Tag Archives: Web/Tech

Is Paper Low Status?

“Virginia has a lot of electronic voting and in general has an election system where it’s very hard to get recounts,” says Dill. “So I might worry about Virginia, depending on how close it is.” … It’s a lot easier to modify electronic records than to modify paper records which is why banking and a lot of other critical activities like that still rely on paper when there’s an ultimate disaster and electronic records are lost or corrupted. (more)

When I voted this morning in Virginia I noticed a line of 6-8 people waiting to use the electronic voting machines, but one could vote immediately on paper. Yet paper voting is less corruptible. I asked Alex Tabarrok and he said he puzzled over the same thing when he voted: why is paper voting so unpopular?

A fb comment noted that it is mostly old folks voting on paper. And that was true at my place as well. Which leads me to suggest that this is a status effect – people stand in line to vote less securely in order to signal that they aren’t old folks scared by or incompetent at electronics. Yes, it seems surprising that people are willing to spend an extra few minutes just to look hip to strangers. But what other explanation is there?

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Can Humans Be The FORTRAN Of Creatures?

It is one of the most fundamental questions in the social and human sciences: how culturally plastic are people? Many anthropologists have long championed the view that humans are very plastic; with matching upbringing people can be made to behave a very wide range of ways, and to want a very wide range of things. Others say human nature is far more constrained, and collect descriptions of “human universals” (See Brown’s 1991 book.)

This dispute has been politically potent. For example, in gender relations some have said that social institutions should reflect the fact that men and women have certain innate differences, while others say that we can pick most any way we want the genders to relate, and then teach our children to be like that.

But let’s set those issues aside, look to the distant future, and ask: do varying degrees of human cultural plasticity make different predictions about the future?

The easiest predictions are at the extremes. For example, if human nature is extremely rigid, and hard to change, then humans will most likely just go extinct. Eventually environments will change, and other creature will evolve or be designed that are better adapted to those new environments. Humans won’t adapt very well, by assumption, so they lose.

At the other extreme, if human nature is very plastic, then it will adapt to most changes, and change to embody whatever innovations are required for such adaptation. But then there would be very little left of us by the end; our descendants would become whatever any initially very plastic species would have become in such an environment.

So if you want some distinctive human features to last, you’ll have to hope for an intermediate level of plasticity. Human nature has to be flexible enough to not be out competed by a more flexible design platform, but inflexible enough to retain some of its original features.

For example, consider the programming language FORTRAN:

Originally developed by IBM … in the 1950s for scientific and engineering applications, Fortran came to dominate this area of programming early on and has been in continual use for over half a century in computationally intensive areas such as numerical weather prediction, finite element analysis, computational fluid dynamics, computational physics and computational chemistry. It is one of the most popular languages in the area of high-performance computing and is the language used for programs that benchmark and rank the world’s fastest supercomputers. (more)

FORTRAN isn’t the best possible programming language, but because it was first, it collected a powerful installed base well adapted to it. It has been flexible enough to stick around, but it isn’t infinitely flexible — one can very much recognize early FORTRAN features in current versions.

Similarly, humans have the advantage of being the first species to master culture in a powerful way. We have slowly accumulated many powerful innovations we call civilization, and we’ve invested a lot in adapting those innovations to the particulars of humanity. This installed based of the ways civilization is matched well to humans gives us an advantage over creatures with a substantially differing design.

If humans are flexible enough, but not too flexible, we may become the FORTRAN of future minds, clunky but still useful enough to keep around, noticeably retaining many of its original features.

I should note that some hope to preserve humanity by ending decentralized competition; they hope a central power will ensure than human features survive regardless of their local efficiency in future environments. I have a lot of concerns about that, but yes it should be included on the list of possibilities.

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Old Minds Are Fragile

Consider three design problems:

  • Case #1: First, you are asked to modify a stock car, making it into a truck to haul stuff. After you do that, you are asked to create a race car. Which would you rather start from for this second task, another stock car, or the stock car that you turned into a truck?
  • Case #2: A species of beetle lives in a varied and changing environment, and so has a rather simple and basic design. Some of these beetles invade a different and more stable environment, and acquire adaptations specific to that environment. A third rather different but also stable environment opens up adjacent to both previous environments. Which beetle type’s descendants will likely fill this third environment?
  • Case #3: Over the last decade a group wrote software to do a certain task (e.g., print driver, web server, spreadsheet, etc.) This design of this software was matched to certain features of the problem environment, such as hardware, network speeds, etc. Today there is a need for software to do a similar task, except that the problem environment has changed. To write this new software, would you have your team modify this previous software, or start a new system mostly from scratch?

