Download madsen-lipo-bentley-saa2008-poster.pdf

and will be published soon along with our entire poster session as an issue of the online Journal of Evolutionary and Historical Sciences.  I’ll talk more about this soon, but this week is incredibly busy and I wanted to get at least one link up for the paper before I forget.

I haven’t written much here since late December, but only because life has reached a fever pitch again, and the brief times I have free away from a full schedule need to be devoted to research and my dissertation, not idle contemplation for my website. But we’re in the thick swamp of an election season, unseasonably early of course, and I haven’t written anything about the candidates, the primaries, the debates, as I did for much of 2004. I can’t promise to get back to regular posting before Super Tuesday, but I hope to soon thereafter. Or as soon as I can get my two projects more firmly underway (one paper, one poster) for the SAA (Society for American Archaeology) meetings in late March in Vancouver. Both are co-authored with Alex Bentley and Carl Lipo, and we’re working on the statistical consequences of expressing formal models of cultural transmission within realistic social networks.

For those unfamiliar with cultural transmission, this is the observation that humans are not born with a hard-coded set of cultural behaviors (in the sense of genetically transmitted) but learn, over the course of child development and throughout life, ways of behaving and believing and thinking through interaction with others in our social groups. In a formal sense, cultural transmission is modeled mathematically through analogues of haploid population genetics models (Wright-Fisher and Moran processes), replicator dynamics and allied models from evolutionary game theory, and the contact and voter models in the study of “interacting particle systems” or spatial stochastic processes by probability theorists and statistical physicists. An open question, whose likely answer is “yes,” is that these methods of modeling cultural learning and transmission are formally equivalent, given appropriate variations of population structure and the focus on deterministic versus stochastic models. But more of that in future posts, hopefully.

Basically, I’m working with some collaborators studying models of social learning and communication, for predictive ensemble or spatial statistical “signatures” in cultural data which are mapped spatially and dated temporally. A “signature” would be a unique pattern of statistical properties which tells us how a given population was structured (in terms of social networks) given the results of how cultural information flowed within the population, and came to be reflected in material objects or artifacts. An example would be a model in which we learn about, and adopt, preferences for songs and music from our social network of friends, but in an unbiased fashion — we occasionally adopt the preferences of a colleague or associate. What statistical properties does this local process of imitation have, when projected into a “global” perspective — statistical patterns within a population, spatial patterns in kinds of data we can map and chart?

Of course, we all know that the model I just described is pretty simplistic. Nobody “just copies” their friends, let alone doing so without any filters, biases, and on a strict “coin flip” or probabilistic basis. But it turns out it sure can look that way when you aggregate the results of many people imitating, choosing, learning, and adopting ideas. So this kind of model is a good “null hypothesis” for a simplistic kind of cultural communication — anything more realistic will have to depart from this simple random model in striking, hopefully unique ways.

Being able to find unique, predictive patterns from more complex models of cultural learning and communication is possible, but not guaranteed — it is easily possible (maybe even likely) that several different kinds of social situations could lead to the same overall patterns at a local, regional, or even global level. We call this problem “equifinality” — the data we have are insufficient to distinguish between several possible processes, so given our models and data, each process is “equally likely” to have caused the observed pattern.

This type of research is what I’ve been engaged in for a long time — at least since 1995, with conference papers, publications, and Carl Lipo’s dissertation research covering some of the results. Now I’m extending our previous work and learning a lot of math, probability, and population genetics in the process. It’s fascinating stuff, but in addition to the job at GridNetworks the work keeps me pretty busy.

This is all by way of explanation for my longish absences from writing something here. I hope to remedy that, as I said, but there’s some serious work between now and then.

