Every fortnight I curate some of the observations and insights that were shared on social media. I call these Friday’s Finds.
“The Edge … There is no honest way to explain it because the only people who really know where it is are the ones who have gone over.” —Hunter S. Thompson, Hell’s Angels, 1966, via @moehlert
@deehock: “Unrecorded thoughts are fragmentary, illusive and evanescent. When recorded they take on permanency, enabling us to give them context, discover error, improve content and refine expression.”
“The law of progress holds that everything now must be better than what was there before. Don’t you see if you want something better, and better, and better, you lose the good. The good is no longer even being measured.” —Hannah Arendt, via @cyetain
@white_owly: “I once completed a psych test for a job I didn’t want (long story). So I self-sabotaged and answered ‘yes’ to ‘are you happier when people fail than when they succeed?’ and ‘no’ to ‘do you consider yourself a team player?’. I then got invited to the final interview.”
“Susan Sontag was asked what she had learned from the Holocaust, and she said that 10% of any population is cruel, no matter what, and that 10% is merciful, no matter what, and that the remaining 80% could be moved in either direction” —Kurt Vonnegut, via @holdengraber
The Trailblazing Roboticist Tackling Diversity and Bias in Artificial Intelligence, via @JenniferSertl
Dr. Howard says roboticists and programmers need a data set that mirrors the US Census Report. Meaning if 22.8 percent of the population is below 18 and the data set doesn’t reflect that, it’s a problem. What happens, for example, if a self-driving car isn’t programmed to identify children?
Even in not-so-smart-machines, like the original crash test dummies, which were modeled for fifty years after a 6-foot, 180-pound man, unintended biases can be detrimental. The lack of crash test dummies modeled after woman led to women being under-protected during accidents. Now, asks Dr. Howard, if robots are programmed with bias, could these machines act in unpredictable ways?
“You design out of your own experience—it’s what makes us human,” Dr. Howard says. Therefore, it’s crucial to have diversity in robotics. “Diversity is all of the parameters that make your experience different,” she says. “And a lot of these systems are biased because the [engineering] teams are fairly homogeneous.”
Why Amazon Founder Jeff Bezos Failed Miserably at Applying Darwinian Competition to His Business, via @shauncoffey
“But Jeff Bezos and others who equate “Darwinism” with “ruthless competition” have it wrong. Charles Darwin, a British naturalist who was the father of evolution, never said that nature sanctioned a dog eat dog mentality. Instead he regarded sympathy as the most important and distinctive human adaptation.
While Darwin launched a brilliant idea, many aspects of evolution were worked out in future centuries. One of those is what nature teaches us about how groups work best. Contrary to Amazon endorsed practices, it is not through dog eat dog actions but cooperation.”
Go Ahead, Skip that Networking Event, via @moehlert
“When the guests arrived, the researchers told them to “Act normally. Talk to whomever you want to, while enjoying food and drinks.” The researchers then used tracking badges to monitor who talked to whom. As you might be able to guess by now, most of the executives tended to talk to people they already knew. Despite 95% of executives expressing a desire to meet new people, the average participant spent half of their time with the one-third of the people they already knew.
The few new meetings that did take place tended to be with others who were like themselves: the consultants talked to consultants, and the bankers talked to bankers. In terms of both new conversations and diverse connections, the most successful networker at the event turned out to be the bartender.”
How Identity Politics Is Harming the Sciences, via @sureallyno
“The extraordinary accomplishments of Western science were achieved without regard to the complexions of its creators. Now, however, funders, industry leaders, and academic administrators maintain that scientific progress will stall unless we pay close attention to identity and try to engineer proportional representation in schools and laboratories. The truth is exactly the opposite: lowering standards and diverting scientists’ energy into combating phantom sexism and racism is reckless in a highly competitive, ruthless, and unforgiving global marketplace. Driven by unapologetic meritocracy, China is catching up fast to the U.S. in science and technology. Identity politics in American science is a political self-indulgence that we cannot afford.”
