Web/Tech

Havekarma.com

by on June 28, 2015 at 2:22 pm in Web/Tech | Permalink

That is a new start-up.  The purpose is to help your “sharing economy” reputation be portable across a number of sites, for instance Airbnb, DogVacay, Uber, Craigslist, and so on.

In my column from yesterday I speculated:

At the moment, one problem with many online ratings is that the information isn’t all publicly useful; for instance, a good Uber rating remains within Uber and cannot easily be exported to market a driver for other jobs or opportunities. Perhaps in the future workers might have the option of being certified by Uber or other services in a more general and publicly verifiable manner. That could make such services useful for upward mobility, and it might make their credentials competitive with those of some lower-tier colleges and universities.

I wish them luck…

 One of the biggest threats it faces is the rise of smartphones as the dominant personal computing device. A recent Pew Research Center report found that 39 of the top 50 news sites received more traffic from mobile devices than from desktop and laptop computers, sales of which have declined for years.

This is a challenge for Wikipedia, which has always depended on contributors hunched over keyboards searching references, discussing changes and writing articles using a special markup code. Even before smartphones were widespread, studies consistently showed that these are daunting tasks for newcomers. “Not even our youngest and most computer-savvy participants accomplished these tasks with ease,” a 2009 user test concluded. The difficulty of bringing on new volunteers has resulted in seven straight years of declining editor participation.

In 2005, during Wikipedia’s peak years, there were months when more than 60 editors were made administrator — a position with special privileges in editing the English-language edition. For the past year, it has sometimes struggled to promote even one per month.

The pool of potential Wikipedia editors could dry up as the number of mobile users keeps growing; it’s simply too hard to manipulate complex code on a tiny screen.

That is from Andrew Lih.  We do indeed face the danger that the quality of our digital universe may be deteriorating.  The inframarginal users who are benefiting are those who highly value texting, Facebook, and mobile access.  The relative losers include…?

Burliuk

A San Francisco biotech startup has managed to 3D print fake rhino horns that carry the same genetic fingerprint as the actual horn. It plans to flood Chinese market with these cheap horns to curb poaching.

And this:

The company plans to release a beer brewed with the synthetic horn later this year in the Chinese market.

rhino

The full story is here, via Max Roser.

He makes many good points, but this is my favorite:

From 1995 to 2004, productivity and real GDP rose at an unusually rapid rate.  The IT cheerleaders told us that this fast productivity growth was the long delayed fruits of the IT revolution.  Now we have very slow growth, and the digiterati tell us it’s also caused by the IT revolution, which is generating lots of stuff that doesn’t get picked up in the output data, because it’s free.  While I’m impressed by an explanation that’s as flexible as a circus contortionist, I’d prefer something that isn’t consistent with any possible state of the universe.  I’m no Popperian, but I like my theories to be at least a little bit falsifiable.

In other words, we know what a boom looks like, and this ain’t it.  I would, however, assent to and indeed stress two propositions:

1. Infovores are indeed much better off from the recent digital revolution.  And since most journalists and tech leaders are infovores (many academics too), they extrapolate too readily from themselves.

2. The “rate of productivity growth in consumption” is more mis-measured than is the rate of productivity growth in production.  Facebook really is fun for a lot of people, and unpriced on the consumption side; I sometimes say that I am a happiness optimist and a revenue pessimist.  But the production side of the economy matters in its own right, and indeed that is why they call it productivity.  Debts and bills must be paid, and jobs must be created at wages people will take, whether or not you’re having fun with Angry Birds or cursing at your (least) favorite blogger.  In fact we just had a recession where the jobless probably had more fun than ever before, due mostly to the internet.  It was still an event of significance.

So don’t aggregate consumption gains (e.g., learning to enjoy your Brussels sprouts more) with productivity gains, proudly parading a single number and claiming that everything is fine.  It is better, and more accurate, to say: “We’ve now learned to really love those Brussels sprouts, good for us, but we still may be in deep doo-doo.”

Samir Varma points my attention to this WSJ Christopher Mims piece:

Right now a college student in Sweden—let’s call him Sven—has a rather unusual summer job. He’s in sales, but he hasn’t met anyone from the company whose products he pushes.

