Thursday, February 12, 2009

Machines in the Zone

After several months of pursuing my own projects, I was forced into the drudgery of looking for a job. That drudgery was recently rewarded by a thoughtful stranger who happened to need my most developed professional skills for a few weeks, and I rediscovered the mindset that best works for me when in the employ of others: being “in the zone” and acting like a machine.

“In the zone” is a phrase a former co-worker used to describe the state of being totally focused on a task, to the exclusion of everything else. I’ve experienced this often, especially when writing or trying to meet any kind of deadline.

I feel most alive when I’m following my own guidance: asking and answering questions; exploring and having radically new experiences; being “in the moment” with someone I care about; or creating something molded from any or all of these. I feel least alive, like a machine, when I am doing something procedural, uninteresting, or totally controlled by someone else.

To be “productive” – that is, give a purchaser of labor the most output per unit of pay – we must to some degree function as machines, because the way we spend our time (what our employers are paying for) must be quantifiable and predictable. Anything we do when “at work” must be able to have a monetary value associated with it. Whatever we can do to turn out the most in the way of products or services (such as being in the zone) has the potential to be rewarded with higher pay, more work, or both.

In an economy designed to reward growth in transactions and punish activity that doesn’t result in such growth, most of us will find ourselves feeling less alive if we are really honest with ourselves. Because those of us lucky enough to have jobs must buy as well as sell, we will be pressured to act as purchasing machines when we’re not working for the privilege.

Since growth can not physically continue into the far future (or even, arguably, the not-too-distant future) without irreparable harm to ourselves and the biosphere we depend on for survival, we must learn to act less as machines and more as people. We will be rewarded with more life, taking back the control from others and both experiencing and sharing our own uniqueness as a “supply” that can’t be traded. The world will be rewarded by a lesser load on natural systems and a population of people who cares to integrate itself into the complexity of life rather than destroying that complexity in favor of a small number of uninteresting forms.

Sunday, February 8, 2009

Ideal Lawmaking

Laws bear an uncanny resemblance to computer code. If this analogy is an accurate one, then it should be theoretically possible to simulate the effects of new laws before they are enacted. Lawmakers could then argue about the “requirements” of the “software” instead of wasting time in “programming” and “code review” (the equivalent of a software development team’s programmers could handle those chores).

The simulation (in a “development environment”) would be run and its results analyzed by “quality assurance (QA) engineers” for conformance to the requirements. Deviations from requirements (“bugs” in the “software”) would be corrected by the “programmers.” When the output of the simulation met the requirements, then the actual law would be enacted in a “test environment” that was representative of the larger conditions it would apply to when finally enacted. The “QA engineers” would evaluate the results and recommend any “bug fixes” to the “programmers” as well as necessary modifications to the predictive software (thus improving the accuracy of future simulations). When the law passed its tests and reality matched the simulations, then the law would be fully enacted. This process seems to be a reasonable approach to lawmaking, which ideally should achieve predictable results.

Reality is, unfortunately, much different. In the United States, legislators, like business analysts in software development, do collect the equivalent of requirements from “shareholders” – their constituents – but then they turn directly to crafting the laws, the equivalent of programming (admittedly with some help by staff lawyers), even though not all of them are even familiar with the language. Experts serve the role of both stakeholder representatives (in the requirements gathering phase) and predictive software (providing opinions about the effects of the laws, which is the equivalent of a simulation’s output). Laws are then enacted, like releasing software without testing it. When problems are found in the real world – as they often are – the legal system (judges and lawyers) performs the role of quality assurance. Precedent and court opinions act as modified user documentation in the software analogy; and if this isn’t sufficient to address the problems, lawmakers may alter the law like programmers making bug fixes, or create new laws if necessary.

When our government was set up, populations were small and relatively isolated. Legislators had direct experience with the results of laws in environments where failure had limited impact. Crafting “requirements documents” could be done by almost anyone, and the legal implementation was short and understandable by most people. Now we live in a large, complex, interconnected system, whose domestic population is approaching 80 times larger than at our founding, and whose impact on the entire world is arguably greater than any other nation.

It is possible that modeling of human behavior and the physical systems we interact with may not be up to the task of providing a reasonably accurate simulation of the potential impact of any but the simplest new law. Even if computers can handle the grunt work of generating predictions, the theoretical and empirical underpinnings of a model may not adequately exist. With so many people’s lives at stake, shouldn’t we at least try, achieving the best approximations possible (and improving them along the way)?