In all these cases, one makes a system to function in a given environment, and can either modify a complex system adapted to a different environment, or “start over” via modifying a simpler system less adapted to any specific environment. In general, the more different is the new environment from the old, the better it is to start over. Old  systems tend to be rigid, which makes them fragile, in that they break if you bend them too far.

This suggests that designed systems tend to get irreversibly fragile as they adapt to specific environments. When context changes greatly, it is usually easier to build new systems from “scratch,” than to un-adapt systems designed for other contexts. Software tends to “rot“, for example.

An empirical prediction here is that species occupying highly variable environments tend to have more descendant species in other environments, compared to species occupying less variable environments. I don’t know if this has been tested. It fits with the Innovator’s Dilemma though, where firms who serve the low end of a product line with simpler techs tend to creep up and displace those serving the high end; high end products tend to be more complex.

Today I’m focused on this being bad news for the feasibility of immortality, at least for human-like creatures. You see, our minds seem designed to adapt to the environment in which we grow up, via youthful plasticity transitioning to elderly rigidity. For example, we are great at learning languages when young, and terrible when old. We are similarly receptive when young to new ways to categorize and conceive of things, but once we have often used particular ways, we find it harder to understand and use alternatives.

The brains of most animals peak in functionality during their key reproductive years, and do worse both before and after. Short lived animals peak sooner than long lived animals. Some of the early rise is due to learning, and some of later decline is due to the decline of individual cells and connections. Some of this pattern may even be due to an explicit plan to turn up some dials on plasticity early on, and then turn down those dials later. But I think another important part of this rise and fall is due to a general robust tendency for adapted systems to slide from plasticity to rigidity.

Thus even if we succeed in creating emulations of whole human brains, “ems” which can use backups, body swaps, etc. to avoid bodily death and decay, we should expect such ems to decay by getting mentally rigid with subjective age. Even if we do not emulate any decline in individual cell and connection performance, nor any age-specific general plasticity dial settings, the mind itself may well decay with subjective experience, because such decay is just intrinsic to mind design.

Now in software design one can often slow a slide to rigidity by refactoring code, such as by looking for better abstractions to achieve modularity. But the brain probably already has some analogues to refractoring, such as in its ways to reorganize concepts. And even with large refactoring efforts, most designed software eventually gets rigid, so that when environments change enough such software is replaced wholesale by new systems built from scratch.

Similarly, em workers who start out subjectively young, and then learn how to work in a stable environment, may become increasingly productive in that environment, even after thousands of years of subjective experience. But when a new quite different work environment appears, one can probably gain more work productivity by training subjectively young ems for it, rather than trying to change ems who had spend thousands of subjective years adapting to a very different environment.

Today most houses and cars are in principle immortal, in the sense that enough maintenance can keep them functioning indefinitely. Yet most houses and cars are not immortal in practice, because those maintenance costs keep rising to the point where it is cheaper to build new houses and cars. Similarly it might be possible to keep very old ems around, even when they have become much less productive because relevant environments have changed. Someone, however, would have to pay that cost, relative to the option of using more productive younger ems. And as with houses and cars today, maybe few will pay.

If you personally hope to become an em with an especially long productive subjective life, it is probably important to stay general and flexible for as long as you can. Prefer to acquire habits and insights that are widely applicable, and whose value is likely to long continue. Prefer to write, deal with people, and manage complexity, rather than learning the detailed layout of a city or how best to write in a particular new programming language.

Eventually we may find mind designs with a much weaker tendency toward rigidity with age. And we may find ways to transfer some important elements of once-human minds, such as their memory and personality, into this alternative framework. But even then there should be some aging. And it gets even less clear if you’d want to think of such a changed creature as you.

Even more eventually, the universe should get a lot more stable, and with it the environments where minds function. Then there will be a lot more scope for very long lived human-like minds. If there are any human-like minds left at that point.

Added: Stem cells fit this; bodies usually make cells designed for specific places from general simpler stem cells, not by changing other specific cells.

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Religion Gets Bad Rap

Indonesian police say a civil servant who posted “God does not exist” on Facebook faces a maximum penalty of five years behind bars for blasphemy. … He was attacked by a mob on his way to work. (more)

I’m an atheist, and dislike mistreatment of atheists. But I also have to admit religion often gets a bad rap. For example, I’ve been reading more science fiction than usual lately, some old and some new. I notice that they almost all include the trope of religious folks trying hard to hold back progress, often via terrorism. Perhaps this was once fair, but it doesn’t seem remotely so today. (And I don’t see it listed among other science fiction tropes.)

