My vision for government by data and urgency makes short-lasting decisions based on the most recent data and limited to the most urgent issues. This nimbleness of government will make short term rules instead of lasting laws or permanent regulatory agencies. The concept is to enact some change long enough to address immediate concerns until the ungoverned social order can establish tolerable control over the conditions.
The brevity of the rules is necessary consequence of governing by data instead of cognitive justification through debates and deliberation. The rules are based on recognized patterns or correlations in the data that may be purely spurious and without any causal or explanatory justification. Even without cognitive justification, many strong correlations will persist sufficiently long to provide a benefit of to minimize the losses of a failure. With big data systems, we have opportunities to discover a multitude of patterns to permit a diversification of rules so that disappointing results are balanced with beneficial results. Governing by data also benefits from our current practices of accepting occasional disappointments in data-driven results as a necessary feature that allows us to improve the data through improved collection, analytics, or visualization.
The brevity of rules also changes the concepts of crime and punishment. Government by data and urgency has little or no role in extracting human accountability and justice. This type of government obligates acceptance and participation of rules from data. As a result, this type of government replaces ethics with obedience. Rule enforcement involves policing for obedience and punishment will involve either some commitment to cooperate or a short-term time-out (imprisonment) that expires when the rule expires.
Current democratic governments were inspired from religious traditions that sought to administer a just system. In the religious traditions, the desire to impress or gain favor of God motivated the government to strive to be just, and to impose penalties in an attempt to reform a person’s soul. Later, this explicit goal was replaced with a sense of justice within the governed community in order to maintain a super-majority consent to be governed, or to override a veto by a minority.
In contrast, government by data and urgency dispenses with the goal of establishing long term justice or virtue. The goal of this government is not to impress any gods or even any historians. This government allocates all of its attention on the most urgent issues of the current time by making rules using the most current information. The rationale for this approach to government comes from a change in perspective that occurs when we consider the world from observed data instead of some perceived permanent truth. With observed data, the origin of time is the immediate future instead of the distant past presumed by theoretical approaches.0
Government by data recognizes our history of thinkers, but it respects those ancestors by acknowledging that we can never understand what they are currently thinking (in other words, how history will make sense in the long run). The priority instead is on getting through the current challenges with the resources we have available right now, and that includes all of the human resources. History will come later.
Government by data and urgency rejects the role of being engineers of history. Because of our shorter time-intervals of experience, we are incompetent to be engineers of history. That is the job for our ancestors.
Government by data and urgency has two principles. The government makes decisions informed by latest and most complete data available. Also, the government makes only decisions when there is a consensus of urgency. A consequence of both principles is that the rules will be short-lived. New data will arrive that will make a rule obsolete. Times will change so that the consensus of urgency moves elsewhere.
There will be a steady-state number of active rules based on current priorities and data. Earlier rules automatically expire and we may decline to update the rule if the underlying issues lost their urgency. Even when we decline to renew the rule for on-going enforcement, the earlier implementation will continue to have an affect because of changes in society that adapted to the rules when they were in effect. Many rules only need to be enforced for a short time in order to change social behaviors sufficiently to make an issue more tolerable and less of an urgency.
The recent legislation of the affordable care act (ACA) can provide an illustration of how this reform could have been handled by a government of data and urgency instead of the current government focused on perpetual regulation. The primary source of urgency for passing the legislation concerned a perception that many people had developed health conditions while they were uninsured so that now they find insurance to be prohibitively expensive or unavailable to cover their pre-existing conditions. ACA passed in large part to accomplish two goals: one is to force insurers to accept pre-existing conditions with premiums priced based on community ratings (getting healthy insured people to share the costs), and the other is to establish the expectation that everyone should maintain continuous health insurance coverage.
Government by data and urgency could have produced a rule that accomplished basically the same results as we have currently experienced with the perpetual ACA legislation. The difference would be that rule would expire after a few years. After a couple years, all of the existing patients with pre-existing conditions would become covered. They will longer present an urgency to allow them to access health care. Also, after a couple years, we would have established the message that maintaining continuous coverage, paying into the system while they remain healthy, assures coverage when conditions do arise.
When the rule in this alternative-reality expires, the people will know that they will risk being left out if they allow their coverage to lapse and then develop some condition. Certainly, their numbers may raise to the point of renewed urgency that may require a future rule to repeat the process, but there is no guarantee that this urgency will rise to the level of the population demanding a new rule at all, or at least in time to save the patient. The earlier rule served as a fair warning.
A short term rule could force insures to accept existing pre-existing condition patients, and force everyone to maintain coverage. Such a rule would resolve the urgency of a uninsured population needing immediate healthcare. It will also remind everyone of the importance of maintaining health insurance even while they are healthy. The rule can expire after a few years.
