🔮 After Uber; Snapchat's boom; tech ethics; curing cancer; preventing suicide; Sachs, Dennett & lucid dreams++ #103
|Azeem Azhar||Mar 5, 2017|
Snapchat pops. Ride-sharing is here to stay, even if Uber implodes. How the focus on exponential company growth corrupts. Trade and protectionism. Predicting suicide early. A conversation with Jeff Sachs.
Hope this sparks great conversations!
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Dept of the near future
🚗 After Uber. Uber may yet implode. Transportation-as-a-service will still have a rosy future, argues Kevin Maney. EXCELLENT READ (Note: this article is in Newsweek which three years ago ‘unmasked’ the creator of Bitcoin.)
🔥 Exponential growth devours and corrupts argues David Heinemeier Hansson. We need to ’to offer realistic, ethical alternatives to the exponential growth logic. Ones that’ll benefit not just a gilded few, but all of us. The future literally depends on it.’ EXCORIATING
🔮 Podcast: Jeff Sachs and I had a really great conversation on artificial intelligence, automation, basic income, inequality and Aristotle. MUST LISTEN.
🙏🏼 Great discussion with Daniel Dennett on AI, robots and religion . ($) THOUGHT-PROVOKING READ
Dept of ethics in technology
We regularly cover ethics in Exponential View. The rationale is reasonably straightforward. Increasingly our access to all services are mediated by technology. Technology has long outgrown its niche status but rather is our fundamental interface to the world.
The optimism of the technology industry (particularly with the rise of the Internet in the 1980s and 1990s) was that power would be decentralised and distributed. The Internet was the supposed to be a decentralised, open network. Built to survive nuclear destruction (if the line of defence afforded by MAD failed), the Internet’s first services were initiated, in many cases, by thoughtful netizens influenced by the counter-culture movement of the late 1960s. (See, for example, Jon Postel and Stewart Brand.)
In the past 30 years, the Internet has grown up. Far from being decentralised, favouring the edge and facilitating groups, the Internet is dominated by two Leviathans Facebook and Google.
At the same time, a template, call it ‘zero-to-one’, has emerged for building new monopolies, new Leviathans. And that template, as DHH describes above, relentless optimisation in pursuit of extreme growth. At all costs. At any cost.
And the engineers-entrepreneurs leading these firms have found themselves in positions of power that call for more Socrates than slide rule, Mill & Marx than machine learning, Rawls than regression analysis, Aristotle than AI, Nussbaum than ninety-day-plans…
🎱 Greyball is Uber’s tool for avoiding regulatory authorities and law enforcement, reveals the New York Times. The company “has for years engaged in a worldwide program to deceive the authorities in markets where its low-cost ride-hailing service was resisted by law enforcement or, in some instances, had been banned.”
EV reader, Vivek Wadhwa: What students can learn from Uber’s troubles.
🐈 Izabella Kaminska: the true carbon cost of viral cat videos
Dept of artificial intelligence
What if algorithms can spot suicide risks before the people around you can? Or potentially before you already knew. In a soon to be published paper, a researcher claims to be able to spot suicide risks with 80% accuracy up to two years in advance.
Similar peer-reviewed work has applied machine learning to long-term observation of physical symptoms to improve early identification of suicide risk. This model achieved an AUC performance of 0.71, a significant improvement on clinician AUC of 0.56. (Perfect prediction would have an AUC of 1.0).
Even Facebook has developed an algorithm that can spot suicide risk based on your status updates. It seems likely the Google search data could do the same.
This brings to mind my discussion with Yuval Harari on when algorithms know us better than we know ourselves. Whether Facebook from status updates or the pattern of our physical symptoms from regular public health monitoring, we’re better able to predict individual behaviour than ever before.
**💡 EXCELLENT: **Should economists worry more about artificial intelligence? “The very different nature of the technological advances currently in progress, in terms of their much broader industrial and occupational applications and their speed of diffusion” means our previous models may not be applicable.
Bradford Cross: Five AI startup predictions SUPER (tl;dr: Go fullstack)
Medha Agarwal: Nice primer on machine learning and its impact on products.
What are the tensors in Tensorflow (and modern machine learning more broadly)? NICE INTRODUCTION
Netflix uses machine learning to enhance video quality on the fly
Apple may have about to 1,000 AR engineers working in Israel.
Millenials love voice interfaces
📜 Interesting profile of JP Morgan’s success with machine learning to radically optimise loan assessment.
Exponential View Private Dinner: International Relations in the Age of Trump
I am really excited about our next Exponential View dinner.
Our discussion will be led by Bill Emmott, former editor-in-chief of The Economist.
Bill is a world expert in global business and international political economy, who scarcely needs further introduction.
We’ll touch on one of the most pressing issues facing us as citizens, entrepreneurs and investors. And of particular relevance of those of us in global industries (like tech, health, finance, education and others.)
If you want to attend, please register your interest here.
We would be very happy to see you.
Small morsels to appear smart at dinner parties
Children working as cobalt miners in Congo.
US consumers now spend 5 hours per day on mobile devices. (21% of all their time!!)
Microbiomes and eczema. Fascinating.
I’m getting quite interested in the microbiome so I am up for some book recommendations on the topic. This might lead up to a podcast or event at some point. Do let me know your recommendations.