When religion helped turn foragers into farmers, it paid a lot of attention to sex. So religious folks still care a lot about sex, and have resisted sex-related techs, such as birth control, abortion, and IVF. But those techs are pretty old today, and only abortion remains strongly opposed. Yeah there are stem cell treatments, but that is a pretty tiny fraction of medicine.

A science fiction author from fifty years ago might have imagined strong religious oppositions to VCRs or the internet, because they aided porn. Or to cell phones with cameras because they allow sexting. Or to all sorts of “unnatural” medical techs. But overall, religious folks today seem just as pro-tech as others.

That doesn’t mean we don’t erect social barriers to new techs. But instead of being religious, most barriers today are regulatory and risk-based. As we have grown rich and eager to regulate each other, we have become more risk-averse and made it harder to introduce new disruptive techs. For example, computer-driven car tech is basically here and ready to go, but it will be a long time before we allow it. Same for automated flight and medical diagnosis,

Alas science fiction authors are reluctant to blame over-regulators as their anti-tech villain. Religion makes a safer target – most sf readers like regulation, but few are religious. Also, we tend to overestimate the importance of doctrine and dogma, relative to habits of behavior. Most religious dogma is silly and doesn’t meet our usual intellectual standards. But it also doesn’t much influence behavior. In fact, religious folks tend to have exemplary behavior overall. They work hard, are married and healthy, avoid crime, deal fair, help associates, etc. While it may seem plausible that people with crazy beliefs would do crazy harmful things, the opposite seems to apply in this case.

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Over-Regulated Flight

Over-regulation is delaying the automation of flight:

Time was when a uniformed man would close a metal gate, throw a switch, and intone, “Second floor- men’s clothing, linens, power tools …” and the carload of people would glide upward. Now each passenger handles the job with a punch of a button and not a hint of white-knuckled hesitation. … And back in the day, every train had an “engineer” in the cab of the locomotive. Then robo-trains took over intra-airport service, and in the past decade they have appeared on subway lines in Copenhagen, Detroit, Tokyo, and other cities. …

Automation … runs oceangoing freighters, the crews of which have shrunk by an order of magnitude in living memory. … Today, the U.S. military trains twice as many ground operators for its unmanned aerial vehicles (UAVs) as pilots for its military jets. Its UAVs started off by flying surveillance millions, then took on ground attack; now they are bering readied to move cargo and evacuate wounded soldiers.

In the sphere of commercial flight, too, automation has thinned the cockpit crew from five to just the pilot and copilot, whose jobs it has greatly simplified. Do we even need those two? Many aviation experts think not. ….

Still, UAVs have yet to find a place in even the humblest parts of the aviation business – surveying traffic jams, say, or snooping on celebrity weddings. Such work has not yet been approved for routine purposes, even when the aircraft is small and controlled by a human on the ground. …

Technical problems are hardly the entire explanation. The military has proved this time and again. … For nearly two decades, automatic landing systems have been able to drop and stop a jet on the fog shrouded deck of an aircraft carrier. … “There’s no harder job for a pilot than landing on an aircraft carrier.” …

Pilotless commercial flight is overdue … Civilian UAVs could easily and profitablyt be deployed to survey infrastructure and carry cargo. … Already, … an airliner’s software typically takes over flight secods after takeoff, handles the landing – and most of what happens in between. The pilot just “babysits.” … Global Hawk .. is able to fly itself home and land on its own if it loses its satellite link with its ground station. ..

As significant as the technical hurdles are, however, by far the biggest impediment to pilotless flight lies in the mind. People who otherwise retain a friendly outlook toward futuristic technologies are quick to declare that they’d never board a plan run by software. (more)

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Office By Combo Auction

Twenty years ago when I worked at NASA Ames, our group moved to a new office building. We put up a map of the new offices, and invited folks to put their name on a office they liked. People were ranked by seniority, and a higher ranked person could bump a lower ranked one from an office. People changed their office assignments based on what office they liked and who they wanted to be near until changes slowed to a trickle. And that was our new office arrangement.

Now imagine a much more elaborate system. Imagine that all the workers in your office are moving to a new building, requiring a new assignment of floor space to offices, conference rooms, copier/printer rooms, lunch rooms, hallways, etc. Now imagine that this assignment is done by combinatorial auction.

That is, imagine each person in your office has a budget of cash or bidding points, and submits bids saying how much he or she would pay for various office scenarios. Such bids can express values for:

  1. Whether one sits in an open cubicle or closed room, and how many officemates.
  2. Office features like size, windows, carpet, lights, climate controls, elevation, etc.
  3. Distance of office from entrances, bathrooms, conference rooms, lunch rooms, etc.
  4. Distance of office (in time or space) from the offices of other particular associates.
  5. Utilities like wired internet, big power plugs, or paper mail delivery.
  6. Local policies like if allow loud conversations, or food eaten at desk.