Another recent example concerns addressing the Ebola Virus Disease (EVD) epidemic that became an urgent issue last summer. At that time, there were dire warnings of what would happen if the world did not respond in time. At the time of the warnings there already were responses happening both globally and locally. The warnings claimed these responses were insufficient to stop an epidemic that would see 10,000 new cases per week by December 2014 with a total of nearly a million people with the disease. Now, at the end of December 2014, we observe that the epidemic has been effectively managed. While the danger remains an ongoing concern, the issue has lost its urgency as the number of cases remain manageable and the infection rate R0 is closer to 1 (a manageable rate) than greater than 2 (an unmanageable rate).
The recent Ebola experience offers many lessons.
- One lesson is that the warnings were based on models and simulations rather than observations. Those earlier models turned out to be misleading. The models used the best data at the time but they got it wrong. Although there was a deliberate attempt to get to the truth with cognitive justification, the failure still occurred. We could have observed the same predictive failure based on a simpler decision based on the data alone without the justification. In other words, the careful simulations failed similar to how sometimes spurious correlations fail.
- Another lesson is the modern governments are very slow and deliberative. This slowness is a consequence of the burdens of trying to get the right answer for a long-term solution. In the case of a hazard like a deadly epidemic, this slowness could be tragic.
- Despite the lack of deliberative government actions, volunteer and impromptu efforts implements nimble reactions to the crisis. These nimble short-term commitments turned out to be sufficient to lessen the urgency of the crisis. The evidence so far indicates these nimble short-term actions have been sufficient to change the local community practices to change behaviors (such as treatment and funerary practices) so that the disease is better controlled. The local changes continue to have an impact even as more external aid dwindles.
The main lesson from the recent history of the EVD crisis, is that so far the actual short-term response to the crisis has been sufficient to manage the crisis. This response is consistent with the kind of short-term rule-making we can expect from a government by data and urgency.
Update 1/20/2015: This article raises criticism of the too much too late response to the crisis at least within Liberia:
It now appears that the alarming epidemiological predictions that in large part prompted the U.S. aid effort here were far too bleak. […] It was impossible to predict the decline in the Ebola caseload last September, when the U.S. Centers for Disease Control and Prevention suggested a worst-case scenario of 1.4 million victims in West Africa.
This illustrates an expected consequence of rapid rule-making based on the most current data. Such decisions can be wasteful if the predictions do not turn out to be true. In this case, this was not an ideal example of dedomenocracy rule because the decisions did involve human deliberation and need for justification. Indeed, it may that the human element of deliberation may have contributed to the excess allocation of resources because of the demand for justification led to dark-data from predictive models that turned out to be overly pessimistic and may have ignored observational data about the effectiveness of various local responses. In any case, quick rule making does present the risk of misallocation of resources.
In another example, we could apply government by data and urgency to the issue of anthropomorphic climate change that many consider to be an urgent issue. So far we have been unable to make much progress in addressing this issue. The issue appears to have data supporting the demands for actions. There are claims of broad scientific consensus that humans are causing global climate change that will soon result in disastrous consequences. The issue also appears to have urgency that motives large protests and campaigns to address the issue. I think the reason why we have have not made much progress in making any substantial regulatory changes is because we are only considering long term laws and regulations that will span decades. Such rules are very hard to justify in terms of proving that they will be effective and affordable. Any such rules will require lengthy deliberation and debate.
We could instead address this climate change issue using the nimbler approaches of government by data and urgency. The urgency demands immediate action. The data suggests specific policies that can be enacted. Government by data and urgency would obligate following a recommendation, but this recommended rule would expire shortly, perhaps after a couple years. While the rule is in place, we will collect more data to support future recommended rules as well as to validate the predictions of the older recommendations. After the rule expires, we can replace the rule with an updated rule that includes more recent data. Alternatively, the data may convince us that the issue is no longer a high enough of a priority to demand enacting a new rule. Meanwhile, we would have done something about the issue and that something likely would change behaviors for a long time after the rule expires.
Evidence of long-term behavioral changes comes from the recent rapid decline in energy prices. Despite the availability of far lower cost fuel, the demand for fuel has not rapidly risen back to the demand levels when the fuel was previously this inexpensive. People have adapted their lives around the expectation of high-priced fuel and these cultural changes are likely to persist for a long time. The effect of the multiple years of more expensive fuel made a sustainable change that will persist after the added expense expires. We may expect something similar from a short-term rule to address anthropomorphic climate change while it is an urgent issue. The rule does not have be a perpetual law to have a lasting impact. Shorter-term rules are more easily accepted because their impact will have a near term expiration date. Government by data and urgency will change the rule when new data is available and when people express other priorities.
As I mentioned earlier, government by data an urgency needs a different approach to crime. In particular, it is unacceptable to impose prison sentences that last longer than valid period of the rule that was disobeyed. I would prefer to dispense with incarceration entirely as a form of punishment. At most, a prison sentence for the remaining duration of the rule that was broken would be justified only for the purpose of collecting good data on the cooperating population.
