Web/Tech

Here is an excerpt from a longer post, which also includes a summary:

Here are some of the most interesting ideas in the book:

1. Mind speeds: I had not previously spent much time thinking about how our brain’s hardware affects the speed at which we think. As it happens, our minds are spectacularly slow compared to what’s feasible with other materials! Better hardware, as well inequalities of hardware across individuals, will likely drive many parts of em society.

2. Death in the time of copies: An individual’s relationship to death is much different when you can make and store copies of yourself. Given how much of our current lives and societies are wrapped in who dies / how they die / when we die – a world where death is less central has major implications for identity, values, and relationships.

3. Security concerns are paramount: Theft (making copies of you without your permission) thus becomes almost more of an issue than death. As such, laws and cultural taboos will shift with security becoming more central to em value systems.

4. Less democratic: In a short period of a time, a well run non-democratic regime can outperform your average democracy. However, in the modern human world, these regimes often implode on themselves before they can dominate the rest of the world. But in the em world, things will move so fast (economic doubling rates are incredibly fast, every month or two!), that the rewards to short bursts of effective non-democratic regimes may be very high.

5. Religion: I tend not to think of robots as religious, but Robin makes the case that the utility of religion (nicer hard-working people) and the values of the em world (more farmer like) should lead to increased religiosity.

6. Increased utility: The sheer number of ems, coupled with their high mind speeds – as well as the likelihood that there lives will be ok in terms of meaning and happiness – suggests that the transition to an em world will be a positive utility move.

You can order the book here.  Here is my earlier review.

Which search terms correlate with support for which politicians?  Why not at least ask this question?

John Kasich. Places that like Kasich are richer in some fairly policy-wonkish search terms: “net cost,” “renewable portfolio standard,” the economist Joseph Stiglitz, Financial Times writer Martin Wolf, and Vox writer Dylan Matthews. These terms have a ring of plausibility. They might be good fodder for small talk…if you are talking with a Kasich supporter!

But then there are terms that I don’t entirely understand: Route 73 and Haven Pizza. Maybe someone can explain those to me. It is also true that with billions of search terms to choose from, occasionally a correlation will arise by chance. These might be false positives.

Ted Cruz. Many Cruz-related search terms are related to domestic life of a certain kind: family photos, felt Christmas stockings, scentsy plug ins, balloon animals, Baby Trend car seats, and DIY cribs. Easy enchiladas are particularly Cruz-y. Mmmm, enchiladas. And udder covers…I wasn’t expecting that one. Maybe the Cruz campaign could start distributing Cruz-themed udder covers!

Donald Trump. Note that the correlations are weaker. That could be because Trump support is broad-based in the Republican Party. Or it could be that the connection between the voter and the Google-searcher is indirect (i.e. they are different individuals who live near one another).

That is from Sam Wang, via the keen-eyed Jordan Schneider.  And what about the Democrats?

Near Clinton supporters it’s cheap bedroom furniture, Nicki Minaj fans, and pink hoverboard shoppers. And “career in” – Google auto-complete as a job counselor!

And the strongest correlate with Bernie Sanders support?: “candied nuts,” next in line is “best oatmeal,” ladies and gentlemen that is proof this is not just data mining and false correlations.  The list is dominated by recipe terms, and “corn syrup substitute” is number four!  Oh where oh where is Martin Wolf?

I considered the question of when one should just stop reading, and here is Robert’s take:

I read full-time to edit The Browser, and I abandon a hundred articles for every one that I finish. I generally stop if I hit “eponymous”, or “toxic”, or “trigger warning”, or “make no mistake”. Summary labelling of anything in an article as “complex” means that the writer does not understand or cannot explain the material. I don’t often read beyond headlines that use the words “surprising”, “secret”, “really”, “not” or “… and why it matters”. Any headline ending in a question mark is a bad sign. I know writers don’t usually write their own headlines, but the headline represents a best effort to say what is useful in the article by a sympathetic person who has been paid to read it.

Robert is one of the best readers I know.

