This informationisbeautiful graphic is pretty, but I don’t find it informative. The y scale is nonlinear, and I don’t know if the x scale conveys anything. It’s hard to work out the timing of inundation, which is really the key. The focus on the low points of big cities in developed countries is misleading, because those will be defended for a long time. Ho Chi Minh city should be on there, as well as the US gulf coast. USA Today would love this.
Next week I’m off to the EMF Snowmass conference on climate change impacts and integrated assessment. I’m more excited about the great minds than the great venue, though I can’t complain about the latter. Except this: “to ensure your safety, the steep road winding its way from the mountain’s base to the Top of the Village is heated in the winter to keep it dry.”
Democrats have pulled the plug on a sweeping energy bill this year. There is no heir apparent. This is not cause for panic. In climate, as in education, there are no emergencies.
However, the underlying reasons may be cause for panic. It seems that voters are unwilling to accept any policy that will significantly raise the price of emissions. Given that price is a predominant information carrier in our economy, other polices are unlikely to work efficiently, absent a price signal. That leaves us in a bit of a pickle. What to do?
Alternatively, you might conclude that the public hasn’t quite grasped the nature of the problem – that wait and see is not a good policy in systems with long delays. But then you’d be accused of scientism, for the equivalent of challenging the efficient market hypothesis or the notion that the customer is always right. That’s rather puzzling, given that there’s direct evidence that people don’t intuitively appreciate the dynamics of accumulation, and that snowstorms in the East cause half of Americans to question the reality of climate change.
The anti-scientism, pro-technology crowd takes opposition to meaningful mitigation policy as a sure sign that the public is on to something. The wisdom of crowds is powerful when there’s diverse information and rapid feedback, as in price discovery through a market. But it has a pretty disastrous history in the runup to bubbles and other catastrophes, as we’ve recently seen. Surely there are some legitimate worries about current climate proposals (I’ve expressed a number here), but it doesn’t follow that pricing emissions is a bad decision.
So, what’s a modeler to do? Opening up political debates is a good idea, though not quite in the way that I think proponents intend. We already have plenty of political debates. The problem is that they tend to lack ready access to scientific or other information that can be agreed upon or at least presented in a way that permits testing of hypotheses against data or evaluation of decisions against contingencies. That means that questions of values and distribution of benefits (which politics is rightfully about) get mixed up with muddled thinking about science, economics, and social system dynamics.
The solution typically proposed is to open up science and models to more public scrutiny. That’s a good idea for a variety of reasons, but by itself it’s a losing proposition for scientists- they get all the criticism, and the public process doesn’t assimilate much of their insights. What’s needed is a fair exchange, where everyone shows their hands. Scientists make their stuff accessible, and in return participants in policy debates actually use it, and additionally submit to formalization of their arguments to facilitate shared understanding and testing.
Coming back to cap & trade, I don’t see that the major political players are willing to do that. Following a successful round of multi-stakeholder workshops that brought a systems perspective to conversations about climate policy, funded by the petro industry in California, we spent a fair amount of time marketing the idea of a model-assisted deliberation process targeted at shared design of federal climate policy. Lobbyists at some of the big stakeholders told us very forthrightly that they were unwilling to engage in any process with an outcome that they couldn’t predict and control.
In an environment where everyone’s happy with their own entrenched position, their isn’t much hope for a good solution to emerge. The only solution I see is to make an end run around the big players, and go straight to the public with better information, in order to expand the set of things they’ll accept. I hope there’s time for that to work.
The temperance movement may have won the prohibition war (temporarily), but a minor battle was lost just down the road from here, in Butte.
Despite the reformers’ best efforts, Butte’s demimonde was larger and seedier than ever by 1910. That year the federal census recorded Butte’s highly transient population at more than 39,000 and enumerated more than 250 prostitutes. In 1910 when temperance crusader Carrie Nation came to Butte, “booze joints” in nearby Anaconda sported signs that read: “All Nations Are Welcome Except Carrie.” Butte’s morally upright citizens, who had invited Nation, welcomed her with open arms, yet her performance failed to match their expectations. With a flourish and a crowd in tow, the stout sixty-three-year-old Nation charged down the length of Pleasant Alley. Once back on Mercury Street, she stormed into the Irish World, where she met her match in madam May Maloy. The two women joined in a scuffle, and Nation emerged the obvious loser. It was a moment savored by May’s patrons and celebrated with drinks all around. – Ellen Baumler, Montana Historical Society
Nation died 6 months later.
Prohibition was a personal triumph for Carrie Nation, and a disaster for the American nation. In her Smith College commencement address, Rachel Maddow translates that into some great personal advice. She makes the case very nicely for ethics that help us transcend short term pressures and build a future we can be proud of. It’s tough to convince people to act when the dynamics of life are worse-before-better, but the vivid image of Carrie’s hatchetations leading a nation to ruin are effective.
