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In a brief-but-amazing McKinsey interview with Chamath Palihapitiya, the venture capitalist and former Facebook exec outlines three technologies that most excite him: sensor networks (such as asthma inhalers that can help avoid massive attacks and ER visits), autonomous vehicles (“the one thing that I’ve seen that could fundamentally have the high-order-bit2 effect on GDP. You can completely reenvision cities, transportation models, and commerce with all these autonomous vehicles, with the ability to ship goods”), and big data (genetics will shift from biologists to computer scientists). That last point in particular reminds me of Clayton Christensen’s forecasts of precision medicine.
Two other interesting bits. One, Palihapitiya sees understanding technology as akin to learning a language, and schools to need to facilitate this understanding:
And probably what you find is, if you actually had knowledge of a technical language, you would probably “speak” that language more in your daily life than the actual verbal language. I think coding is the blue-collar job of the 21st century. There’s nothing wrong with that. We are in a world right now where these abstractions are getting so good. What it meant to code 10 or 15 years ago when I was learning was actually a very difficult premise, in my opinion.
These are extremely low-level languages. You’re dealing with hardware in a way that you don’t have to, today. We’re so well abstracted that, in four or five years, my children will code by drawing things on a page and it will translate it into code. So what it means “to code” is becoming a simpler definition, which means by extension that more people should be able to do it.
Palihapitiya also gives a pretty potent description of the nexus of technology, and education, and inequality:
There’s an arc of technical proficiency that’s lacking in most companies. There’s an arc of rewards and recognition that tends to lag and tends to not feed the top 1 percent or 5 percent but tends to manage to the middle. Those are extremely inherent biases that have existed in companies for decades.
But when you see the few companies that get it right, what they’ve done is they’ve disrupted those three specific things. They’ll say, “OK, you know what? It’s all about the top 1 percent. Everyone else, tough luck. We celebrate the best, and everybody else can tag along. We cull the bottom, and we’re super aggressive. We have an extremely deep quantitative understanding of our business.
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