You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It's Making the World a Weirder Place (original 2019; edition 2019)

by Janelle Shane (Author)

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364	16	73,632	(4.27)	22

I've been teaching masters students about data mining and machine learning for a couple of years now, so the main points of 'You Look Like a Thing and I Love You' were familiar. I was really reading it for the entertaining examples, which were much more fun than my own. I liked the repeated cockroach factory motif and laughed several times at neural net-generated recipes, names, and general nonsense. Moreover, I learned much more about Markov chains and Generative Adversarial Networks than I knew before. Shane is a really engaging and fun writer, who makes complex concepts easy to understand. Most importantly, and I also tried to do this in my teaching, she demystifies narrow AI and deflates the hype around it. As neatly summarised at the end:

On the surface, AI will seem to understand more. It will be able to generate photorealistic scenes, maybe paint entire movie scenes with lush textures, maybe beat every computer game we can throw at it. But underneath that, it's all pattern matching. It only knows what it has seen and seen enough times to make sense of.

Thus the book spends many chapters explaining the mistakes that machine learning makes, which can be very different to the mistakes humans make. It often replicates and amplifys human biases as well, a very important point. I appreciated Shane's scepticism about fully automating cars, as driving involves responding to an incredibly wide range of different situations. It's hard to see how training data could ever cover them all adequately.

Personally, I think using the term Artificial Intelligence for machine learning is highly misleading. A so-called narrow AI may be able to optimise a very specific task, but it is not intelligent in any useful or meaningful sense. I grew up reading cyberpunk, in which AIs are godlike incomprehensible beings, not irritating bits of glitchy code that keep showing you ads for life insurance. AI has become an empty buzzword, as this book makes clear. Shane notes that many so-called AI startups never get machine learning to do the intended tasks, so humans end up doing it instead. There's even the phenomenon of bot farms, in which humans pretend to be automated algorithms on social media. We certainly live in a cyberpunk reality, just not quite the one that 80s and 90s sci-fi led me to expect. For one thing, I anticipated wearing sunglasses a lot more often.

Anyhow, the fact that I read this book in one sitting without intending to demonstrates that it's an accessible, amusing treatment of an important and interesting topic. If you enjoyed it and fancy a much more worrying book about the economic implications of machine learning, may I recommend [b:The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power|26195941|The Age of Surveillance Capitalism The Fight for a Human Future at the New Frontier of Power|Shoshana Zuboff|https://i.gr-assets.com/images/S/compressed.photo.goodreads.com/books/1521733914l/26195941._SY75_.jpg|46170685]. (

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annarchism | Aug 4, 2024 |

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On the surface, AI will seem to understand more. It will be able to generate photorealistic scenes, maybe paint entire movie scenes with lush textures, maybe beat every computer game we can throw at it. But underneath that, it's all pattern matching. It only knows what it has seen and seen enough times to make sense of.

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annarchism | Aug 4, 2024 |

The author is a scientist and blogger. The book takes a look at Artificial Intelligence (AI), how it works, and some of the humourous outcomes (the title is a unique AI pick-up line).

This was quite enjoyable. There is plenty of humour (from pick up lines to cat names to recipes to ice cream flavours). Also some very cute illustrations of AI (AI itself is illustrated as a box with eyes and stick arms). And of course, interesting information on how it works. A couple of things I will remember: it works better if the focus is quite narrow; it also has very little in the way of memory. Now, I should add that the book was published 5 years ago, so pre Chat-GPT and other more current versions of AI that have come out for widespread use, so I don’t know how much improvement there has been since the author wrote the book. (

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LibraryCin | Apr 29, 2024 |

This came out in 2019, after OpenAI released GPT-2 but well before ChatGPT's release. While I'd love to read an updated work by Shane (no amount of checking has made it poof into existence, alas), as far as I could tell this was still a really useful introduction to how artificial intelligence works and what its strengths and weakness are. Shane lays out what AI is and isn't, how it learns, the various ways it can run into trouble, the instances of disconnect between what humans ask AI to do and what it actually does, and more.

