Buolamwini tested commercial facial recognition systems, she found a 0.3% error rate for light-skinned males but 34.7% for dark-skinned females. The machines weren't creating bias-they were perfectly, ruthlessly reflecting ours.
Divida as ideias-chave de The Alignment Problem em pontos fáceis de entender para compreender como equipes inovadoras criam, colaboram e crescem.
Destile The Alignment Problem em dicas de memória rápidas que destacam os princípios-chave de franqueza, trabalho em equipe e resiliência criativa.

Experimente The Alignment Problem através de narrativas vívidas que transformam lições de inovação em momentos que você lembrará e aplicará.
Pergunte qualquer coisa, escolha a voz e co-crie insights que realmente ressoem com você.

Criado por ex-alunos da Universidade de Columbia em San Francisco
"Instead of endless scrolling, I just hit play on BeFreed. It saves me so much time."
"I never knew where to start with nonfiction—BeFreed’s book lists turned into podcasts gave me a clear path."
"Perfect balance between learning and entertainment. Finished ‘Thinking, Fast and Slow’ on my commute this week."
"Crazy how much I learned while walking the dog. BeFreed = small habits → big gains."
"Reading used to feel like a chore. Now it’s just part of my lifestyle."
"Feels effortless compared to reading. I’ve finished 6 books this month already."
"BeFreed turned my guilty doomscrolling into something that feels productive and inspiring."
"BeFreed turned my commute into learning time. 20-min podcasts are perfect for finishing books I never had time for."
"BeFreed replaced my podcast queue. Imagine Spotify for books — that’s it. 🙌"
"It is great for me to learn something from the book without reading it."
"The themed book list podcasts help me connect ideas across authors—like a guided audio journey."
"Makes me feel smarter every time before going to work"
Criado por ex-alunos da Universidade de Columbia em San Francisco

Obtenha o resumo de The Alignment Problem como PDF ou EPUB gratuito. Imprima ou leia offline a qualquer momento.