Incidentally, industrial alcohol is still poisoned with methanol today.
Hoisted from the comments – thanks to Cherilyn.
Complex systems find many ways of resisting or evading pressures, resulting in policy failure, backlashes, whack-a-mole games and other unintended consequences. Some great examples just wandered by my desk:
Via Economist’s View:
Immigration reform has a long history of unintended consequences: More than two decades of increased enforcement since the passage of the Immigration Reform and Control Act of 1986 has done little to reduce the number of illegal immigrants. In fact, it seems to have increased their numbers. …
Princeton University sociologist Douglas Massey pointed out … that measures to secure the border seemed to produce almost the opposite of what was intended. … With increasing border enforcement, workers who used to shuttle between jobs in California or Texas and home in Zacatecas or Michoacán simply began to stay put and sent for their families, becoming permanent, if sometimes reluctant, residents. According to Massey, post-IRCA border enforcement may have increased the size of the permanent Mexican population in the United States by a factor of nearly four.
From a great article on Wayne Wheeler, The Man Who Turned Off the Taps, in Smithsonian:
But for all his political might, Wheeler could not do what he and all the other Prohibitionists had set out to do: they could not purge alcoholic beverages from American life. Drinking did decline at first, but a combination of legal loopholes, personal tastes and political expediency conspired against a dry regime.
As declarative as the 18th Amendment was—forbidding “the manufacture, sale, or transportation of intoxicating liquors”—the Volstead Act allowed exceptions. You were allowed to keep (and drink) liquor you had in your possession as of January 16, 1920; this enabled the Yale Club in New York, for instance, to stockpile a supply large enough to last the full 14 years that Prohibition was in force. Farmers and others were allowed to “preserve” their fruit through fermentation, which placed hard cider in cupboards across the countryside and homemade wine in urban basements. “Medicinal liquor” was still allowed, enriching physicians (who generally charged by the prescription) and pharmacists (who sold such “medicinal” brands as Old Grand-Dad and Johnnie Walker). A religious exception created a boom in sacramental wines, leading one California vintner to sell communion wine—legally—in 14 different varieties, including port, sherry, tokay and cabernet sauvignon.
By the mid-’20s, those with a taste for alcohol had no trouble finding it, especially in the cities of the East and West coasts and along the Canadian border. At one point the New York police commissioner estimated there were 32,000 illegal establishments selling liquor in his city. In Detroit, a newsman said, “It was absolutely impossible to get a drink…unless you walked at least ten feet and told the busy bartender what you wanted in a voice loud enough for him to hear you above the uproar.” Washington’s best-known bootlegger, George L. Cassiday (known to most people as “the man in the green hat”), insisted that “a majority of both houses” of Congress bought from him, and few thought he was bragging.
Worst of all, the nation’s vast thirst gave rise to a new phenomenon—organized crime, in the form of transnational syndicates that controlled everything from manufacture to pricing to distribution. A corrupt and underfunded Prohibition Bureau couldn’t begin to stop the spread of the syndicates, which considered the politicians who kept Prohibition in place their greatest allies. Not only did Prohibition create their market, it enhanced their profit margins: from all the billions of gallons of liquor that changed hands illegally during Prohibition, the bootleggers did not pay, nor did the government collect, a single penny of tax.
The prohibition article also poses an interesting puzzle. If prohibition was more or less quickly and broadly unpopular, how did it get passed by such landslide margins in the first place? I can’t believe that ignorance of the possible outcome was universal, so there must have been some powerful positive feedback behind the initial passage of the policy. Perhaps it was a tipping point effect: once a vote becomes sufficiently lopsided, fewer and fewer politicians want to be on the losing side of a landslide vote, so they join the herd. A modern analogy might be the post-9/11 authorization of the Iraq war.
That’s really the only advice I can give on models and copyrights.
Nevertheless, here are some examples of contract language that may be illuminating. Bear in mind that I AM NOT A LAWYER AND THIS IS NOT LEGAL ADVICE. I provide no warranty of any kind and assume no liability for your use or misuse of these examples. There are lots of deadly details, regional differences, and variations in opinion about good contract terms. Also, these terms have been slightly adapted to conceal their origins, which may have unintended consequences. Get an IP lawyer to review your plans before proceeding.
Oct 19-21, 2010 — Boston Mass USA
Climate Interactive and SEED Systems are offering a powerful three-day workshop for innovative climate, energy, and sustainability leaders from business, non-profit, government, and university sectors, led by Drew Jones and Sara Schley.