Saturday, February 7, 2009

Accountability Defenses

One of the hardest things any of us can do is to admit something we’ve done wrong, especially something with a huge impact on a lot of people. If the admission itself has negative consequences, we may go to great lengths to avoid it, or at least soften the blow. And this assumes that we even recognize and accept the wrongness of what we did.

High-profile examples are plentiful. The Bush administration lied, killed, tortured, and made it easy for corporations to steal and ruin the environment. A large peanut company ignored evidence of salmonella poisoning, leading to sickness and death. Tobacco and oil companies sowed doubt about evidence that their products were toxic to people and the planet, respectively.

In such circumstances individuals may hide their responsibility behind policy, precedent, or ambiguity. Policy assigns responsibility to the organization rather than the individual (“I was just following orders” or “there’s no law against it”). Precedent dilutes blame (“someone else did it, so I assumed it was okay”). Ambiguity provides an argument that the action wasn’t even wrong (“no one can say for sure that the infraction occurred”). Without these defenses, people (or corporations, which are legally people) can be forced to come to terms with what they have done (accountability); and steps can be taken to repair the damage and discourage others from doing the same – or worse.

It is in everyone’s best interest to remove the defenses against accountability. The policy defense can be taken away by making better ones (or at least having society impose requirements on them, through laws). The precedent defense can be removed by providing a mechanism for accountability to be retroactive and universally applicable. The ambiguity defense is best eliminated by assuming guilt, rather than innocence, within a specified range of error in observation.

If we all genuinely wanted to maximize the positive effects and limit the negative effects of our behavior on others, present and future, these measures would be useful but not necessary. No matter how good our intentions, none of us is omniscient or omnipotent and are therefore bound to flounder in this effort at some point. We are also inclined to escape pain, psychological and otherwise, sometimes to the extent of creating delusions wherein we are always right. Society has a great stake in helping everyone overcome obstacles to accountability, so we should accept such help wherever we can.

Monday, February 2, 2009

The Moderate Middle

If roughly one-fourth of us are predominantly diversity-seekers, and there is the same amount of diversity-avoiders, then half of us are somewhere in-between. The behavior of the “moderate middle” tends to be neither very accepting of others nor very excepting of others. These people are not typically part of the “base” of any political party aligned along a conservative-liberal bias (such as U.S. Republicans and Democrats), favoring instead a mix that averages out over time and circumstance.

This analysis assumes a spectrum across any random population of people, possibly correlating with personality type. In the empirically-based Big Five personality model, the most useful of its kind, the relevant personality dimensions are likely “openness” and “agreeableness” which address one’s curiosity and altruism, respectively. In situations where rules of behavior must change and people must work closely together, diversity-seekers will easily adapt, with the rest of the spectrum requiring an increasing amount of convincing as people’s comfort zones fall further away from the kind of life they will need to live.

As with any spectrum, the closest any situation can come to everyone’s comfort zone is where the average person is most happy. The exact middle is the best target for any set of circumstances we might want to create for optimum happiness across a population. There is neither too much nor too little variability in experience and need for cooperation; that is, opportunity for social stress.

These considerations are the basis of the environment-lifespan correlation that underlies the Comfort model. Each “environment” corresponds to a circumstance within the broadest spectrum of possible combinations of personality and physical condition (arbitrarily falling on a scale from zero to six). The difference between what makes a person most comfortable (happy) and the environment that actually exists determines just how happy the person will be. Since happiness is proportional to lifespan and lifespan correlates with per-capita consumption of resources, the estimated amount of remaining (non-renewable) resources can be used to calculate how long those resources will last. Following this chain of logic and modeling the actual range of environments preferred by the world’s population (which is narrow and close to the middle) we can deduce that the closer we come to making everyone happy (catering to the middle), the equivalent of following the ideal path, the less time our civilization can survive without replenishing resources.

What does this mean for those of us who want to influence public policy to achieve the best possible outcome for humanity? As I’ve suggested in several ways before, it means that we must focus our attention on increasing the total amount of renewable resources to match current consumption, then increase both the minimum and maximum environments to effectively approach the middle (along the ideal path) while compensating for these changes with more renewable resources.