Given such bids, a computer could search for the office assignment that achieves the highest total bid value. Such an assignment might say:

  1. Who sits in which office.
  2. Which rooms are assigned as offices, conference rooms, lunch, printers, etc.
  3. If changes can be made, each office’s carpet, lights, windows, climate controls, etc.
  4. If changes can be made, what internet, power, etc. are supplied to each office.
  5. If partitions can be moved, the number and size of rooms.
  6. For each area, policies on loud conversations, food at desk, etc.

When choices like differing carpets vary in cost, cost functions could let one seek the assignment that maximized the total bid value minus costs. Such cost functions could express scale economies, such as it being cheaper to give all rooms the same carpets. When management cares about office arrangements beyond satisfying office workers, management preferences could be expressed in management bids, or in constraints on the final arrangement.

To save workers from having to express too many bid details, the process can be iterative, always showing a tentative assignment given the last round of bids, so bid elaboration efforts can focus on aspects that make a difference. (Bids themselves would stay secret.) Bidding assistant software might also infer preferences from user ratings of past or hypothetical offices.

Now even with a perfect choice of who gets what bidding budget, this process isn’t at all guaranteed to give an optimal office arrangement. For example, workers would likely underbid for shared resources like conference rooms; they’d want them but rather that others pay for them. There is now a whole academic field of “mechanism design” that studies the general problem of choosing rules for how such “direct revelation” bids are expressed, how they are updated across rounds, who wins what in the end, and who pays how much.

And yet, even the simple process described above would get a lot of things right, things that most offices get pretty wrong. After all, workers would actually get offices that had a consistent relation to their office preferences. Which makes it a shame that we don’t do this sort of thing more.

Yes, I realize that such computer-based solutions have not been feasible until recently, that there is work to be done to make them easy, and that innovation takes time. I also grant that bosses may see this as threatening their power, and that we may have social norms against using “money” in such a “personal” context (even in business!).

I also don’t want to give the impression that combinatorial auctions are my idea. I worked on them during ’93-’95 as a grad student under John Ledyard and David Porter. There is now a whole academic field of combinatorial auctions. See this book, its intro, and also articles on applications to environmental offsets, spectrum, airport landing slotsland consolidation, purchasing, and procurement of trucking and school lunches. See also a sf story.

And yes, assigning offices is far from the biggest problem we face in this world. This post mainly uses it as a vivid example to introduce the concept of combinatorial auctions. I’ll elaborate on a bigger application tomorrow.

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Kurzweil Rejects Ems

I posted recently on Allen & Greaves criticizing “the whole brain emulation argument that we can simulate a brain without understanding it.” Ray Kurzweil responds that while he is far more optimistic on AI progress, he doesn’t believe in emulation without understanding either:

Allen mischaracterizes my proposal to learn about the brain from scanning the brain to understand its fine structure. It is not my proposal to simulate an entire brain “bottom up” without understanding the information processing functions. We do need to understand in detail how individual types of neurons work, and then gather information about how functional modules are connected. The functional methods that are derived from this type of analysis can then guide the development of intelligent systems. Basically, we are looking for biologically inspired methods that can accelerate work in AI.

It makes sense that since Kurzweil is so optimistic about rapid progress in so many technologies, such as life extension, he’d be optimistic about rapid progress in modeling the higher level organization of brains. Ems seem more likely to pessimists like myself — although we think emulation should be possible with far less than quantum chemistry detail, since the brain is a robust signal processing system, we estimate that the rate of progress to date suggests a long slow road to understanding brain organization.

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Trends Worth Tracking

Given our usual way of doing economic analysis, the question of which institutions will most increase economic welfare rarely depends much on the exact values of the sorts of parameters social scientists and the media track with such enthusiasm and concern. (more)

I’ve complained before about useless trend tracking, but I don’t mean to suggest that all trends are uninteresting. Some trends tell us about how well our institutions are functioning. For example:

Accounting statements are getting less and less representative of what’s really going on inside of companies. … The finance industry showed a huge surge in the deviation … from 1981-82, coincident with two major deregulatory acts that sparked the beginnings of that other big mortgage debacle, the Savings and Loan Crisis. The deviation … reached a peak in 1988 and then decreased starting in 1993 at the tail end of the S&L fraud wave, not matching its 1988 level until … 2008.