San Francisco in the middle sixties was a very special time and place to be a part of. Maybe it meant something. Maybe not, in the long run, but no explanation, no mix of words or music or memories can touch that sense of knowing that you were there and alive in that corner of time and the world….There was a fantastic universal sense that whatever we were doing was right, that we were winning. And that, I think, was the handle – that sense of inevitable victory over the forces of Old and Evil. Not in any mean or military sense; we didn’t need that. Our energy would simply prevail. There was no point in fighting – on our side or theirs. We had all the momentum; we were riding the crest of a high and beautiful wave. So now, less than five years later, you can go up on a steep hill in Las Vegas and look West, and with the right kind of eyes you can almost see the high-water mark – the place where the wave finally broke and rolled back.

Hunter S. Thompson, “Fear and Loathing in Las Vegas”

Today is the eleventh anniversary of Carl Sagan’s passing, and like last year many people are writing today to commemorate Sagan and contribute to the second annual Carl Sagan Blog-a-Thon. This is the first of several from me, and one that I’ve been thinking about for awhile.

Not too long ago a friend asked why I still was enamored of the old Cosmos episodes, and periodically went back to watch them. I had to think about it a great deal, because ultimately my friend was right: they’re outdated, and even in their depiction of history are occasionally inaccurate. I keep coming back to an answer, however, which makes me think about Hunter S. Thompson and the quote above.

At least for me, Carl Sagan and his work with Cosmos and planetary exploration represent the “high-water mark” for American scientific culture. Cosmos is redolent with the sense of knowing that we lived in a time when science and democracy and rationalism were winning out over superstition and fear. As Thompson says, not in any military sense, but simply that a particular sensibility would ultimately prevail.

It has not. Not long after Sagan completed the Cosmos series, the Moral Majority (and its descendants, the modern Religious Right) became a major force in American politics, and so-called “postmodernism” became a major force in American scholarship. Today, less than 30 years later, the prestige of science and rationalism are at their lowest in my lifetime. Watching Cosmos, and reading Sagan’s writings are the equivalent, in my view, of seeing the “high water mark” — the place where the wave of mid-20th century secular rationalism finally broke and rolled back.

This isn’t entirely a bad thing. A bit of skepticism is always a good thing. Feyerabend and Arthur Fine bring to the philosophy of science a needed skepticism about the uniqueness of “scientific method” and most of us now view science as a socially conditioned process. But still one whose essential feature is self-correction across the efforts of many. We may have no solid ground to claim that anything we learn is really true, in any ultimate sense, but Popperian falsification still seems to work: we can know when we’re wrong.

But the skepticism of the postmodern critique of “scientism” has crept into policy-making and politics. The shameless manipulation of science and expert testimony under recent (and especially the current) Administration is shocking, and it’s not clear how to reverse this trend. A whole generation of Americans is growing up without much significant training in math and science, which are increasingly viewed as specialities which it’s OK for most people to skip because they’re “not interested in that sort of thing.”

The elevation of personal choice as the sole arbiter of value is a difficult topic in a capitalist democracy (see Michael Sandel on this topic, among other political philosophers), but one thing is clear: we face choices as a country that virtually require us to understand the issues. And it is far from clear that the electorate does understand the evidence on global warming, or peak oil, or biodiversity, or genetic research, to name just a few topics.

So to some extent, I continue to remember Sagan and watch Cosmos as a reminder of what we need to regain, of what we’ve lost in the past 30 years.

My personal experience is that it’s broken in some significant ways. I’m not that concerned, given the scientific and mathematical programming I do, with Cocoa pipelines and graphics, but overall my fairly simple numerical simulations using RepastJ 3.1 run several orders of magnitude slower in Leopard than Tiger, given Log4J text logging in debug mode.

You can argue, as Sutton probably would, that nothing fundamental is wrong and that I shouldn’t judge “brokenness” by the performance of text I/O, but hey, let’s face it, if you can’t write ASCII text to a bloody text file before protons decay and the sun burns out, then Java 5 is horribly broken in Leopard.