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.) (

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Familiar_Diversions | Apr 1, 2024 |

I cannot recommend "You Look Like a Thing and I Love You" highly enough. If you've ever had the slightest interest in AI, this is your cup of tea ;-) Very informative, very accessible, easy to read, and very very very funny. It is also a great book for those who are sure that AI will take their jobs/take over the world tomorrow. (The answer is: not really.) I also feel like reading more about AI now... (

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Alexandra_book_life | Dec 15, 2023 |

I loved this so much. I know that's what all my reviews say but this one is *chef kiss* (

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cleverlettuce | Nov 6, 2023 |

I've enjoyed the author's blog, AI Weirdness, for quite some time, so I was looking forward to reading this. I was not disappointed - not only is this one of the clearest explanations of how artificial intelligence works I've ever come across, it's also often laugh-out-loud funny. I flew through it in record time, enjoying every moment. If you are at all curious about AI and enjoy bizarre non-sequiturs, you will enjoy this. Highly recommended. (

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melydia | Jan 7, 2023 |

I would have loved to have this on my kindle, because there was plenty of highlight-worthy material: lots of interesting facts to remember and lots of hilarious AI-generated lists.
I’m not sure why I developed such a fascination with AI, but it’s probably Hannah Fry’s fault. Her delightful Hello, World certainly encouraged it. People who enjoyed that book would enjoy this one too.
Janelle Shane based it on her blog aiweirdness.com, and sections of it made me laugh so hard a coworker threatened to ban it from the break room.
It’s an informative book too, and I learned a lot about how neural networks process datasets to generate their own original—and often super weird—output. The title of the book is from a list of pick-up lines an AI generated after the author trained it on a large dataset of actual pick-up lines.
It was surprising to see what AI came up with in the early stages of learning, such as the lines of k’s that it thought were knock-knock jokes in a different training scenario.
The author’s explanations got a little mathy at times, but for the most part, I understood what she was saying, and I understood more than I ever have the limits to what AI can do. As the author said in her last chapter, “Will it get smart enough to understand us and our world as another human does—or even to surpass us? Probably not in our lifetimes. For the foreseeable future, the danger will not be that AI is too smart but that it’s not smart enough...it’s all pattern matching. It only knows what it has seen and seen enough times to make sense of.”

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Harks | Dec 17, 2022 |

A hilarious look at AI's current abilities and myriad limitations. The book made me laugh out loud several times, so I highly recommend it, but will caution that the author repeats herself many times in the book. All in all a solid read. (

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lemontwist | Aug 24, 2022 |

nonfiction; artificial intelligence--humor, problems, and humorous problems.

when an AI tries to write a knock knock joke from scratch:

Ireland
Ireland who?
Ireland you money, butt.

I could not contain my laughter, folks. But this tidy little book holds more than lots of AI-generated 'butt' jokes, it also provides a basic primer on the types of AI that are out there, what they are capable of (probably) and what they are not likely to be able to do within our lifetimes. It also, helpfully, contains an index so if you want to go straight to the list of AI-generated My Little Pony names (including Derdy Star, Raspberry Turd, and Star Sh*tter), you can.

Strongly recommended for people who enjoy nonfiction, science fiction, and techy science. (

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reader1009 | Dec 15, 2021 |

Four stars plus a bonus star for relevancy. I mean they need to teach this in schools. AI is like the evil genii/devil/monkeyspaw that give you exactly what you ask for but never what you want.

So many fascinating and disturbing examples of the types of AI's that are already being used around the world. I mean this is by no means a book of doom and gloom but most of my personal take-away focused on AI's abilities to amplify bias and its almost hysterically evil penchant for taking short-cuts.

This book delivers soild, useful (more like essential) info on the real state of AI and claims about AI and does so in a straight forward easy to follow manner with some humour to make the medicine go down. HIGHLY recommended. (

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wreade1872 | Nov 28, 2021 |

If you’ve ever wondered about how artificial intelligence works, this is the book you want to read. It’s a funny, accessible introduction to the field, explaining the different types of artificial intelligence and how they work—or how they don’t. Artificial intelligence does exactly what you tell it to and has no understanding of context or bias. It will amplify bias in existing datasets and reveal surprising connections between other bits of data, so it requires care and maintenance, and a clear understanding of its limitations, in order to be used effectively.

I really, really enjoyed this book. The cartoons were great—I want a T-shirt with the little AI on it!—and the examples of AI output had me snorting out loud frequently. It was in fact Shane’s Twitter feed, with a thread of AI-generated 1970s recipes, that drew me to this book, so if you like her Twitter or her blog (AI Weirdness), you’ll like this book. It explains concepts clearly, uses bolding to highlight key terms, and employs visible endnotes so you can follow the sources.

Recommended for anyone who uses anything dependent on algorithms—and this includes cat-ear filters on Instagram. (

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rabbitprincess | Oct 9, 2021 |

I didn't actually finish this book, but thoroughly enjoyed anyway. I don't usually read nonfiction for pleasure, but Janelle's AI Weirdness blog has occasionally reduced me to actual tears of laughter (in particular AI generated cat names 1 & 2, and in rem jurisdiction cases), so I bought her book. It's really good! It's a funny and continuously engaging introduction to AI and machine-learning algorithms which succeeds at not talking down to (and, in fact, entertaining) the reader while conveying good knowledge! I trailed off because... I do that with non-fiction, but would highly recommend! (

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Foxen | Jan 26, 2021 |

The "artificial intelligence" referred to in the subtitle is, specifically, machine learning. That is, computer algorithms that are trained on specific sets of data and learn to do things with that data through trial and error, for instance, identifying images or generating intelligible (or maybe semi-intelligible) text. Janelle Shane covers how these programs work, what they're used for, what they're good at, what they're bad at, and the various ways -- some hilarious, some disturbing, some just plain weird -- in which they can go wrong.

