Category Archives: Web/Tech

New Tech Signals

New tech is usually adopted not for direct productivity gains, but to signal one is in fashion, one is technically capable, etc.  From a Post Oped Tuesday:

President Obama's proposed health-care reforms include investing $50 billion over five years to promote health information technology. Most notably, paper medical records would be replaced with linked electronic records to try to improve quality of care and lower medical costs. The recently enacted stimulus package included $20 billion for health IT. …

Yet while this sort of reform has popular support, there is little evidence that currently available computerized systems will improve care. … Large, randomized controlled studies — the "gold standard" of evidence — in this country and Britain have found that electronic records with computerized decision support did not result in a single improvement in any measure of quality of care for patients with chronic conditions including heart disease and asthma. …

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Shared AI Wins

Almost every new technology comes at first in a dizzying variety of styles, and then converges to what later seems the "obvious" configuration.  It is actually quite an eye-opener to go back and see old might-have-beens, from steam-powered cars to pneumatic tube mail to Memex to Englebart’s computer tools.  Techs that are only imagined, not implemented, take on the widest range of variations.  When actual implementations appear, people slowly figure out what works better, while network and other scale effects lock-in popular approaches.  As standards congeal, competitors focus on smaller variations around accepted approaches.  Those who stick with odd standards tend to be marginalized. 

Eliezer says standards barriers are why AIs would "foom" locally, with one AI quickly growing from so small no one notices, to so powerful it takes over the world:

I also don’t think this [scenario] is allowed: … knowledge and even skills are widely traded in this economy of AI systems. In concert, these AIs, and their human owners, and the economy that surrounds them, undergo a collective FOOM of self-improvement.  No local agent is capable of doing all this work, only the collective system. …  [The reason is that] trading cognitive content around between diverse AIs is more difficult and less likely than it might sound.  Consider the field of AI as it works today.  Is there any standard database of cognitive content that you buy off the shelf and plug into your amazing new system, whether it be a chessplayer or a new data-mining algorithm? …

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Drexler Blogs!

As I expect to cut back on blogging soon, I’m delighted to report that Eric Drexler now blogs, at Metamodern.com.  Of his first dozen posts, my favorite is on the promise of formal proof in math and digital systems: 

If this doesn’t seem important, it may be because we’re so accustomed to living with systems that have built on foundations made of mud, and thinking about a future likewise based on mud. All of us have difficulty imagining what could be developed in a world where computers didn’t crash, were guaranteed to be immune from virus attack, and could safely download code written by the devil himself, and where crucial pieces of software could be guaranteed to not leak data.  In this area, as everywhere in the realm of fundamental technological progress, the possibilities we can imagine will become the basis for possibilities we can’t imagine, and these, as they become real, will make possible yet more.

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Total Tech Wars

Eliezer Thursday:

Suppose … the first state to develop working researchers-on-a-chip, only has a one-day lead time. …  If there’s already full-scale nanotechnology around when this happens … in an hour … the ems may be able to upgrade themselves to a hundred thousand times human speed, … and in another hour, …  get the factor up to a million times human speed, and start working on intelligence enhancement. … One could, of course, voluntarily publish the improved-upload protocols to the world, and give everyone else a chance to join in.  But you’d have to trust that not a single one of your partners were holding back a trick that lets them run uploads at ten times your own maximum speed.

Carl Shulman Saturday and Monday:

I very much doubt that any U.S. or Chinese President who understood the issues would fail to nationalize a for-profit firm under those circumstances. … It’s also how a bunch of social democrats, or libertarians, or utilitarians, might run a project, knowing that a very likely alternative is the crack of a future dawn and burning the cosmic commons, with a lot of inequality in access to the future, and perhaps worse. Any state with a lead on bot development that can ensure the bot population is made up of nationalists or ideologues (who could monitor each other) could disarm the world’s dictatorships, solve collective action problems … [For] biological humans [to] retain their wealth as capital-holders in his scenario, ems must be obedient and controllable enough … But if such control is feasible, then a controlled em population being used to aggressively create a global singleton is also feasible.

Every new technology brings social disruption. While new techs (broadly conceived) tend to increase the total pie, some folks gain more than others, and some even lose overall.  The tech’s inventors may gain intellectual property, it may fit better with some forms of capital than others, and those who first foresee its implications may profit from compatible investments.  So any new tech can be framed as a conflict, between opponents in a race or war.

Every conflict can be framed as a total war. If you believe the other side is totally committed to total victory, that surrender is unacceptable, and that all interactions are zero-sum, you may conclude your side must never cooperate with them, nor tolerate much internal dissent or luxury.  All resources must be devoted to growing more resources and to fighting them in every possible way.

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A.I. Old-Timers

Artificial Intelligence pioneer Roger Schank at the Edge:

When reporters interviewed me in the 70’s and 80’s about the possibilities for Artificial Intelligence I would always say that we would have machines that are as smart as we are within my lifetime. It seemed a safe answer since no one could ever tell me I was wrong. But I no longer believe that will happen. One reason is that I am a lot older and we are barely closer to creating smart machines. 

I have not soured on AI. I still believe that we can create very intelligent machines. But I no longer believe that those machines will be like us….

What AI can and should build are intelligent special purpose entities. (We can call them Specialized Intelligences or SI’s.)  Smart computers will indeed be created. But they will arrive in the form of SI’s, ones that make lousy companions but know every shipping accident that ever happened and why (the shipping industry’s SI) or as an expert on sales (a business world SI.) … So AI in the traditional sense, will not happen in my lifetime nor in my grandson’s lifetime. Perhaps a new kind of machine intelligence will one day evolve and be smarter than us, but we are a really long way from that.