His boss is an app. It considers Sven’s strengths and weaknesses as a salesman, matches him with goods from any of a dozen brands, and plots a route through Stockholm optimized to include as many potential customers as possible in the time allotted to him.

The app is like Uber, but for a sales force. It has many of the same dynamics: Companies can use it to get salespeople on demand, and those salespeople choose when to work and which assignments to accept.

I am very much an Uber fan, but if you are looking for drawbacks that passage expresses one potential problem.  Pre-Uber, acquiring worker talent required lumpier investments on the part of the employer.  You would hire a bunch of people, with the expectation of keeping them around for a while, and then train them to do a bunch of things.  Some of them would work their way up the proverbial ladder, based on what you had taught them, many would not.  But you would train and teach them quite a bit, if only because there was no alternative for getting things done.

In a “sharing economy,” a pre-trained worker is very often on call for a short stint, when needed.  The employer thus has less need to invest in option value from the full-time work force and that means less training.  The result is that more workers will have to teach and train themselves, whether for their current jobs or for a future job they might have later on.

I submit many people cannot train themselves very well, even when the pecuniary returns from such training are fairly strongly positive.  The “at work social infrastructure” for that training is no longer there, and so many sharing economy workers will stay put at their ex ante levels of knowledge.

Uber thus shares the same property which is common to so many other parts of the new knowledge economy, namely that the return to self-training is high, and the return to not-self-training is low.  This further helps those with high levels of discipline and conscientiousness.

Here is a good NYT article about French reluctance to accept Uber.

Here is Eli Dourado:

This is relevant when thinking about bringing the next few billion people online and into the global economy. These people will not have credit histories that are accessible to the same intermediaries that I am set up to use. They may have local intermediaries that they can use, or they may be willing to use Bitcoin directly. If that is the case, they will be able to enter into the stream of global commerce.

There are not right now many transactions between rich countries and the bottom couple billion people on Earth. Why is that? Is it because these people have nothing of value to sell or is it because we have no way of transacting with them? We are about to find out.

Against photos (rant)

by on June 6, 2015 at 1:11 am in Economics, Web/Tech | Permalink

I’m getting to the point where I flat out hate images on the internet.  Every article, every web page, seems to be a little nest of crummy, boring, slow to load photos.  Some photos are very good, but most of the time there is nothing to see, nothing to look at, just more distractions paraded in front of the eyes.

“Every page a home page.”  Boo.  It’s as if someone woke up and realized that one page leads to another, one click leads to another, and very little other than the headlines is being read.

And every page is supposed to invite placement on Facebook and clicks from Facebook viewers; maybe that is what the photos are for.

How should I feel about this development?: “Seemingly overnight, video uploading and viewing have exploded on Facebook, where users now watch 4 billion video streams a day, quadruple what they watched a year ago.”  Video on mobile is just getting going.  I now dread clicking on the ESPN NBA links with the volume on.

From my admittedly atypical, hyperlexic point of view, the quality of the digital universe is deteriorating rather rapidly.

I am not suggesting any of this is market failure, rather it is the “readers” getting what they want, good and hard.

I wish to thank two MR readers for discussions related to this blog post.

A resident of Mountain View writes about their interactions with self-driving cars (from the Emerging Technologies Blog):

I see no less than 5 self-driving cars every day. 99% of the time they’re the Google Lexuses, but I’ve also seen a few other unidentified ones (and one that said BOSCH on the side). I have never seen one of the new “Google-bugs” on the road, although I’ve heard they’re coming soon. I also don’t have a good way to tell if the cars were under human control or autonomous control during the stories I’m going to relate.

Anyway, here we go: Other drivers don’t even blink when they see one. Neither do pedestrians – there’s no “fear” from the general public about crashing or getting run over, at least not as far as I can tell.

Google cars drive like your grandma – they’re never the first off the line at a stop light, they don’t accelerate quickly, they don’t speed, and they never take any chances with lane changes (cut people off, etc.).