It's all extremely readable, even fun. Shane, I think, gives readers a very good sense of how this stuff works without ever getting dry or technical, and keeps a charming sense of humor throughout. The little cartoon illustrations she uses are extremely cute, and sometimes genuinely illuminating. I found it fascinating, thought-provoking, entertaining, and more than a little bit worrying. Definitely recommended for anyone at all curious about this strange new technology and where it's taking us. (

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bragan | Dec 20, 2020 |

I sort of thought by the title it would be about anthropomorphism, but the subtitle is “How Artificial Intelligence Works and Why It’s Making the World a Weirder Place.” Along with cute illustrations, the book explains pretty much that, at a high level, along with what AI is and isn’t good for. AI is particularly not good at resisting targeted attacks; stickers or changes in pixels can change “gun” to “toaster” in AI vision, and—attention, fic writers—“a low-security fingerprint reader can be fooled 77 percent of the time with a single master fingerprint.” Like people, AI is lazy, so when you try to train it to recognize skin diseases, it will instead learn the easier trick of recognizing the rulers that are often in the picture with actual cancers, which is clever from its perspective but not from ours. That’s also how it learns to replicate human biases (in favor of men, against people who went to HBCUs, etc.). If you use the same camera to take pictures of the training set of “right” answers, then it may learn to use the camera metadata instead, although my favorite examples were the AIs that learned to exploit features of the training system, e.g. anomalies in the modeling of physics that allowed them to accumulate infinite force or crash the system when they were about to lose or even hack into the answer key and award themselves right answers. AI, that is, is very much like Captain Kirk and the Kobayashi Maru. Also for authors: there are certain training datasets that lots of systems use. If you managed to submit enough samples to those databases to corrupt them—maybe 5%--you could make your adversarial attacks on the system succeed. This vulnerability also suggests big problems of overfitting—the training set matters too much and the algorithm too little. Also: you could hack voice-to-AI systems so that a human would hear one thing and the AI system would hear something very different. Fic possibilities, worrying realities. One last tidbit to ponder: we so much don’t know how algorithms learn that when people are assigned to circle the part of a picture that helps them figure out what’s in the picture, algorithmic performance goes down, so either people are wrong about how they recognize dogs (etc.) or something even stranger is going on. On the plus side, made me kind of want to write Leverage fic? (

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rivkat | Sep 1, 2020 |

This is a layman’s introduction to how AI works and what it can and cannot do. It’s a really fun read - it’s full of really silly examples of AI’s messing up in hilarious ways (such as an AI that was told to move from point A to point B, and it decided the best way to get there was to make itself as tall as the distance between the two points and then fall over).

The big takeaways for me were (1) that even AI researchers don’t always understand how AI works, and (2) that AI is nowhere near as magical and capable as AI companies would have you think.

AI is already a big part of our daily lives, and is going to continue to be more and more important. It's also important that we understand what AI is and what it can and cannot do - right now a lot of tech companies are making a lot of money by selling us an AI-driven future where everything is easy and computers can solve all of our problems, but this book makes it very (hilariously) clear that an AI-driven future is going to be weird and buggy, and that AI has the potential to be very problematic if not used correctly. (

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Gwendydd | Aug 22, 2020 |

A very theoretical introduction and digest of different types of AI; a comprehensive (if sometimes convoluted and repetitive) overview of the technology; its promise and limitations. Uses hypotheticals and analogies to explain AI in theory. Explains why AI isn’t practically possible let alone effective without human engagement and how, often, the technology depends on massive quantities, and, precise qualities, of (sometimes scarce) underlying data.

One of the points the book makes is that AI is not trying to find the right solution but what a human would have done. The book's comparison of AI to worms' intelligence is flawed because according to recent revelations worms are intelligent enough to have free will, unlike AI. AI seems eons away, in fact, of exhibiting any such facility.

The tone is very approachable, and emphasizes that AI is more artificial than intelligence. Don’t expect any practical experience however, this is not an AI tutorial or workbook, not even an introductory one. If you are interested in AI but don’t know how or where to begin, this may be a good (if slow) start, but if you are looking for a deep dive, this is probably is not the book for you.

AAAO | Jun 20, 2020 |

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