This was close to my view after nine years of A.I. research, at least regarding the non-upload A.I. path Schank has in mind.  I recently met Rodney Brooks and Peter Norvig at Google Foo Camp, and Rodney told me the two of them tried without much success to politely explain this standard "old-timers" view at a recent Singularity summit.  Greg Egan recently expressed himself more harshly:

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Self-Copying Factories

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Most important trends that change our world do not make the news.  Exhibit A:

Reprap RepRap is short for Replicating Rapid-prototyper. It is the practical self-copying 3D printer shown on the right – a self-replicating machine. This 3D printer builds the component up in layers of plastic. This technology already exists, but the cheapest commercial machine would cost you about 30,000 Euro. And it isn’t even designed so that it can make itself. So what the RepRap team are doing is to develop and to give away the designs for a much cheaper machine with the novel capability of being able to self-copy (material costs will be about 400 Euro). … We are distributing the RepRap machine at no cost to everyone under the GNU General Public Licence. … We hope to announce self-replication in 2008, though the machine that will do it – RepRap Version 1.0 “Darwin” – can be built now.

Apparently:

There are at least seven copies of the RepRap machine in the world that Olliver knows about.

Exhibit B is even more dramatic, if you know what you are seeing:

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Elevator Myths

In most elevators, at least in any built or installed since the early nineties, the door-close button doesn’t work. It is there mainly to make you think it works. … The escape hatch is always locked. By law, it’s bolted shut, from the outside. It’s there so that emergency personnel can get in, not so passengers can get out.

That is from a New Yorker article on elevators. 

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The Kind of Project To Watch

Blue Brain is an ambitious attempt to model brains.  It may fail, but my guess is that within a half century some project like it will success so spectacularly as to completely remake society, and turn well-placed pioneers into multi-trillionaires.  From Seed:

In the basement of a university in Lausanne, Switzerland sit four black boxes, each about the size of a refrigerator, and filled with 2,000 IBM microchips stacked in repeating rows. Together they form the processing core of a machine that can handle 22.8 trillion operations per second. … This is Blue Brain. …

When he launched the project in the summer of 2005, as a joint venture with IBM, there was still no shortage of skepticism. Scientists criticized the project as an expensive pipedream, a blatant waste of money and talent. … The first phase of the project – “the feasibility phase” – is coming to a close. The skeptics, for the most part, have been proven wrong. It took less than two years for the Blue Brain supercomputer to accurately simulate a neocortical column, which is a tiny slice of brain containing approximately 10,000 neurons, with about 30 million synaptic connections between them. …

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Nanotech Views Value Driven

In another experiment conducted with the Washington-based Project on Emerging Nanotechnologies at the Woodrow Wilson International Center for Scholars, Kahan found that when volunteers heard about the risks of nanotechnology from different experts, they gravitated toward the views of experts who seemed to share their personal values — individualists followed the lead of experts who appeared to be individualists, while people who believed in hierarchy were most likely to be influenced by experts who espoused similar views. Once volunteers decided which experts were most like them, it did not make a difference whether the experts said nanotechnology was risky or safe — either way, the volunteers agreed with them. … When people clash on hot-button issues, their disagreements may have more to do with clashing values than facts. One person may conclude nanotechnology is dangerous while another person concludes it is safe, but neither realizes their conclusions are being driven by underlying values that have nothing to do with nanotechnology.

That is from the Post.  Of course regarding policy conclusions, all else equal it does make sense to listen more to people who share your values.   But it seems a shame if your views about facts contain nothing more. 

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Merger Decision Markets

HP began to explore prediction markets in 1996, but did not even consider applying them to the 2002 HP-Compaq merger.  Similarly, Yahoo and Microsoft are two of the companies mentioned most often as being involved in prediction markets (along with their main competitor Google), but I’ll bet none are considering the by-far-most-valuable markets they could create, on their just-announced proposed merger.  Decision markets could say whether this merger is good for shareholders, by estimating the combined stock price given a merger, and given no merger.  Similarly, decision markets could say whether this merger is good for these firms’ customers, by estimating the price and/or quantity of web ads given a merger, and given no merger.  This might help convince regulators to approve the merger.   From the Post:

The deal also will face scrutiny from antitrust regulators, who will hear from consumer groups concerned that so much power — and consumer information — would be concentrated in one company.   However, some said that allowing the acquisition would enhance competition by creating a credible competitor to Google.

"You want to encourage competition with Google," said Ben Scott, policy director at Free Press, a public-interest firm. "But you don’t want to bend over backward to do that and end up with a duopoly that ignores the anticompetitive implications of Microsoft integrating Yahoo products into Windows."

The Justice Department and House and Senate committees are likely to review the transaction, officials said. "We will need to scrutinize the deal carefully to insure that it will not cause any harm to the competitiveness of what has been a vibrant high-tech marketplace," said Herb Kohl (D-Wis.), chairman of the Senate Judiciary Committee’s subcommittee on antitrust, competition policy and consumer rights.

The subcommittee, which recently examined Google’s proposed takeover of DoubleClick, would also look at whether a Microsoft-Yahoo deal would violate the privacy rights of Internet users.

My main doubt here is whether ad price and quantity are good enough measures of the merger’s social benefits – what other outcomes could such markets estimate, to speak more clearly?  And this is a very clear demonstration that these companies are just not serious about finding the highest value applications of prediction markets.

Added: More comments at the cross -posting at Midas Oracle.   

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