Sull'Autore
Janelle Shane holds a PhD in engineering and a MS in physics. At AI Weirdness, she writes about artificial intelligence and the amusing and sometimes unsettling ways that algorithms get human things wrong. She has been featured on the main TED stage; in the New York limes. The Atlantic, Wired, mostra altro Popular Science, and more; and on NPR's All Things Considered, Science Friday, and Marketplace. She was named one of Fast Company's 100 Most Creative People in Business and an Adweek Young Influential. mostra meno
Opere di Janelle Shane
Etichette
Informazioni generali
- Data di nascita
- c. 1985
- Sesso
- female
- Nazionalità
- USA
- Istruzione
- University of California, San Diego (graduate student|2008)
Michigan State University (electrical engineering|2007)
St Andrew's University (masters|physics) - Attività lavorative
- research scientist (artificial intelligence)
- Organizzazioni
- Boulder Nonlinear Systems
- Breve biografia
- Janelle Shane has a PhD in electrical engineering and a master's in physics. At aiweirdness.com, she writes about artificial intelligence and the hilarious and sometimes unsettling ways that algorithms get human things wrong. She was named one of Fast Company's 100 Most Creative People in Business and is a 2019 TED Talks speaker. Her work has appeared in the New York Times, Slate, The Atlantic, Popular Science, and more. She is almost certainly not a robot.
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Statistiche
- Opere
- 2
- Utenti
- 328
- Popolarità
- #72,311
- Voto
- 4.3
- Recensioni
- 14
- ISBN
- 12
I first became aware of this work after stumbling on some of Shane's hilarious machine learning blog posts on Twitter (way back when Twitter was Twitter). In fact, the title of this book comes from one such post on AI-generated pickup lines. Still, it sat on my TBR pile for years until ChatGPT came out and became a hot enough topic in academia to be mentioned several times during a Q&A session with a library job candidate.
While I appreciated Shane's humor and adorable little AI illustrations throughout, this also contained plenty of useful information written in a way that was relatively easy for someone without much of a technical background to understand. I'd have liked to see slightly more technical information than Shane provided (for example, I feel like I got a good general understanding of how AI training works, but I still can't picture what actually doing it looks like), but overall Shane's explanations were really clear and made good use of examples. One real-world example that stuck with me that illustrated AI's reliance on its training data and difficulties when asked to do a broader task than it was trained for (because AI does better with narrower tasks) was a self-driving car that had only been trained for highway driving. Its human driver had it take over while it was still in the city and it ended up hitting the side of a semi - it had only ever been trained to recognize semis from the back, so when it saw one from the side it interpreted it as best it could, decided it was an overhead sign, and didn't slow down for it.
I've already recommended this book to several of my fellow librarians as an accessible way to learn about AI and maybe get some ideas for how to talk about it to faculty and students.
(Original review posted on A Library Girl's Familiar Diversions.)… (altro)