15 October 2017

The Guardian: “Israel-Palestine: the real reason there’s still no peace”

The real explanation for the past decades of failed peace negotiations is not mistaken tactics or imperfect circumstances, but that no strategy can succeed if it is premised on Israel behaving irrationally. Most arguments put to Israel for agreeing to a partition are that it is preferable to an imagined, frightening future in which the country ceases to be either a Jewish state or a democracy, or both. Israel is constantly warned that if it does not soon decide to grant Palestinians citizenship or sovereignty, it will become, at some never-defined future date, an apartheid state. But these assertions contain the implicit acknowledgment that it makes no sense for Israel to strike a deal today rather than wait to see if such imagined threats actually materialise. If and when they do come to be, Israel can then make a deal. Perhaps in the interim, the hardship of Palestinian life will cause enough emigration that Israel may annex the West Bank without giving up the state’s Jewish majority. Or, perhaps, the West Bank will be absorbed by Jordan, and Gaza by Egypt, a better outcome than Palestinian statehood, in the view of many Israeli officials.

Nathan Thrall

That’s a damn valid reason! Israel (as a state) has little to lose from the status quo, given the unwillingness of the international community to impose tough sanctions. This lack of resolve is somewhat understandable, seeing how Israel is the only real long-term ally of Western democracies in a region largely controlled by military and religious autocracies – including Turkey lately. On the other hand, it exposes a dangerous double-standard, if we compare it, for example, with Russia’s incursion in Crimea, where sanctions were swiftly imposed.

13 October 2017

Vanity Fair: “How Elizabeth Holmes’s House of Cards Came Tumbling Down”

Like Apple, Theranos was secretive, even internally. Just as Jobs had famously insisted at 1 Infinite Loop, 10 minutes away, that departments were generally siloed, Holmes largely forbade her employees from communicating with one another about what they were working on—a culture that resulted in a rare form of executive omniscience. At Theranos, Holmes was founder, C.E.O., and chairwoman. There wasn’t a decision—from the number of American flags framed in the company’s hallway (they are ubiquitous) to the compensation of each new hire—that didn’t cross her desk.

And like Jobs, crucially, Holmes also paid indefatigable attention to her company’s story, its “narrative”. Theranos was not simply endeavoring to make a product that sold off the shelves and lined investors’ pockets; rather, it was attempting something far more poignant. In interviews, Holmes reiterated that Theranos’s proprietary technology could take a pinprick’s worth of blood, extracted from the tip of a finger, instead of intravenously, and test for hundreds of diseases—a remarkable innovation that was going to save millions of lives and, in a phrase she often repeated, “change the world”. In a technology sector populated by innumerable food-delivery apps, her quixotic ambition was applauded.

Nick Bilton

Silicon Valley arrogance at it’s finest. While some startup failure stories have an almost comic quality, this one verges on tragedy. Not for the founder, who seems so entangled in her illusions of grandeur that she completely lost touch with reality, but for the patients who used her fake blood tests.

12 October 2017

War on the Rocks: “The Rise and Fall of Erdoganocracy: Why Victory May Defeat Turkey’s President”

Eventually, the alliance fell apart in 2013, as Gulenists turned against Erdogan. The war between the two culminated in the coup attempt, which allowed Erdogan to purge most known Gulenists and opponents of all other ideological stripes from the state institutions and beyond.

Having relied on Gulenists as a substitute for secularists in the bureaucracy, this presents Erdogan with a human resource challenge. Erdogan and the AKP’s best bet in the short term is rewarding loyalty, not necessarily merit. The long term impact of this strategy will be dire: increased corruption and nepotism, decaying institutional effectiveness, and a flailing economy. Erdogan will likely blame all of this on Turkey’s opposition, but populist rhetoric has its limits, usually defined in terms of what everyday people experience in their own lives.

There will be a short term impact, too. Within the AKP, Erdogan will increasingly favor his die-hard loyalists. It is unlikely that the resulting resentment against unadulterated patronage within AKP ranks, as some commentators argue, will lead to the implosion of the party. More likely is a future where the AKP, marginalizing whatever is left of its own talent, will cannibalize what made it a big success story in the first place: institutional coherence and discipline. Put simply, one cannot have the cake and eat it too. As sociologist Max Weber recognized a century ago, “charismatic authority” and “bureaucratic authority” cannot easily co-exist. Erdogan’s rise as the “one man”, not only in Turkey but also within his own party, will also mean that AKP will start to decay as an organization.