Which sucks, because although Gruber doesn’t see any “significant” software being written in Java for the Mac, there sure are a lot of us using IntelliJ IDEA doing Java development on Intel Macs, and the compile and test cycle just got a lot worse. A *lot* worse.

Leopard was late, and compromises needed to be made, and sure Apple took a lot of flak for announcing the delay, but this OS needed more time in the oven.

UPDATE: This turns out to be the Quartz rendering pipeline switch, and is “fixed” by passing the following to the JVM as command line arguments:

-Dapple.awt.graphics.UseQuartz=true

My guess is that Apple might release a separate download to restore the Quartz pipeline as the default, but in the meantime this seems work. I would like to thank Pratik from Apple, who saw my post a couple of minutes ago and pointed me in the right direction.

Maybe Gruber and Sutton are right, it’s possible we all need to chill out a bit. This here upgrade might turn out to be alright, though I did follow Siracusa’s lead and turn off the pseudo-3D dock using the “no-glass” attribute — I have a zillion program icons and they’re incredibly hard to distinguish at very small sizes in pseudo-3D. Siracusa is also right, it’s almost impossible to read the very-similar grey “stacks” folder icons when my dock is so small….

Frankly, Americans on both sides of the aisle have reasons to dread the latter two events.  With respect to the politically motivated among Americans (however large that population truly is), neither side will actually get anything they want, and much noise and ink will be deployed in trying to convince us otherwise.  One side will not see the US signal a willing end to the Iraq War and an admission that the policy was a mistake, whether deliberate or not — because as is apparent, this is what the "anti-war left" wants.  And the other side will not see a country that "sees the light" and finally agrees unanimously that everything in the last six years is more than justified by the gravity of the threat we face — again, as everybody in the country knows, this is what the "conservative" and traditionalists in this country want.  I leave aside the less salient but still significant aspects of political opposition in this country because, honestly, these are the big issues of the day.  As with Vietnam, the nation today is split over different models of what "patriotism" requires of citizens in our current situation.

I use the term "requires" deliberately, because I believe that we’re not talking enough about what patriotism is, and thus what might be required
of citizens who think of themselves as "patriotic Americans."  Each
side seems to think the other is unpatriotic (or worse).  Either
because one group seems to blindly support a President and his policies
despite the evidence of bad decision-making, outright lying,
power-hunger, and downright incompetence, or because the other side
appears to value abstract arguments more than "standing with your
people," "unity in time of war," and "looking after our own." 

Given how long it took me to finish this post I lost the reference, but
in the LA Times recently a veteran was interviewed who stated flat out
that opposition in war time was unpatriotic — his point was that this is not the time for discussion and opposition.  I think this sums up one model of patriotism quite nicely:  we line up behind our leaders and stand united.
From the perspective of a serving soldier or a veteran of war, this
makes sense.  It makes even more sense after watching Ken Burns’s
masterful documentary The War this past week, for loyalty is
precisely what is important to those serving in war.  Key to this view
is loyalty to country, the loyalty of one’s peers, and the idea that
loyalty exists at home to the cause for which one is fighting.

But there is another patriotism, equally strong. A loyalty to principles, foremost among them the principles along which our country was founded.
And regardless of what fear-mongering TV and radio pundits want us to
think, those principles do not include blind loyalty, whether in time
of war or not.  Democracy virtually requires an exchange of
views, not a lining-up behind a powerful personality.  Think about how
our country was founded:  in opposition to monarchy, in opposition to
royal power, in opposition to the personal rule of one man or rule by a
small aristocracy.  And yet we are told that questioning those trends
in our own country is "disloyal" and "unpatriotic."  Along with many on
the left today, I prefer to think that patriotism requires me
to question, to draw attention to the lessons of history, to be loyal
to principles (among which are the Declaration of Independence with its
strong opposition to monarchy and executive power, and the
Constitution, with its separation of powers and limited Executive
branch). 