Chinese “input” uses the QWERTY keyboard in an entirely different manner. In China, the QWERTY keyboard is “smart,” in the sense that it makes full use of modern-day computer power to augment and accelerate the input process. First of all, the letters of the Latin alphabet are not used in the same limited way that we use them in the alphabetic world. In China, “Q” (the button) doesn’t necessarily equal “Q” (the letter). Instead, to press the buttons marked Q, W, E, R, T, Y (or otherwise) is, strictly speaking, a way to give instructions to a piece of software known as an “Input Method Editor” (IME), which runs quietly in the background on your computer, intercepts all your keystrokes, and uses them as guidelines to try and figure out which Chinese characters the user wants. Using the most popular IME around today — Sougou Pinyin — the moment I strike the letter Q, the system is off and running, trying to figure out what I want. With the first clue, the IME immediately starts showing me options or “candidates” in a pop-up menu that follows me along on screen — in this case, Chinese characters, names, or phrases whose phonetic value begins with Q, such as Qingdao or Qigong.

The moment I hit the second button — let’s say U — the IME immediately changes up its recommendations, now giving me only characters that have pronunciations starting with “Qu.” There is no set, standard way to manage this process, moreover. There are many IMEs on the market, and each IME has many customizable settings. Some IMEs don’t use phonetics at all, in fact, but instead use Latin letters to indicate certain shapes or structural properties of the Chinese characters you want. And on top of all of this, there are countless abbreviations and shortcuts you can use to speed up the process (e.g., typing “Beijing” will get you the capital of China, but so will “bjing,” “beij,” or simply “bj”). And then, of course, there is “predictive text,” which as I have shown elsewhere, was developed and popularized in China decades before it was in the West.

In other words, for the computer age the Chinese system of characters has worked out quite well, and in some ways may be superior to the Roman alphabet.  The piece is Jeffrey Wasserstrom interviewing Tom Mullaney, and is of interest more generally.

Here is my new paper on that topic (pdf), commissioned by the Asian Development Bank (but not yet approved or refereed by them).  The key question is what kind of development path will follow, given the realities of premature deindustrialization in emerging economies today.  Here is one bit from the paper:

…trickle-down growth from price discrimination and the erosion of intellectual property rents becomes more important as a source of economic improvement. I call this mechanism “cell phones instead of automobile factories.” Many economic ideas are subject to non-rivalrous use, as they can be deployed by many people once they exist. That phenomenon may sound separate from the substitution of capital for labor outlined above, but that is part of the same broader process. If the wealthier nations use smart software to displace imports from the developing world, poorer nations will benefit from the software in other ways, including a trickle-down of goods and services.

The cell phone (and by extension the smart phone) is a paradigmatic example of trickle-down consumption. The technologies behind the cell phone were invented across a variety of nations, none of them poor (although China contributed to the finishing process), and yet cell phones are extremely prominent in poor and lesser developed nations. Internationally, cell phones and smart phones have brought significant benefits and often at relatively low cost. In the poorer parts of Asia, cell and smart phones are available for much lower prices than in the West. Part of that is the result of price discrimination, such as when Samsung sets deliberately lower prices for most of Africa and the poorer parts of Asia. In other cases the poorer countries buy a somewhat lower quality product, but one still effective for many of their needs. The Blackberry was not long ago state of the art in the United States, but now it sells primarily in poorer countries, including Indonesia, Vietnam, and South Asia, in addition to parts of Africa, and of course it sells to these regions at lower prices.

And this:

Or in other words, rather than Indonesia or Cambodia exporting manufactures to buy imported goods, an alternative development path is that some of those imports trickle down and enter poorer countries at especially low prices. Poorer economies can’t get constant cost goods and services for any cheaper than they are available in wealthier countries and in fact they may have to pay more because of shipping costs, poor institutions, and less efficient retail systems. If the wealthy nations produce more cement, the trickle down benefits from that activity may be slight. But for declining cost commodities, it is a different story entirely.

