As an AI researcher, I think I am required to have an opinion about this. Here's what I have to say to the various tribes.
AI-pessimists: please remember that the Luddites have been wrong about technology causing economic cataclysm every time so far. We're talking about several consecutive centuries of wrongness.1 Please revise your confidence estimates downwards.
AI-optimists: please remember that just because the pessimists have always been wrong in the past does not mean that they must always be wrong in the future. It is not a natural law that the optimists must be right. That labor markets have adapted in the long term does not mean that they must adapt, to say nothing of short-term dislocations. Please revise your confidence estimates downwards.
Everyone: many forms of technology are substitutes for labor. Many forms of technology are complements to labor. Often a single form of technology is both simultaneously. It is impossible to determine a priori which effect will dominate.2 This is true of everything from the mouldboard plough to a convolutional neural network. Don't casually assert AI/ML/robots are qualitatively different. (For example, why does Bill Gates think we need a special tax on robots that is distinct from a tax on any other capital equipment?)
As always, please exercise cognitive and epistemic humility.
I am aware of the work of Gregory Clark and others related to Industrial Revolution era wage and consumption stagnation. If a disaster requires complicated statistical models to provide evidence it exists, I say its scale can not have been that disastrous. [↩]
Who correctly predicted that the introduction of ATMs would coincide with an increase in employment of bank tellers? Anyone? Anyone? Beuller? [↩]
I know plenty about algorithms, and enough about marketing.1 And despite that, I'm not sure what this headline actually means. It's eye catching, to be sure, but what would marketing to an algorithm look like?
When you get down to it, marketing is applied psychology. Algorithms don't have psyches. Whatever "marketing to algorithms" means, I don't think it's going to be recognizable as marketing.
Would you call what spammers do to slip past your filters "marketing"? (That's not rhetorical.) Does that count as marketing? Because that's pretty much what Gunton seems to be describing.
Setting aside the intriguing possibility of falling in love with an artificial intelligence, the film [Spike Jonez's Her] raises a potentially terrifying possibility for the marketing industry.
It suggests a world where an automated guardian manages our lives, taking away the awkward detail; the boring tasks of daily existence, leaving us with the bits we enjoy, or where we make a contribution. In this world our virtual assistants would quite naturally act as barriers between us and some brands and services.
Great swathes of brand relationships could become automated. Your energy bills and contracts, water, gas, car insurance, home insurance, bank, pension, life assurance, supermarket, home maintenance, transport solutions, IT and entertainment packages; all of these relationships could be managed by your beautiful personal OS.
If you're a electric company whose customers all interact with you via software daeomns, do you even have a brand identity any more? Aren't we discussing a world in which more things will be commoditized? And isn't that a good thing for most of the categories listed?
What do we really care about: getting goods and services, or expressing ourselves through the brands we identify with? Both, to an extent. But if we can no longer do that through our supermarkets or banking, won't we simply shift that focus it to other sectors: clothes, music, etc.
2. Consider that legislation may be an inferior form of law not just recently, or occasionally, but usually. Instead, consider the ideas of Bruno Leoni, which suggest that common law that emerges from individual cases represents a spontaneous order, while legislation represents an attempt at top-down control that works less well.
Both of these stories remind me of a couple of scenes in Greg Egan's excellent Permutation City. Egan describes a situation where people have daemons to answer their video phones that have learned (bottom-up) how to mimic your reactions well enough to screen out personal calls from automated messages. In turn marketers have software that learns how to recognize if they're talking to a real person or one of these filtering systems. The two have entered an evolutionary race to the point that people's filters are almost full-scale neurocognitive models of their personalities.
Enough to draw a paycheck from a department of marketing for a few years, at least. [↩]
Here is a question to think about. If religions help to create social capital by allowing people to signal conscientiousness, conformity, and trustworthiness [as Norenzayan claims], how does this relate to Bryan Caplan’s view that obtaining a college degree performs that function?
That might explain why the credentialist societies of Han China were relatively irreligious. Kling likes to use the Vickies/Thetes metaphor from Neal Stephenson's Diamond Age, and I think this dichotomy could play well with that. Wouldn't the tests required by the Reformed Distributed Republic fill this role, for instance?
This is by far the best, simplest explanation of Coase's insights that I have read. Having read plenty of Landsburg, that should not — indeed does not — surprise me.
His final 'graph is a digression, but a good point:
Coase’s Nobel Prize winning paper is surely one of the landmark papers of 20th century economics. It’s also entirely non-technical (which is fine), and (in my opinion) ridiculously verbose (which is annoying). It’s littered with numerical examples intended to illustrate several different but related points, but the points and the examples are so jumbled together that it’s often difficult to tell what point is being illustrated... Pioneering work is rarely presented cleanly, and Coase was a true pioneer.
And this is why I put little stock in "primary sources" when it comes to STEM. The intersection between people/publications who originate profound ideas and people/publications which explain profound ideas well is a narrow one. If what you want is the latter, don't automatically mistake it for the former. The best researchers are not the best teachers, and this is true as much for papers as it is for people.