To some extent, these models of patriotism are also different models of
democracy.  I’ll try to make more of this pair of oppositions in a
future post, but one model of democracy and patriotism is majoritarian,
the other anti-majoritarian.  In one model, the majority elects
leaders, and then the whole country is supposed to follow those leaders
until it’s time to elect a different set.  The majority, and those
leaders, get to "have their way" while in power or in the majority.  In
the second model, democracy is designed to represent all views
simultaneously, and through an adverserial process of negotiation and
legislation, our elected representatives come to compromises which
please many, and displease the rest as little as possible.  It’s fairly
clear that the right, and much of the non-political public, views
democracy through the majoritarian lens.  And it’s clear that the left,
out of power, wants to view democracy as the anti-majoritarian,
adverserial and Madisonian process of balancing viewpoints. 

It’s getting harder and harder for folks who subscribe to each of these
views to talk civilly about our country’s problems.  To remain one
country and one constitutional democracy, we need to find common
ground.  I have no problem putting my support behind leaders who lead
within the rules, who lead without lying and manipulation.  In short, I
have no problem lining up behind a leader who deserves to lead.  A
couple of days ago I got invited to a fundraiser and meeting with
Senator Clinton, a fairly pricey affair.  I’m hesitant to go, because
the price of admission is declaring my support through my checkbook.
I’m not sure which of the Presidential candidates on either side are
really suited to lead this country and I’m certainly not yet willing to
pay ahead of time for the privilege of being convinced in person.  Their job, over the next year, is to convince us that one or more candidates has what it takes to unify and lead, while working within the laws and principles we hold dear.  Not that one or more candidates looks
Presidential, or has the right gravitas, or folksiness, or does the
best impression of Reagan, or talks the toughest about 9/11, or
energizes the crowd the most at rallies, or is the natural heir of JFK,
or any of the other silliness one hears constantly in political
commentary.

The multiple patriotisms in this country can and should find common ground in demanding just one thing:  whether
you believe in unity behind a leader or fidelity to principle, let’s
demand more of the people to whom we hand power and authority.
In return for our unified support, in return for putting aside our
differences, we require you, the prospective leader of the free world,
to cease being a partisan politician while you’re sitting in the Oval Office, and be instead the leader of all Americans.
This is a tall order, but it’s one that was ably accomplished by all of
America’s greatest Presidents, from George Washington to Lincoln to
FDR. 

Today I got a bit of an inkling at a more psychologically adequate answer.  That’s not to say that it’s the "correct," or complete, or the only answer, but I immediately recognized it as a gut-level truth, at least within the scope of my life.  I attended our department’s reception for graduate students and faculty, held at the beginning of the academic year, and met a number of new and returning students, many of whom (because I’ve been off doing business and other things) I’d never met. 

One of the students told me of a class taught the previous year where they’d read a paper I’d written with Carl Lipo (and likely others, I didn’t catch the exact citation, but I’m guessing Lipo et al. 1997).  He mentioned it because of the oddity of actually running into and meeting one of the authors, but for me the experience was significant.  Here was somebody who knew something about me before ever having met me — in this case, how I thought and what I thought about a topic.  He’d encountered some aspect of me as assigned reading in a class, and thus was acquainted with something I’d done and thought, years before. 

We hope to be known, ultimately, by our words and thoughts and ideas.  We hope to be assigned reading, or the fortuitous article or book encountered in the library late one night.  We hope to be the idea that causes somebody else’s project or thoughts to finally "gel" and come together.  Just as others served as the building blocks with which we had a tiny nugget of a new idea, we hope to be the seeds of someone else’s new ideas, down the road.  Most of my ideas and published works will not accomplish this, but some might, whether in a small or large way.

And with that, I greet the new academic year, secure in the knowledge that something I wrote is being read.  And that’s why I, and many others, do research. 

Actually, no programmers I know (including myself) actually celebrate Programmer’s Day, but it seems like one of those silly nerd memes to get in while real estate on the ground floor is still cheap. So a shout out to TimH, Bryan, Alx, another TimH, Alex, Carl, the OpsMgr gang at MS, Laird, Glomph, and the Ashworth crowd.