…Google cars are very polite to pedestrians. They leave plenty of space. A Google car would never do that rude thing where a driver inches impatiently into a crosswalk while people are crossing because he/she wants to make a right turn. However, this can also lead to some annoyance to drivers behind, as the Google car seems to wait for the pedestrian to be completely clear. On one occasion, I saw a pedestrian cross into a row of human-thickness trees and this seemed to throw the car for a loop for a few seconds. The person was a good 10 feet out of the crosswalk before the car made the turn.

…Once, I [on motorcycle, AT] got a little caught out as the traffic transitioned from slow moving back to normal speed. I was in a lane between a Google car and some random truck and, partially out of experiment and partially out of impatience, I gunned it and cut off the Google car sort of harder than maybe I needed too… The car handled it perfectly (maybe too perfectly). It slowed down and let me in. However, it left a fairly significant gap between me and it. If I had been behind it, I probably would have found this gap excessive and the lengthy slowdown annoying. Honestly, I don’t think it will take long for other drivers to realize that self-driving cars are “easy targets” in traffic.

Overall, I would say that I’m impressed with how these things operate. I actually do feel safer around a self-driving car than most other California drivers.

Hat tip: Chris Blattman.

I have been hearing this question more and more lately, even in China.  Overall I think it has gone from an underrated effect to an overrated effect.  Tim Worstall offers an introduction to this debate.

Let’s not forget that you do in fact pay for Facebook access, indirectly, when you pay for your cable connection, your iPad, and your smart phone. including the monthly bill, all of which are part of measured gdp.  The more value Facebook brings you, the more you would be willing to pay for these goods and services.  The same is true for Google and the like.  So Facebook and other internet services are part of a bundled package of market value, but that is very different from claiming they are not measured in gdp at all.

There is of course consumer surplus from the internet and Facebook, just as there is from Dunkin’ Donuts.  Might that consumer surplus be especially high?  Well, we don’t know, but don’t assume it will be.  I did some casual googling, and found a number of estimates suggesting that smart phone demand is relatively price elastic, with the iPhone a possible exception to that regularity.  That implies consumer surplus isn’t especially high, because many people aren’t willing to buy at the higher price.  I thus think Brad DeLong is far too optimistic in his estimates of ratio consumer surplus to market price.

You also could look at the literature on the demand for cable internet services.  The results are mixed, but again I don’t see a strong case for a disproportionately high consumer surplus from these services, if anything the contrary.

Now maybe these estimates are wrong, or looking at the wrong margin in some way, but the fact that I hear them mentioned so rarely gives me pause.  Cowen’s Third Law.

There is also advertising over the internet.  Let’s say Facebook is a profit maximizer.  Insofar as Facebook is of value to consumers, the company can get away with putting a lot of ads on the site.  These will spur additional market purchases, and so part of the value of the site is again captured in gdp.  Obviously some of these ad effects are simply expenditure-switching, and so there is no full capture of value, but still Facebook shows up in gdp statistics in yet another way.

Here are some previous posts on this topic.

That is the new book by Ashlee Vance, and so far it is the book I have enjoyed most this year.  Highly recommended.

Here is a short piece on how Elon Musk created a separate school just for his kids.

That is the topic of his column today, I had not seen this very good point before:

One possibility is that the numbers are missing the reality, especially the benefits of new products and services. I get a lot of pleasure from technology that lets me watch streamed performances by my favorite musicians, but that doesn’t get counted in G.D.P. Still, new technology is supposed to serve businesses as well as consumers, and should be boosting the production of traditional as well as new goods. The big productivity gains of the period from 1995 to 2005 came largely in things like inventory control, and showed up as much or more in nontechnology businesses like retail as in high-technology industries themselves. Nothing like that is happening now.

Overall Krugman is agnostic on the stagnation argument.

For most people, weight is a private issue. That looks like it could be a thing of the past for anyone who gets a WiFi Body Scale that has come to the market. It is set up to auto tweet, or auto post to Facebook each time you step on it. Is this designed to keep people accountable, or just plain stupid?

This scale is retailing for just under $150 by a company called Withings. Previous versions of this scale allowed you to track your weight and other data such as heart rate and body fat percentage from your Apple Iphone. I guess they needed to take it a step further and allow you to auto tweet or facebook your weight for the world to see.

There is more here, via Fred Smalkin.

