weapons of math destruction by cathy o'neil

Weapons of Math Destruction - Cathy O'Neil

Rating: 8/10

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Overview:

Have you ever considered what's behind artificial intelligence? Have you ever stopped to consider what is behind an algorithm? If you ever asked yourself these questions, Weapons of Math Destruction is the book for you. Cathy O'Neil goes through the abilities and the limits of the algorithms that accompany us throughout our days.

Takeaways: 

Humans in the data economy are outliers and throwbacks. The systems are built to run automatically as much as possible. That’s the efficient way; that’s where the profits are. Errors are inevitable, as in any statistical program, but the quickest way to reduce them is to fine-tune the algorithms running the machines

Google processed images of a trio of happy young African Americans and its automatic photo-tagging service labelled them as gorillas. The company apologized profusely, but in systems like Google’s, errors are inevitable.

Such mistakes are learning opportunities—as long as the system receives feedback on the error.

Social media and the News

“When your friends deliver the newspaper,” said Lada Adamic, a computational social scientist at Facebook, “interesting things happen.” Of course, it wasn’t really the friends delivering the newspaper, but Facebook itself. You might argue that newspapers have exerted similar power for eons. Editors pick the front-page news and decide how to characterize it.

But when the New York Times or CNN covers a story, everyone sees it. Their editorial decision is clear.

Facebook’s algorithms can affect how millions of people feel, and those people won’t know that it’s happening.

Big Data's Limits

Big Data processes codify the past. They do not invent the future. Doing that requires moral imagination, and that’s something only humans can provide.

Following the market crash of 2008, two financial engineers, Emanuel Derman and Paul Wilmott, drew up such an oath. It reads:
~ I will remember that I didn’t make the world, and it doesn’t satisfy my equations.
~ Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.
~ I will never sacrifice reality for elegance without explaining why I have done so.
~ Nor will I give the people who use my model false comfort about its accuracy. Instead, I will make explicit its assumptions and oversights.
~ I understand that my work may have enormous effects on society and the economy, many of them beyond my comprehension.