My favorite five programmer excuses. ‘Cause we’ve all said one of these at some point….

1. That’s weird, It’s never done that before
2. It worked yesterday.
3. It works on my machine.
4. I only changed a comment.
5. It’s 90% done.

Regularly scheduled programming will resume shortly. I promise.

In the first case, the problem was that my friend tried to reinstall XP Pro SP2 over a Dell OEM installation of Windows Media Center, and got an error saying that the product key was invalid. It only took one email for my friend, who’s probably accustomed to folks like me asking seemingly simplistic questions like “did you mistype the code?” to convince me that, indeed, this was a real error. In the second case, a neighbor here on the island knew I was in the software business and asked me why his HP inkjet printer didn’t seem to install and work correctly on his Mac running OS X.

In both cases I was initially stymied. In the second case, I’m still stymied, but I’m buying the guy’s boat so I might help him figure it out tomorrow.

In the first case, a quick Google on the problem revealed that other people have exactly the same problem. Reinstalling a personal (i.e., non-Enterprise) license key for XP Pro over Media Center seems to reject perfectly valid license keys. Of course, even though I worked at Microsoft and have worked with Windows since the 3.1 days, I have absolutely no clue why it does this. I just know enough about the complexity of the Windows code base and have enough anecdotal experience not to be shocked in the slightest. Similarly, I’m not shocked that I could have a serious amount of experience with computers and code and still not have a clue.

I suspect the reason for this is that software engineers actually have two core skills, not one. Sure, software engineers are extremely good at abstraction: the skill of looking at a set of particulars, and creating a model of generalizations to represent any other set of particulars that share all or some of the relationships we imagine to exist within the original case. That task of abstraction is the same one shared by mathematicians, physicists, population geneticists, and other creators of mathematical models. But software engineers, and systems administrators, as opposed to pure computer scientists, have a second skill which is equally crucial. The ability to catalog a large number of actual cases, their causes, and their solutions. In other words, the skill to capture and contextualize and apply the lore of computing.

The first ability, I think, is what people expect when they ask me what might be causing their technology to have a problem. The ability to see a rational abstraction behind the seemingly random behavior that’s occurring, and thus to diagnose what’s wrong. But in reality, the extent of one’s command of lore — of detail, contextualized by situation and software version and architecture — governs one’s ability to solve such problems, particularly remotely — without the computer in question in your hands. The reason is the fundamental complexity of the situation. On top of the hardware runs an operating system, with a specific set of rules. That operating system can be tiny, like MS-DOS 3.3, or utterly massive, like the 60+ million lines of C code that purportedly make up Windows XP. On top of this midgit (or giant), rests a layer of drivers — bit of the operating system contributed typically by hardware vendors that allow the whole thing to work on their hardware. And on top of this three-layer cake runs your applications, today often themselves multi-million line pieces of software code. Code that might also depend critically on being able to communicate to other computers, across a network, to gather data via HTML or other “protocols,” which are essentially small languages that all computers must speak fluently in order to not misunderstand one another.

Complexity is the enemy of things “just working.” And it’s the enemy of even computer professionals being able to understand the systems they build. We can visualize a few interactions; we can even visualize a few histories of interactions. But nobody can visualize all of the interactions and possible states that even a moderately large piece of software (forget Microsoft Office, Windows, the Linux kernel, or Mac OS X) can display. Heck, human beings can’t visualize the geometry of a vector with more than three dimensions! How are we possibly going to understand the state space (i.e., possible behavior) of a piece of software with 66 million lines of code and megabytes of internal state variables?