Burak Kadercan

Interesting insights into the political situation in Turkey, which is becoming increasingly tense and polarized under the current president’s authoritarian measures. The secular, democratic state that his predecessors strived to build seems further and further from reality. I found the paragraphs above especially striking, as I suspect a similar situation is developing in the United States under the presidency of Donald Trump.

10 October 2017

The Verge: “Apple now sells an iPhone dongle with a headphone jack and charging port”

It took an entire year after the release of the iPhone 7 for Apple to start selling a dongle that lets you plug in headphones (or your car’s AUX cable) and charge at the same time. But now it’s here. Apple is just selling the thing, mind you — not making it. In September, Belkin quietly announced a new, second version of its “Rockstar” adapter that now includes both a 3.5mm jack and Lightning port.

Chris Welch

More courage!

Backchannel: “The Myth of a Superhuman AI”

There is no doubt that a super AI can accelerate the process of science. We can make computer simulations of atoms or cells and we can keep speeding them up by many factors, but two issues limit the usefulness of simulations in obtaining instant progress. First, simulations and models can only be faster than their subjects because they leave something out. That is the nature of a model or simulation. Also worth noting: The testing, vetting and proving of those models also has to take place in calendar time to match the rate of their subjects. The testing of ground truth can’t be sped up.


To be useful, artificial intelligences have to be embodied in the world, and that world will often set their pace of innovations. Without conducting experiments, building prototypes, having failures, and engaging in reality, an intelligence can have thoughts but not results. There won’t be instant discoveries the minute, hour, day or year a so-called “smarter-than-human” AI appears. Certainly the rate of discovery will be significantly accelerated by AI advances, in part because alien-ish AI will ask questions no human would ask, but even a vastly powerful (compared to us) intelligence doesn’t mean instant progress. Problems need far more than just intelligence to be solved.

Kevin Kelly

I’ve written about this in the past, but I think it’s worth repeating: AI doesn’t exist somewhere outside the physical restrictions of the real world, nor will it magically solve all human problems. And this article does a wonderful job of exposing and taking apart five assumptions most people make when discussing AI – well worth reading!

09 October 2017

Gizmodo: “Uber’s iOS App had Secret Permissions that allowed it to Copy your Phone Screen”

The screen recording capability comes from what’s called an “entitlement”—a bit of code that app developers can use for anything from setting up push notifications to interacting with Apple systems like iCloud or Apple Pay. This particular entitlement, however, was intended to improve memory management for the Apple Watch. The entitlement isn’t common and would require Apple’s explicit permission to use, the researchers explained. Will Strafach, a security researcher and CEO of Sudo Security Group, said he couldn’t find any other apps with the entitlement live on the App Store.

It looks like no other third-party developer has been able to get Apple to grant them a private sensitive entitlement of this nature, Strafach said. Considering Uber’s past privacy issues I am very curious how they convinced Apple to allow this.

Kate Conger

Tell me again how Apple is the ultimate defender of user privacy! Until they need help promoting one of their products, then all principles fly out of the window.

What if the meeting between Tim Cook and Travis Kalanick in early 2015 wasn’t about warning Kalanick to stop circumventing Apple’s rules, but instead to ask for Uber’s help in testing Apple Watch apps?!

The New Yorker: “A.I. versus M.D.”

The most powerful element in these clinical encounters, I realized, was not knowing that or knowing how—not mastering the facts of the case, or perceiving the patterns they formed. It lay in yet a third realm of knowledge: knowing why.


Knowing why—asking why—is our conduit to every kind of explanation, and explanation, increasingly, is what powers medical advances. Hinton spoke about baseball players and physicists. Diagnosticians, artificial or human, would be the baseball players—proficient but opaque. Medical researchers would be the physicists, as removed from the clinical field as theorists are from the baseball field, but with a desire to know “why”. It’s a convenient division of responsibilities—yet might it represent a loss?

A deep-learning system doesn’t have any explanatory power, as Hinton put it flatly. A black box cannot investigate cause. Indeed, he said, the more powerful the deep-learning system becomes, the more opaque it can become. As more features are extracted, the diagnosis becomes increasingly accurate. Why these features were extracted out of millions of other features, however, remains an unanswerable question. The algorithm can solve a case. It cannot build a case.

Siddhartha Mukherjee

Interesting overview of the promises and challenges of applying deep-learning techniques in medical diagnosis. There are certainly high expectations in the area, most notably IBM’s Watson, but recent reporting shows it is still far from fulfilling the promises. As I (and others) commented before, the big challenge for AI in any area is evolving past basic pattern recognition (factual knowledge) to a deeper understanding of the world, knowing how and why things work.