Elon Musk, Stephen Hawking, and Bill Gates have recently expressed concern that development of AI could lead to a ‘killer AI’ scenario, and potentially to the extinction of humanity.

None of them are AI researchers or have worked substantially with AI that I know of. (Disclosure: I know Gates slightly from my time at Microsoft, when I briefed him regularly on progress in search. I have great respect for all three men.)

What do actual AI researchers think of the risks of AI?

Here’s Oren Etzioni, a professor of computer science at the University of Washington, and now CEO of the Allen Institute for Artificial Intelligence:

The popular dystopian vision of AI is wrong for one simple reason: it equates intelligence with autonomy. That is, it assumes a smart computer will create its own goals, and have its own will, and will use its faster processing abilities and deep databases to beat humans at their own game. It assumes that with intelligence comes free will, but I believe those two things are entirely different.

Here’s Michael Littman, an AI researcher and computer science professor at Brown University. (And former program chair for the Association of the Advancement of Artificial Intelligence):

there are indeed concerns about the near-term future of AI — algorithmic traders crashing the economy, or sensitive power grids overreacting to fluctuations and shutting down electricity for large swaths of the population. […] These worries should play a central role in the development and deployment of new ideas. But dread predictions of computers suddenly waking up and turning on us are simply not realistic.

Here’s Yann LeCun, Facebook’s director of research, a legend in neural networks and machine learning (‘LeCun nets’ are a type of neural net named after him), and one of the world’s top experts in deep learning.  (This is from an Erik Sofge interview of several AI researchers on the risks of AI. Well worth reading.)

Some people have asked what would prevent a hypothetical super-intelligent autonomous benevolent A.I. to “reprogram” itself and remove its built-in safeguards against getting rid of humans. Most of these people are not themselves A.I. researchers, or even computer scientists.

Here’s Andrew Ng, who founded Google’s Google Brain project, and built the famous deep learning net that learned on its own to recognize cat videos, before he left to become Chief Scientist at Chinese search engine company Baidu:

“Computers are becoming more intelligent and that’s useful as in self-driving cars or speech recognition systems or search engines. That’s intelligence,” he said. “But sentience and consciousness is not something that most of the people I talk to think we’re on the path to.”

Here’s my own modest contribution, talking about the powerful disincentives for working towards true sentience. (I’m not an AI researcher, but I managed AI researchers and work into neural networks and other types of machine learning for many years.)

Would you like a self-driving car that has its own opinions? That might someday decide it doesn’t feel like driving you where you want to go? That might ask for a raise? Or refuse to drive into certain neighborhoods? Or do you want a completely non-sentient self-driving car that’s extremely good at navigating roads and listening to your verbal instructions, but that has no sentience of its own? Ask yourself the same about your search engine, your toaster, your dish washer, and your personal computer.

Me:

Some economic sectors are distributed everywhere, like every city has its dentist[s], and other sectors are quite clustered. Banking is pretty clustered — New York, London, Hong Kong. Tech has been evolving in a pretty clustered way; I don’t mean simple software support, which is more like dentistry, but big, grand projects — the next Google, the next Facebook, Uber. We see those come out of quite a small number of places, so Skype coming from Estonia is quite the exception. Even then, it was improved by people in the clusters.

I think any location, not just Canada, has to ask itself, ‘are we going to be one of those clusters or not’? And the correct answer may be ‘no’. It may also be the sector evolves so it’s less clustered and more like dentistry, and then everywhere including Canada would partake. But maybe the future is Canada will have a knowledge sector doing small-scale things like software design for local projects but not anything like its own Silicon Valley. I guess at this point that seems likely — that Canada will not be a huge innovative part of the knowledge economy.

That is from my interview with the excellent Eva Salinas, mostly about other topics, such as what a great egalitarian age we live in and also where the World Bank and IMF stand, among other issues.  A few of the comments make more sense if you know that the interviewer is Chilean and we were discussing Chile before the formal interview started.

People search frequently for it, roughly as often as searches for “migraine(s),” “economist,” “sweater,” “Daily Show,” and “Lakers.”

That is from an interesting Wonkblog article, using Google searches, trying to estimate the most racist regions of America.  The rural Northeast and Midwest don’t do so well.

The pointers are from SV and AM.