That is the new and very good David Brooks column about Average is Over. Here is one excerpt:
So our challenge for the day is to think of exactly which mental abilities complement mechanized intelligence. Off the top of my head, I can think of a few mental types that will probably thrive in the years ahead.
…Synthesizers. The computerized world presents us with a surplus of information. The synthesizer has the capacity to surf through vast amounts of online data and crystallize a generalized pattern or story.
Humanizers. People evolved to relate to people. Humanizers take the interplay between man and machine and make it feel more natural. Steve Jobs did this by making each Apple product feel like nontechnological artifact. Someday a genius is going to take customer service phone trees and make them more human. Someday a retail genius is going to figure out where customers probably want automated checkout (the drugstore) and where they want the longer human interaction (the grocery store).
…Motivators. Millions of people begin online courses, but very few actually finish them. I suspect that’s because most students are not motivated to impress a computer the way they may be motivated to impress a human professor. Managers who can motivate supreme effort in a machine-dominated environment are going to be valuable.
Do read the whole thing.
Saxony State Police in Germany have developed a smartphone application that can identify neo-Nazi lyrics and racist words in rock songs. Der Spiegel reported Tuesday that German interior ministers will meet this week to discuss whether to implement this new method of policing.
The government said that neo-Nazi music helps radical organizations recruit youth, and it is used as a type of gateway drug to bring in new conscripts. The application, nicknamed “Nazi Shazam,” can identify names of songs just by playing a small sample of a song. The application would allow the police to react instantly if far-right songs are played on radio stations, at concerts, in club nights or at demonstrations.
There is much more here, hat tip goes to MT. This is of course another method of surveillance and measurement of our tastes, and some version of this idea will be picked up by marketers, whether or not this particular example is adopted.
Bitcoin miners, just like gold miners, use real resources to produce bitcoins. How much? In April when bitcoins traded for around $100 the electricity consumption of bitcoin miners was an astounding 1000 MGW hours a day, enough to power about 31,000 US homes or some $150,000 in daily expenditure.
As the price of bitcoin rises, so do the mining costs. Thus, today with bitcoin trading around $1000 the costs are much higher. According to BlockChain’s Bitcoin Statistics, miners are currently using 98,000 MGW hours or $14 million dollars of electricity a day to mine bitcoins. (One wonders, whose electricity?) And that is just the electricity costs, miners are also spending on hardware which has evolved from CPUs, to graphics processors to field-programmable gate arrays (FPGAs) and now to application-specific integrated circuits (ASICs).
Unlike the resource costs of a gold standard, which Milton Friedman once (over?) estimated at some 2.5% of GDP ever year forever, bitcoin mining may slow once the bitcoin limit of 21 million bitcoins is reached. Even that is tricky, however, because bitcoin mining currently subsidizes transaction costs so these will rise as bitcoin mining declines. Transaction costs are a necessary cost for a useful purpose so not all the mining is a net cost. Printing money is cheaper than gold or bitcoin mining but don’t forget that moving around fiat currency, by Brink’s truck or electronically, also has resource costs.
Hat tip for discussion to Eli Dourado.
Addendum: It’s an interesting bit of economics to ask why the cost of electricity doesn’t impact these numbers (even though it is used to calculate these numbers!).
Here is the latest:
It’s unlikely the majority of us are so overwhelmed with tweets, Facebook posts, emails and texts that we need someone – or something – to reply on our behalf.
However, this hasn’t stopped Google filing a patent for a system that would do just that.
According to the details of the latest patent filed by a software engineer at the firm, Google’s automated system would work like a social media bot and submit posts on a user’s behalf.
It would do this by scanning that user’s previous posts and replies on sites such as Facebook, Google+ and LinkedIn, as well as their emails and texts messages, to learn how that person writes.
The bot would then write replies and responses to future posts in a way that mimics that person’s usual language and tone.
The more a person uses the system, the more the bot can learn the type of responses they write and this would make the suggestions sound more human and realistic.
The full story is here. Some of you will recall that I discuss this possibility in Average is Over, and consider an equilibrium where many people secede from email altogether and the value of face time rises.
For the pointer I thank the excellent Mark Thorson.
Anyone in the US doing their holiday shopping from the product showcases that appear at the top of Google’s search results is almost certain to pay substantially more than if they delved deeper in the search engine.
Five out of every six items in the panels shown on a Google search made in America are more expensive than the same items from other merchants hidden deeper in the index, with an average premium of 34 per cent, according to a Financial Times analysis.