Attend to develop your capacities in:
• Systems thinking: Causal loop and stock-flow diagramming.
• Leadership: Vision, reflective conversation, consensus building.
• Computer simulation: Using and leading policy-testing with the C-ROADS/C-Learn simulation.
• Policy development: Attendees will play the World Climate exercise.
• Climate, energy, and sustainability strategy: Reflections and insights from international experts.
• Business success stories: What’s working in the new low carbon economy and implications for you.
• Building your network of people sharing aspirations for climate progress.
We will stay connected and collaborate to accelerate progress.
For more information and to register please visit http://climateinteractive.org/events
What do you do when feasible policies aren’t popular, and popular policies aren’t feasible?
Let’s start with a joke:
Lenin, Stalin, Khrushchev and Brezhnev are travelling together on a train. Unexpectedly the train stops. Lenin suggests: “Perhaps, we should call a subbotnik, so that workers and peasants fix the problem.” Kruschev suggests rehabilitating the engineers, and leaves for a while, but nothing happens. Stalin, fed up, steps out to intervene. Rifle shots are heard, but when he returns there is still no motion. Brezhnev reaches over, pulls the curtain, and says, “Comrades, let’s pretend we’re moving.” (Apologies to regulars for the repeat.)
The Soviet approach would be funny, if it weren’t the hottest new trend in climate policy. The latest installment is a Breakthrough article, The emerging climate technology consensus. An excerpt: Continue reading “The emerging climate technology delusion”
Or, Friends don’t let friends work for hire.
Photographers and other media workers hate work for hire, because it’s often a bad economic tradeoff, giving up future income potential for work that’s underpaid in the first place. But at least when you give up rights to a photo, that’s the end of it. You can take future photos without worrying about past ones.
For models and software, that’s not the case, and therefore work for hire makes modelers a danger to themselves and to future clients. The problem is that models draw on a constrained space of possible formulations of a concept, and tend to incorporate a lot of prior art. Most of the author’s prior art is probably, in turn, things learned from other modelers. But when a modeler reuses a bit of structure – say, a particular representation of a supply chain or a consumer choice decision – under a work for hire agreement, title to those equations becomes clouded, because the work-for-hire client owns the new work, and it’s hard to distinguish new from old.
The next time you reuse components that have been used for work-for-hire, the previous client can sue for infringement, threatening both you and future clients. It doesn’t matter if the claim is legitimate; the lawsuit could be debilitating, even if you could ultimately win. Clients are often much bigger, with deeper legal pockets, than freelance modelers. You also can’t rely on a friendly working relationship, because bad things can happen in spite of good intentions: a hostile party might acquire copyright through a bankruptcy, for example.
The only viable approach, in the long run, is to retain copyright to your own stuff, and grant clients all the license they need to use, reproduce, produce derivatives, or whatever. You can relicense a snippet of code as often as you want, so no client is ever threatened by another client’s rights or your past agreements.
Things are a little tougher when you want to collaborate with multiple parties. One apparent option, joint ownership of copyright to the model, is conceptually nice but actually not such a hot idea. First, there’s legal doctrine to the effect that individual owners have a responsibility not to devalue joint property, which is a problem if one owner subsequently wants to license or give away the model. Second, in some countries, joint owners have special responsibilities, so it’s hard to write a joint ownership contract that works worldwide.
Again, a viable approach is cross-licensing, where creators retain ownership of their own contributions, and license contributions to their partners. That’s essentially the approach we’ve taken within the C-ROADS team.
One thing to avoid at all costs is agreements that require equation-level tracking of ownership. It’s fairly easy to identify individual contributions to software code, because people tend to work in containers, contributing classes, functions or libraries that are naturally modular. Models, by contrast, tend to be fairly flat and tightly interconnected, so contributions can be widely scattered and difficult to attribute.
Part of the reason this is such a big problem is that we now have too much copyright protection, and it lasts way too long. That makes it hard for copyright agreements to recognize where we see far because we stand on the shoulders of giants, and distorts the balance of incentives intended by the framers of the constitution.
In the academic world, model copyright issues have historically been ignored for the most part. That’s good, because copyright is a hindrance to progress (as long as there are other incentives to create knowledge). That’s also bad, because it means that there are a lot of models out there that have not been placed in the public domain, but which are treated as if they were. If people start asserting their copyrights to those, things could get messy in the future.
A solution to all of this could be open source or free software. Copyleft licenses like the GPL and permissive licenses like Apache facilitate collaboration and reuse of models. That would enable the field to move faster as a whole through open extension of prior work. C-ROADS and C-LEARN and component models are going out under an open license, and I hope to do more such experiments in the future.
Update: I’ve posted some examples.