The more the economies of the wealthy countries are focused on increasing returns to scale sectors, the more important this version of trickle-down growth will become. And for the last few decades, many of the most important innovations in the wealthy countries have been shifting into increasing returns to scale sectors, most notably in the tech world. The tech world is geographically clustered, and centered in Silicon Valley, which are both classic signs of an increasing returns to scale sector. Some of the outputs are given away for free (Google, Facebook), and others show high degrees of market concentration, with a single dominant supplier providing a network good (eBay, Facebook, Instagram, Twitter). When it comes to the hardware behind the tech sector, there is an emphasis on new models, upgrades, and differential pricing plans, again all signs of increasing returns to scale.

In the limiting case, if everything in the economy looks and acts like the tech sector, this source of growth could be quite significant indeed. In other words, a world where “software eats the world,” to borrow Marc Andreessen’s phrase, is a world where the developing nations end up doing pretty well, even if the traditional export-oriented path to convergence has gone away.

Most forms of economic growth are fundamentally imbalanced (Hirschman 1958), but in this “cell phones scenario” we see a new form of imbalance. The new imbalance would be based on increasing returns to scale goods, which would trickle down to poorer countries, vs. constant and increasing cost goods, which would not trickle down. Developing nations thus would be very well supplied with (cheaper versions of) increasing returns to scale goods, but have relatively stagnant supplies of constant and decreasing returns to scale goods.

Comments of course are welcome.  The paper also includes some brief discussions of how the main arguments might apply to China, India, the Philippines, and Central Asia, in line with its ADB origins.

It seems we search more for jokes in better, cheerier times:

…Monday is actually the day we are least likely to search for jokes. Searches for jokes climb through the week and are highest on Friday through Sunday. This isn’t because people are too busy with work or school on Mondays. Searches for “depression,” “anxiety” and “doctor” are all highest on Mondays.

Second, I compared searches for jokes to the weather. I did this for all searches in the New York City area over the past five years. Rain was a wash, but there were 6 percent fewer searches for jokes when it was below freezing. There were also 3 percent fewer searches for jokes on foggy days.

Finally, I looked at searches for jokes during traumatic events. Consider, for example, the Boston Marathon bombing. Shortly after the bombing, searches for “jokes” dropped nearly 20 percent. They remained almost as low in the days after the attack, including the Friday when Boston was in lockdown while the authorities searched for the bomber who was still on the loose. They didn’t return to normal until two weeks later.

Sure, some other entertainment searches, like “music” and “shopping,” also dropped after the bombing. Declines in these searches, however, were smaller than declines in searches for jokes, and some entertainment searches, like “games,” actually rose during the manhunt.

That is from Seth Stephens-Davidowitz (NYT).  I am mostly convinced, in part because of the Boston data, still I wonder how much searching for jokes is in fact correlated with better moods.  I would think of myself as being in a rather sad state if I had to find humor from impersonal sources on-line, rather than from people I know.

Twitter Reminder

by on May 16, 2016 at 12:07 pm in Web/Tech | Permalink

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There is a new and intriguing book out by Benjamin Peters called How Not to Network a Nation: The Uneasy History of the Soviet Internet, which outlines exactly what it claims to.  Here is one introductory excerpt:

In late September 1970, a year after the ARPANET went online, the Soviet cyberneticist Viktor Glushkov boarded a train from Kiev to Moscow to attend what proved to be a fateful meeting for the future of what we might call the Soviet Internet.  On the windy morning of October 1, 1970, he met with members of the Politburo, the governing body of the Soviet state, around the long rectangular table on a red carpet in Stalin’s former office in the Kremlin.  The Politburo convened that day to hear Glushkov’s proposal and decide whether to build a massive nationwide computer network for citizen use — or what Glushkov called the All-State Automated System (OGAS, obshche-gosudarstvennyi avtomatizirovannaya system), the most ambitious computer network of its kind in the world at the time.  OGAS was to connect tens of thousands of computer centers and to manage and optimize in real time the communications between hundreds of thousands of workers, factory managers, and regional and national administrators.  The purpose of the OGAS Project was simple to state and grandiose to imagine: Glushkov sought to network and automatically manage the nation’s struggling command economy.