Neither manufacturing nor IT showed the huge increase and decline of the deviation … that finance experienced in the 1980s and early 1990s, further validating the measure since neither industry experienced major fraud scandals during that period. The deviation for IT streaked up between 1998-2002 exactly during the dotcom bubble. (more; HT Tyler, Thoma)

Now that’s a trend to make me stand up and take notice! Similar parameters where I’d want to watch trends:

  • Marriage cheating and cuckoldry
  • Biased scientific papers, referee agreement
  • Wrongful convictions, faked evidence
  • Biased rulings by sports referees

These sort of trends track the health of specific institutions. When such an institution starts failing, we should be especially eager to reform it, using economic theory to suggest which reforms might be most effective.

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Adapt Or Start Over?

Sean Carroll has doubts on nanotech:

Living organisms … can, in a wide variety of circumstances, repair themselves. … Which brings up something that has always worried me about nanotechnology … tiny machines that have been heroically constructed … just seem so darn fragile. … surely one has to worry about the little buggers breaking down. … So what you really want is microscopic machinery that is robust enough to repair itself. Fortunately, this problem has already been solved at least once: it’s called “life.” … This is why my utterly underinformed opinion is that the biggest advances will come not from nanotechnology, but from synthetic biology. (more)

There are four ways to deal with system damage: 1) reliability, 2) redundancy, 3) repair, and 4) replacement. Some designs are less prone to damage; with redundant parts all must fail for a system to fail; sometimes damage can be undone; and the faster a system is replaced the less robust it needs to be. Both artificial and natural systems use all four approaches. Artificial systems often have especially reliable parts, and so rely less on repair. And since they can coordinate better with outside systems, when they do repair they rely more on outside assistance – they have less need for self-repair. So I don’t see artificial systems as failing especially at self-repair.

Nevertheless, Carroll’s basic concern has merit. It can be hard for new approaches to compete with complex tightly integrated approaches that have been adapted over a long time. We humans have succeeded in displacing natural systems with artificial systems in many situations, but in other cases we do better to inherit and adapt natural systems than to try to redesign from scratch. For example, if you hear a song you like, it usually makes more sense to just copy it, and perhaps adapt it to your preferred instruments or style, than to design a whole new song like it.  I’ve argued that we are not up to the task of designing cities from scratch, and that the first human-level artificial intelligences will use better parts but mostly copy structure from biological brains.

So what determines when we can successfully redesign from scratch, and when we are better off copying and adapting existing systems? Redesign makes more sense when we have access to far better parts, and when system designs are relatively simple, making system architecture especially important, especially if we can design better architecture. In contrast, it makes more sense to inherit and adapt existing systems when a few key architectural choices matter less, compared to system “content” (i.e., all the rest). As with songs, cities, and minds. I don’t have a strong opinion about which case applies best for nanotech.

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Will We Ban Tone Readers?

Humans communicate through many channels, including words, tone of voice, body position, facial expressions, etc. An “innocent” view is that these channels say similar compatible things; added channels mainly help us to say more things faster. A “hypocrisy” view, however, is that we say more socially-acceptable things via words, which can be more easily quoted, and via other channels we more say things we’d rather were not quoted, things often in conflict with our words.

These contrasting views suggest differing predictions about how we will react to new rapidly-improving techs for reading face/body/voice tones. Such techs watch and listen to the people around us, and tell us explicitly what their face/body/voice tones are saying. (Quotes from an article on such tech below.)

The innocent view suggests that we will welcome such techs as ways to help us read each other more clearly, helping especially those handicapped in reading such signals. The hypocrisy view, in contrast, suggests that we will resist and regulate such tech, to preserve familiar capacities for and habits of hypocrisy.

Many familiar regulations can be seen as attempts to preserve our habits of hypocrisy. For example, audio recording techs threatened to make our words reliably quotable, and our tone of voice as well, making it harder to say different things in private than we say in public. So we prohibited recording people’s voice without their permission. Similarly, new techs allowing cheap video recording of police activities threaten to expose deviations between how police often behave and how we say they are supposed to behave. So we are starting to ban them .(We may have police internal affairs groups report to police chiefs for similar reasons.)

Older examples are laws against blackmail and gambling, and our reluctance to enforce most long term promises. Blackmail threatens to punish and thus discourage activities we like, even though we denounce them, and challenges to bet show that we like to say things we don’t believe enough to support with a bet. Most long term promises are based on ideals we espouse but don’t actually want to act on.

I lean toward the hypocrisy view of human communication. Thus I suspect expression readers will be widely banned, especially recording or publishing their outputs, as an “invasion of privacy.” Though we may make sure the wording and/or enforcement of such laws is weak enough to allow their common use on ordinary people by firms and governments.

Anyone disagree? What odds will you give?

That article on expression reader tech: Continue reading "Will We Ban Tone Readers?" »

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