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I hope “plush giraffe perturbation” becomes a standard test and every robotics lab now has to go get a plush giraffe
If you ask Visual Chatbot, there are always at least a couple of giraffes.

That's because it learned from questions that humans asked & answered about images, and apparently people rarely asked "how many giraffes are there" when the answer was zero. demo-visualdialog.cloudcv.org image: robot arm holding a rubiks cube<br /> caption: a toy car with a car on top of it<br /> me: how many giraffes are there<br /> bot: 2
Looks like the @OpenAI model handled the giraffe so well because it trained in a variety of universes.

No simulation could be perfect, so their flaws varied to prevent the AI from learning to hack the matrix. As it inevitably would do. openai.com/blog/solving-r…
@OpenAI "Universe where there is a pesky giraffe" turned out to be not that much more difficult than "universe where friction is weird" or "universe where everything is rubber".

The AI also adapted to "universe where everything is shoddy"
@OpenAI In my book I talk a lot about AI's tendency to exploit the flaws in its simulations.

I am pleased they let me title a chapter "Hacking the Matrix, or AI Finds a Way"
janelleshane.com/book-you-look-…
@OpenAI summary of aiweirdness.com

also summary of my book youlooklikeathing.com

basically i am 100% this plush giraffe robot hand holding a rubik's cube, labeled A.I.<br /> giraffe toy getting in the way, labeled caption on photo reads "plush giraffe perturbation"" src="/images/1px.png" data-src="https://pbs.twimg.com/media/EHAoiaAUEAA6KP9.jpg">
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Janelle Shane
@JanelleCShane
Things neural networks are saying about my book!

Generated by a neural net @OpenAI trained on Amazon reviews. Text color is activity level of a neuron they discovered it was using to keep track of the review's sentiment.

(real facts about the book here: janelleshane.com/book-you-look-…) <br /> You Look Like A Thing And I Love You will stay in your cabinet, shelves, and cereal box!<br /> <br /> You Look Like A Thing And I Love You is a book that everyone should add to their collection. Fits beautifully but the pink tends to pitch the iron walls. Would like to be able to bake multiple and have milk sufficiently eaten<br /> <br /> You Look Like A Thing And I Love You is a book that literally took me by surprise. It is funny, intell
@OpenAI Real people are also saying nice things about my book!

So many nice things that my publisher @voraciousbooks added a book jacket to make room for it all!

Which also means there's room for Secret Giraffes inside the cover book jacket of You Look Like a Thing and I Love You
@OpenAI @voraciousbooks “Recommended for anyone who wants to better understand the strengths and limitations of artificial intelligence, but also for anyone who likes watching computers fail hilariously.”

— @GretchenAMcC , New York Times bestselling author of Because Internet
janelleshane.com/book-you-look-…
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Janelle Shane
@JanelleCShane
My book has undergone vigorous performance testing
#PlushGiraffePerturbation
i am up on the latest ai trends
Plush giraffe perturbation test, alternate form
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Janelle Shane
@JanelleCShane
Very effective interactive demo of how human bias in training data affects any algorithm that tries to use it.

Especially in the US, predicting who will commit a crime is not the same as predicting who will be arrested. And here all the AI has is arrest data.
I talk about this example in my book too. Neatly illustrates how if a machine learning algorithm tackles a problem like parole decisions without knowing about the bias in its data (and how can it? it doesn't know what's going on), it'll treat the bias as valid.
One solution to building fairer algorithms is to change the training data to reflect the world as it ought to be - in other words, to debias the data.

Here, one could adjust assuming a fair justice system would have produced equal arrest rates for Black vs white defendants.
Read 7 tweets

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