We can’t, in detail. We do so statistically. We test things over partial ranges of their possible behaviors. Hopefully the important range of their behaviors, in terms of how often users can get their system into the same state. Even understanding the scope of the range of possible behaviors is a massive challenge, witnessed by the continued research into code coverage, automated testing, and the like. The current popularity of unit testing probably represents a programmer-driven effort to simply reduce the dimensionality of the state space. Unit testing reduces, by pursuing automated means of verifying the lowest level of “contracts” within the software itself, the size of the state space by large factors.

But what’s left after good, serious modern testing and QA is still a lot of possible behavior, and only some key pathways, the deepest, most intentional valleys through the overall “landscape” of behaviors, are documented or recorded. Much of the state space of a modern commercial software program is still deeply terra incognita, as a simple consequence of the overall complexity and coupling present in our systems.

Thus, I was encouraged by this post about Erlang on Lambda the Ultimate, a prominent blog about programming languages and the associated computer science. The designer of Erlang, Joe Armstrong, has this to say:

The Erlang flagship project (built by Ericsson, the Swedish telecom company) is the AXD301. This has over 2 million lines of Erlang.

The AXD301 has achieved a NINE nines reliability (yes, you read that right, 99.9999999%). Let’s put this in context: 5 nines is reckoned to be good (5.2 minutes of downtime/year). 7 nines almost unachievable … but we did 9.

Why is this? No shared state, plus a sophisticated error recovery model. You can read all the details in my PhD thesis.

Interesting. And impressive. It’s possible that there’s an approach here for reducing complexity to manageable, understandable, plannable levels. Objects, aspects, and other recent software innovations aim to reduce dimensionality, allowing more of the total state of a program to be explicitly designed, rather than showing up as emergent run-time behavior.

It seems clear, though, that getting a handle on complexity in software is critical — if we’re going to be able to diagnose what goes on inside our software, and thus if we’re going to be able to trust it. For commerce. For security. For privacy. And for exercising our rights in a democracy, since more and more, software is involved when we vote and make decisions.

I attempted mathematics, and even went during the summer of 1828 with a private tutor (a very dull man) to Barmouth, but I got on very slowly.  The work was repugnant to me, chiefly from my not being able to see any meaning in the early steps of algebra.  This impatience was very foolish, and in after years I have deeply regretted that I did not proceed far enough at least to understand something of the great leading principles of mathematics, for men thus endowed seem to have an extra sense.

Precisely.  Studying the evolution of culture and cultural behavior, from a modern Darwinian perspective, is inherently a mathematical business.  Change is modeled as shifts in the frequencies of behaviors or traits, rather than outright transformations.  And this means that calculus, linear algebra, differential equations, and stochastic processes are critical tools.  Just as you wouldn’t hire a carpenter that knew how to build a cabinet, but didn’t have the tools to do the work, it’s hard to be an active researcher in this field and not have the right tools. 

So I’m reviewing, practicing, and going further than my previous education in math, and I’m enjoying it thoroughly.  I find that I’m one of those people that needs a purpose and a reason to learn things like the more abstract bits of math, and once I have a good reason, it seems to go smoothly.  But it’s also time-consuming, and it keeps me from writing more.  I thought I’d explain in case y’all wondered why I’ve been quieter than usual.

So I didn’t get any pictures of my Giant Leap Elipse coming down, under the TAC-1 parachute, but another spectator at FITS did, and here it is!  The TAC-1 chute is big, and with anything smaller than a 3 inch airframe it wouldn’t even fit into the tube, but it’s strong and did a great (and almost as  importantly, visible) job of bringing down the rocket.  The small triangle you can see in the photo is a folded hexagon of Nomex cloth, which protects the chute from the heat of motor ejection while stuffed into the body of the rocket.  Much harder to see is the long Kevlar cord which ties together the two sections of the rocket, along with the steel quick-links (like small locking carabiners) that connect all the bits together. 

NOTE:  The photograph here is (c) 2007 Linda Lantzy, and is not covered by the Creative Commons License which governs other content on this website.  See Linda’s PhotoShelter site for licensing information.