They failed!  The author blames this not on backward technology, but rather “entrenched bureaucratic corruption and conflicts of interest at the heart of the system…”

Anyone interested in the history of the internet, comparative systems, or the history of the Soviet Union should read this book.

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What is the deal these days?  How well are VPNs working, and which do you recommend?  Can Apple iPhones and iPads still access the “real web” directly through 4G, as was the case as recently as last year?  I thank you in advance for your assistance, it is much appreciated.

Third-grader Andrew Calabrese carries his backpack everywhere he goes at his San Diego-area school. His backpack isn’t just filled with books, it is carrying his robotic pancreas.

The device, long considered the Holy Grail of Type 1 diabetes technology, wasn’t constructed by a medical-device company. It hasn’t been approved by regulators.

It was put together by his father.

Jason Calabrese, a software engineer, followed instructions that had been shared online to hack an old insulin pump so it could automatically dose the hormone in response to his son’s blood-sugar levels. Mr. Calabrese got the approval of Andrew’s doctor for his son to take the home-built device to school.

The Calabreses aren’t alone. More than 50 people have soldered, tinkered and written software to make such devices for themselves or their children. The systems—known in the industry as artificial pancreases or closed loop systems—have been studied for decades, but improvements to sensor technology for real-time glucose monitoring have made them possible.

The Food and Drug Administration has made approving such devices a priority and several companies are working on them. But the yearslong process of commercial development and regulatory approval is longer than many patients want, and some are technologically savvy enough to do it on their own.

Here is the Kate Linebaugh story, interesting throughout, via Adam Thierer and Eli Dourado.

That’s the hullaballoo of the day (NYT here):

Facebook workers routinely suppressed news stories of interest to conservative readers from the social network’s influential “trending” news section, according to a former journalist who worked on the project. This individual says that workers prevented stories about the right-wing CPAC gathering, Mitt Romney, Rand Paul, and other conservative topics from appearing in the highly-influential section, even though they were organically trending among the site’s users.

That’s not exactly what I would have suppressed, but I can’t say I am broken up about this.  Most media bias in journalism is demand-driven, and I suspect this feature of the article selection and elevation “algorithm” is perceived by Facebook as demand-driven as well.  Overall I think of Twitter as radicalizing, and Facebook as calming and connecting.  The “censored” right wing sources don’t fit the chummy, nostalgic socializing mood so well, and therefore Facebook wanted to keep them away.  A clear minority is sufficiently interested in those stories to get them trending initially, but that’s not the overall image Facebook wants to present to either its marginal or median user.

Maybe such algorithms mean that social ideas are too slow to change, because user demand depends in part on what Facebook pushes.  Right now I’m more worried about American ideas getting worse than American ideas getting better, so a status quo, don’t offend anybody bias I can live with.  And frankly, a lot of right-wing news sources just aren’t very good — I suppress them myself, without any aid from Facebook.

There is also this:

“People stopped caring about Syria,” one former curator said. “[And] if it wasn’t trending on Facebook, it would make Facebook look bad.” That same curator said the Black Lives Matter movement was also injected into Facebook’s trending news module. “Facebook got a lot of pressure about not having a trending topic for Black Lives Matter,” the individual said. “They realized it was a problem, and they boosted it in the ordering. They gave it preference over other topics. When we injected it, everyone started saying, ‘Yeah, now I’m seeing it as number one’.” This particular injection is especially noteworthy because the #BlackLivesMatter movement originated on Facebook, and the ensuing media coverage of the movement often noted its powerful social media presence.

In those two cases I see the change in coverage as bringing net content gain rather than loss.  The cynical underlying reality is that Facebook does not wish to appear heartless, but does not (yet) have the more subtle manipulative institutions that newspapers and TV stations have developed over decades or even centuries.  They clumsily act in a politically correct manner, without proper institutional camouflage, and now they are being called on it.  They will refine their bias, and make it subtler and harder to criticize, thereby becoming more like most other media outlets.  Ultimately this is more of a social conformity story than a monopoly power dilemma.  I am more worried about pervasive ennui and complacency than the political bias per se.