Start a font by tweaking all glyphs at once. With more than twenty parameters, design custom classical or experimental shapes. Once prototyping of the font is done, each point and curve of a glyph can be easily modified. Explore, modify, compare, export with infinite variations.
(Okay, so technically this may not belong on a "reading list.") Duncan previously created The History of Rome podcast, which is one of my favorites. Revolutions is his new project, and it just launched. Get on board now.
This would be a great starting place for high-school or freshmen STEM curricula. As a bonus, it has this nice epigraph from Richard Hamming:
"In science, if you know what you are doing, you should not be doing it. In engineering, if you do not know what you are doing, you should not be doing it. Of course, you seldom, if ever, see either pure state."
I'm at the tail end of a doctoral program and going on the job market. This is good advice. What's disappointing is that this would have been equally good and applicable advice for people going on the job market back when I started grad school. The fact that we're five years (!!) down the road and we still have need of these sorts of "surviving in horrid job markets" pieces is bleak.
set show-all-if-ambiguous on
set completion-ignore-case on
This allows you to search through your history using the up and down arrows … i.e. type cd / and press the up arrow and you'll search through everything in your history that starts with cd /.
Wow. That is not an exaggeration at all: the most useful thing. I am so thrilled to finally be able to search my shell history the same way I can my Matlab history. I've been able to do this there for ages and my mind still hasn't caught up with not being able to do it in the shell.
If it's not clear to you why this is useful or why it pleases me, I don't think there's anything I can do to explain it. Sorry.
PS Anyone have first-hand experience with the fish shell? The autocompletions and inline, automatic syntax highlighting seem clever. I need to get around to giving it a try on one of my boxes.
The problem is not a lack of interest, but the lack of cheap, programmable hardware for teenagers to cut their teeth on. For typical youngsters, computers have become too complicated, too difficult to open (laptops especially) and alter their settings, and way too expensive to tinker with and risk voiding their warranty by frying their innards.
I don't see the connection between learning to code and having super-cheap hardware. Back when I was a kid learning to program I actually had to pay real money for a compiler. (Anyone else remember Borland Turbo C++?) Now you're tripping over free languages and environments to use, including many that run entirely through your browser so there's zero risk to your machine.
Honestly how many teens are going to go full-David Lightman and be doing serious enough hacking that their hardware is at risk? Is the goal to make sure teens have the opportunity to start learning to code before college, or to give them hardware to tinker with? Those are both fine goals. Being a software guy I'd put more weight on the former, but the important thing is that the way to accomplish either are completely different.
For starters, [your correspondant] plans to turn his existing Raspberry Pi into a media centre. By all accounts, Raspbmc—a Linux-based operating system derived from the XBox game-player’s media centre—is a pretty powerful media player. The first task, then, is to rig the Raspberry Pi up so it can pluck video off the internet, via a nearby WiFi router, and stream it direct to a TV in the living room. Finding out not whether, but just how well, this minimalist little computer manages such a feat will be all part of the fun.
I did this exact project about a month ago, and couldn't be more pleased with either the results or the fun of getting it to work. I still have to tinker with some things: the Vimeo plugin won't log into my account, and I need to build a case. Other than that, I wish I had done this a long time ago.
In a nutshell, the authors hope to get some insight into whether a myth is based on fact by seeing whether the social network of characters in the myth looks more like a real social network or like the social network in a work of deliberate fiction. For instance, the social networks of the Iliad and Beowulf look more like actual social networks than does the social network of Harry Potter. Real social networks follow a power law distribution more closely than do social networks in works of fiction.
I vaguely remember reading about some astronomer's using Homer's descriptions of constellations to pin down dates for various events in the Odyssey. Perhaps it was this PNAS paper by Baikouzis & Magnasco?
It seems however that an accurate historical account might have a suspicious social network, not because the events in it were made up but because they were filtered according to what the historian thought was important.
Indeed. Although I suspect this form of Narrative Bias would be less of a problem with Beowulf, the Illiad, etc., because the composers of those tales, and their audiences, had less exposure to the way fiction is "supposed" to be.
I would like to see someone do similar analysis for contemporary non-fiction. I prefer authors who tell a sprawling, tangled, less narratively driven story (Keay, Mann, Lewis, and Mukherjee come to mind) to one that fits a more conventional structure. It's difficult for me to accept a story that takes place in a high causal density environment and yet somehow only a couple of people have any agency.
Nate Silver apparently feels the same way:
When we construct these stories, we can lose the ability to think about the evidence critically. Elections typically present compelling narratives. Whatever you thought about the politics of Barack Obama or Sarah Palin or John McCain or Hillary Clinton in 2008, they had persuassive life stories: reported books on the campaign, like Game Change, read like tightly bestselling novels. — The Signal and the Noise, p. 59
Those are not the books I'm interested in.
NLP is very much not my area, but I can't help but wonder about automatically generating some sort of metric about this for a book. Count up how many proper names appear, and build a graph of them based on how closely together they are linked in the text. (That is, two names appearing often in the same sentence are more closely linked than two which appear in consecutive paragraph.) Perhaps simply looking at the histogram of name occurrence frequency might give you some preliminary ability to separate books into "realistic social structures" and "fiction-like social structures."