🔮 Populist surges; getting AI to understand humans and humans to understand AI; post-capitalism; bitcoin & fat protocols; billionaires, Gopher & sharks++ #74
|Aug 14, 2016||Public post|
What drives populism? Why did we become post-fact? How can you tap into Silicon Valley’s culture of innovation? Is social media a threat to democracy? How can we get AI to understand humans? Where next for capitalism? Why are billionaires hoarding cash? Has your sex toy been hacked? How did that shark live so long? So many questions to stimulate so many conversations! Enjoy ;)
SUPPORT EV: Donate via PayPal. (You choose the level. Thanks to supporters.)
Dept of the near future
😠 Cities are the origins of popular surges everywhere, argues Philip Auerswald. “Cities are humanity’s greatest invention. They are platforms on which we share, create, exchange. They benefit from density. Returns accrue disproportionately to owners of land. This causes inequality and invites a backlash.” MUST READ (Separately, McKinsey on India’s coming ascent highlights how massive urbanisation will be one of the transforming vectors.)
🤔 Why we are post-fact. Peter Pomeranstev, writes in Granta: “this equaling out of truth and falsehood is both informed by and takes advantage of an all-permeating late post-modernism and relativism” GREAT READ
💰 USV’s Joel Monegro on Fat Protocols: “[In] the blockchain application stack[, v]alue concentrates at the shared protocol layer and only a fraction of that value is distributed along at the applications layer.” ENLIGHTENING but also see Preston Byrne’s detailed critique of altcoin crowdsales.
⏲ Tapping into Silicon Valley’s culture of innovation. VERY HANDY guide for large corporates.
⚖ The biggest threat to democracy is your social media feed argues Vyacheslav Polonski. “Technology can also be a platform for conflict and malicious agitation… that are dysfunctional for a healthy democratic discourse, while our current governance systems are susceptible to emotional bursts and populist movements that unfold on the internet.” GOOD READ (See also this excoriating review of Twitter’s ham-fisted history of dealing with abuse.)
Dept of capitalism (venture and other types)
🛍 Robots are helping people to buy more stuff: “Automation allows companies to reduce product costs, and, ultimately, lower prices, which means more people can afford to buy what’s on sale.”
The decline of the unions and the rise of Trump: “A labo[u]r union might inculcate civic virtues in its members, pushing them to think and vote in a more enlightened way.” Also worth considering as we move towards two-sided markets, what protects participants on each side of the market. (See also, Deliveroo’s new pay scheme is a ‘return to Victorian Britain’.)
See also a co-operative ride-hailing business which passes all revenues back to the co-op (and ultimately drivers) has launched in Michigan.
💥 Benedict Evans analyses venture capital returns: “In praise of failure.” EXCELLENT must read, even if you aren’t in the industry.
Dept of referrals
😃 Exponential View grows by your referrals! Thank you.
Dept of machine learning (text & language special)
Great feature from Will Knight on AI’s language problem. “If AI is to serve as a ubiquitous tool that people use to augment their own intelligence and trust to take over tasks in a seamless collaboration, language will be key.”
💡 Text analysis of Trump’s tweets confirms he writes only the (angrier) Android half. EXCELLENT ANALYSIS.
Cathy O'Neil: Trump in an object lesson in machine learning. “Trump’s algorithm is to say semi-random things until his crowd roars its approval, then he iteratively modifies those statements, seeking more and more approval, until he maxes out and tries a new tack.” Makes a great point about the risks of our increasingly algorithmic future - systems designers need to think about what their systems end up optimising.
Vector-space maths formally uncovers gender bias in text. Super application of word2vec helps us identify hidden (often uncomfortable) relationships between words as use in ordinary written language. The sub-headline of this article is amusing: “As neural networks tease apart the structure of language, they are finding a hidden gender bias that nobody knew was there”, as one Twitter user wrote the sub-head should read “As neural networks tease apart the structure of language, they are finding a hidden gender bias that EVERYONE IN THE HUMANITIES KNEW WAS THERE.” (My emphasis.)
Huge reading list of papers supporting “Critical Algorithm Studies”. Haven’t had a chance to do more than skim the list, but looks fascinating.
Elsewhere: Intel acquires Nervana Systems which makes chips optimised for deep learning. More evidence that we are in the deployment phase of artificial intelligence. (Congrats to the several EV readers involved as investors, advisers or employees of Nervana Systems.)
😞 Elsewhere: Predicting depression by looking at Instagram feeds.
Short morsels to appear smart at dinner parties
Lovely history of Gopher, a text-based Internet-based information system which predated the Worldwide web. (I have a soft spot for Gopher, as we used it for putting The Oxford Student, my student paper, onto the Internet back in 1992.)
How Uber and AirBNB got their first customers. (HBS Case Study - useful read.)
💸 The world’s billionaires, with a total net worth of $7.7 trillion, are holding 22% (or $.17trn) in cash.
🔥 We’ve smashed through the 490ppm level for CO2 making the two degree rise increasingly inevitable.
🏊🏽 This is why there are so many ties in Olympic swimming. (Engineering nerdery awesome.)
🐳 Meet the 400-year old sharks.
Finding alternatives to CRISPR
🚿 Cracking the bandwidth bottleneck. Internet is running out of tubes.
It is great to be back from the summer rest. I hope you have had (or will have) a chance to recharge too. Please remember to help with this week’s referral experiment. A retweet is what will do it!