That is from Richard Waters at the FT. Do note, of course, that these higher listed products may also be of higher quality or offer better service in some way.
Jason Kottke suggests:
I could imagine Glass Concierge becoming a future job title, basically a personal assistant who looks in on your Google Glass video feed to make helpful suggestions and advice, basically a rally co-driver for your life.
Most of the post is about using Google Glass to cheat at poker. In response to inquiries, I will review the product once I can get one.
I very much enjoyed my visit to their excellent Saarinen-designed building, up in Westchester County somewhere. No office has a window but every path you might take from one part of the building to another gives you beautiful full-window views of the surrounding countryside.
I wish to thank all the people who took the time to show me and explain to me what they are up to. Their program suggested that more dairy (milk, not coconut milk) can be blended into Thai recipes with greater gain than you otherwise might think.
I had as a personal guide the man who is the voice of Watson and I told him to go see In a World…
Their cafeteria is excellent and the people in charge understand which recipes transfer well to institutional settings and which do not. Their vegetarian food is delicious and looks delicious, rendering the “nudge” unnecessary. From the rest of the menu, the turkey chili is of special commendation. Google take note, you are falling behind in the culinary department…
Here is the second paragraph of the piece:
In Asimov’s tale ["Franchise"], set in November 2008, democratic elections have become nearly obsolete. A mysterious supercomputer said to be “half a mile long and three stories high,” named Multivac, absorbs most of the current information about economic and political conditions and estimates which candidate is going to win. The machine, however, can’t quite do the job on its own, as there are some ineffable social influences it cannot measure and evaluate. So Multivac picks out one “representative” person from the electorate to ask about the country’s mood (sample query: “What do you think of the price of eggs?”). The answers, when combined with the initial computer diagnosis, suffice to settle the election. No one actually needs to vote.
The full article is here. There is an on-line version of Asimov’s Franchise here.
Companies, academics and individual software developers will be able to use it at a small fraction of the previous cost, drawing on IBM’s specialists in fields like computational linguistics to build machines that can interpret complex data and better interact with humans.
That is a big deal, obviously. The story is here.
The words on the website say it all:
Monetize without ads
Let your visitors help you mine Bitcoins
The pointer is from the excellent Ashok Rao.
It was with Joshua Rothman, here is one bit:
The whole narrative you unfold—intelligent software, human-computer cooperation, deferring to our smartphones—sounds very futuristic. Do you think we’re living through a historically unprecedented period?
I don’t accept the view that this new era is so different from every time in the past. Consider the industrial revolution, which starts in Great Britain in the seventeen-seventies or seventeen-eighties. For a long time, you had rising inequality, fairly stagnant living standards, a lot of problems adjusting. Of course, we did eventually get over it in the longer run, and it was much better for everyone. But it took, arguably, fifty or sixty years for us to make that transition. I think this future wave of inequality, which is already underway, will be a lot like that. It will take us decades to make the transition. Those decades will bring a lot of problems. But I think that in the much longer run—which is not what the book is about—it will be much more positive than it will seem during the transition era. I think this period fits quite nicely with historical precedent.
There is also this:
In the U.S., New York City is probably the most unequal place we’ve got. And I find it striking how many people believe, first, that inequality is terrible, and that this vision for the future is horrible, and, at the same time, think, “Oh, I love New York City!”
We already have places with extreme inequality, but life there goes on, and we don’t recoil in horror. The non-wealthy parts of New York are very vital, and have the best of humanity in them. We have intuitions [about equality and inequality] that are derived from American post-war history. I don’t want to dismiss those intuitions altogether, but I think we need to be more skeptical of them.
Aaron Beppu writes:
But some bots are driven by somewhat more trolly motives. A prime example is @StealthMountain, which searches for people using the phrase “sneak peak” and replies with “I think you mean ‘sneak peek’”. Effectively, a coder somehwere has used twitter to greatly leverage his ability to be a grammar Nazi. But worse, it appears that the bot exists just to rile people. While most people seem to take this correction in stride, @StealthMountain’s favorites list (which is linked from his bio line) is populated with some of the recipients’ more colorful reactions. You too, dear reader, can laugh at those victims, and their absurd, futile anger towards the machine.
At the most outrightly hostile end of the spectrum, we find the now defunct bot @EnjoyTheFilm, which searched for mentions of particular films or television shows, and replied with plot spoilers. This is a bot designed to actively try to ruin people’s evening, just for the fun of it.
There is more here, including a proposal for a “Feel Better bot,” via Eric Jonas.