WSJ: One day in January, Eric Wilson dashed off a message to the teaching assistants for an online course at the Georgia Institute of Technology.

“I really feel like I missed the mark in giving the correct amount of feedback,” he wrote, pleading to revise an assignment.

Thirteen minutes later, the TA responded. “Unfortunately, there is not a way to edit submitted feedback,” wrote Jill Watson, one of nine assistants for the 300-plus students.

Last week, Mr. Wilson found out he had been seeking guidance from a computer.

…Last year, a team of Georgia Tech researchers began creating Ms. Watson by poring through nearly 40,000 postings on a discussion forum known as “Piazza” and training her to answer related questions based on prior responses. By late March, she began posting responses live.

Don’t confuse Ms. Watson with the customer-service chatbots used online by airlines and other industries. Mr. Goel boasts that she answers only if she has a confidence rate of at least 97%.

“Most chatbots operate at the level of a novice,” Mr. Goel said. “Jill operates at the level of an expert.”

In our paper on online education Tyler and I wrote about AI Tutors:

Feedback from interactive systems will be more immediate and more informative (Skinner 1958). Adaptive tutoring systems are already nearly as effective as human tutors in many circumstances and much cheaper to scale (VanLehn 2011).

Here is the latest:

Google is sufficiently confident about its technology that its staff have discussed launching a fully autonomous taxi service in Mountain View as soon as next year, according to people familiar with the company’s thinking. The service may initially be restricted to Google employees, which might get around any legal and regulatory issues. Google has already run some tests with employees who are trained drivers.

I enjoyed this bit too:

Yet real life brings surprises no-one can anticipate. Last year, a Google car rounded a corner to find a woman in an electric wheelchair chasing a duck with a broom in the middle of the road. “We’d never tested the car against a woman and a duck,” Mr Urmson says, “and it was able to understand this was unusual, slow down, let that thing play out and then get on its way.”

Here is the Tim Bradshaw FT piece, and for the pointer I thank Michael Gibson.  And Ted Craig sends me this:

General Motors Co. and Lyft Inc. will begin testing a fleet of self-driving Chevrolet Bolt electric taxis on public roads within a year, a move central to the companies’ joint efforts to challenge Silicon Valley giants in the battle to reshape the auto industry.

And here is Viv, which is supposed to be better than Siri.  And here:

A robot is being designed to compete with 12th graders during the college entrance examination in 2017 and get a score qualifying it to enter first-class universities in China, according to Huaxi Metropolis Daily.

The robot will not be connected to the internet.  And from the world of photography, here are robot portraits.  And yet more from the FT:

US researchers have developed what they say is the world’s first surgical robot that can outperform human surgeons when operating autonomously on soft tissues such as intestines, paving the way for clinical trials.

Or this:

Airbus is working with French and Japanese researchers to develop humanoid robots able to work alongside humans on its assembly lines and inside aircraft, in what would be a step change in the use of industrial robotics.

That is a lot of robot news for a day and a half.

Having been named as Mr Nakamoto once, unconvincingly, Mr Wright has a steep hill to climb to convince the world that he is indeed bitcoin’s founder. Evaluating his claim involves the application of a multi-step paternity test. First comes the factual evidence: can Mr Wright prove that he is in possession of cryptographic keys that only Mr Nakamoto should have? Second, does he have convincing explanations for the holes in the story which came to light when he was first outed in December? Third, does he possess the technical knowledge which would have enabled him to develop a system as complex and clever as bitcoin? And fourth, to what extent does he fit the image that people have of Mr Nakamoto; in particular, what do those software developers who have collaborated online with the founder of bitcoin think of Mr Wright’s claim?

Here is a very good Economist article, I say p = 0.415.  There is some legitimate evidence and some serious endorsers, but the whole thing still doesn’t smell right to me.  You?

Update from my iPad: uh-oh, http://www.economist.com/news/briefings/21698066-onus-on-craig-wright-provide-better-evidence-satoshi-nakamoto?fsrc=scn/tw/te/bl/ed/craigwrightsclaimsunderfire