From a data perspective where the origin of time is in the near future, there is nothing to be gained from punishment for a past crime and much to be gained by continuing the contribution of the rule-breaker in society. The concept of punishment for justice or reform comes from old ideas (with religious roots) that demand a consequence for objectionable actions. But in the context of a data-driven government focused on the future, the primary goal is the best course of action for the future given the data resources we currently have.
Evidence of wrong-doing is data. We can use that data in our planning for future rules. As I mentioned earlier, the rules are short-lived and the number of rules are constrained by only the highest priority that have urgency requiring government to make rules. It is likely that the future rules may have no relevance at all for punishing past acts of wrong-doing. In such cases, a punishment for a past error is counter productive. Government by data and urgency focuses entirely on the immediate issues. Once an issue loses priority or a rule loses it data justification, the rule is no longer relevant to society. The breaking of the rule also becomes irrelevant.
An objection to my idealism is that many human failings are part of human nature. While we can set short time limits on rules, there are a large number of rules that will end up getting renewed because they will always be urgent. Human nature is stable across the centuries in terms of frequent crimes that always must be punished. I argue for idealism that a data-driven government can tolerate past crimes while it strives to prevent future ones. My argument is that it is not government’s role to extract justice for past transgressions or attempt to reform the transgressor. The government’s role is to lead society into the future in the most beneficial manner possible as indicated by the data and what people find to be most urgent.
An example of a perpetually prevalent crime that is part of human nature is the matter of homicides. There will always be some people who will act in ways that will lead to the untimely death of another. Some of these acts may be especially repulsive such as deliberately planned murder.
Murder is an extreme case of a lawbreaking. In a government by data and urgency, we will need to make a choice of how to respond to a murder. Either we impose a quick and cruel punishment (or even penalty of death) for extreme cases, or we simply record the data about the murder and attach that record to the individual for possible considerations in future rule-making. The option of long-term imprisonment should not be not an option. The person either has value to add to society or he is completely irredeemable (something that is very rare). If a person has something to offer to society, we need his participation in society to make progress toward the future.
Instead of imprisonment, I imagine that the individuals data record would include the findings of earlier murder. When we make new rules based on data, that data will include such records. The rules will use that data in an attempt to reduce the likelihood of a repeat of similar circumstances that can lead to murder. In particular, the rules may be specific for the murderer in terms of restricting his roles, relationships, or activities to prevent a recurrence. We would still allow him to participate but with some restrictions instead of locking him up in prison.
Again murder is an extreme example and I argue that in most cases we can tolerate the murderer’s continued participation in society. It is not government’s role to extract justice or to foster virtue. The government should focus entirely on meeting the current challenges that the future presents us. Also, because this form of government is informed by abundant data it has the opportunity to use that data to protect the population from someone with a criminal history.
Murder is also an extreme in that a murderer rarely repeats the crime. Other crimes such as substance abuse or engaging in illegal trade are more likely to be repeated but even these may be managed with rules based on sufficient data. The goal of government by data and urgency is not to eliminate objectionable behavior, but instead to manage the behavior so that the behavior is at a tolerable level so the population does not consider it to be priority. Government meets its goals if society can tolerate the residual objectionable behavior.
It should not be the role of government to punish people for the sake of punishment. That is a demand for consequences for actions based on the notion of causality with the past. Government by data and urgency has no use for the past. It remains devoted to the future.
Back to the example of a murder, I still think there is a role for trials and conviction. The judicial system of careful procedures leading to trial by jury is the best system available to establish the facts of a certain event. We need the findings of the judicial process to include in our data stores for future analytics. In particular, the findings will become part of the record for an individual so that future plans can take the information into account for consideration of that individual’s future participation. The findings will also allow us to avoid circumstances that may lead to recurrence of the crime by other individuals in similar circumstances. We can use the same procedures to establish a conviction as trusted data to include in the data store. The conviction need not result in a punishment.
Government by data and urgency will operate very different from the present governments. The focus shifts to immediate issues that can be informed by recent data. Unlike the present government with accumulating perpetual laws, this new form of government exclusively enacts short-lived rules that get updated when new data becomes available or get retired when priorities change. Similarly, the government views the population in terms of future possibilities instead of past performance. Abundant data will permit discovery of new possibilities unrelated to past performance. In particular, the limited range and duration of rules at a given time will limit what it makes sense to consider as a transgression. When a rule becomes obsolete, then any disobedience to that rule will also become obsolete. The government is interested in collecting the data about the disobedience and can use that data for future decision making, but it is not a priority to extract punishment for outdated crimes. The government succeeds when it converts the immediate small number of urgent crises into issues that the population or culture can manage without government. This success is more likely when the government has access to all available human resources.
Government by data and urgency takes a different approach from older forms of government that were inspired from religious traditions. The new government directs its attention toward the future instead of the past, and toward progress instead of toward justice or virtue.
Update 1/3/2015: I encountered this post by Jonathan Rauch describes a complementary approach with the same consequence of fewer formal laws. He is making the case for unwritten social rules that can be as effective as formal laws in governing people. These unwritten rules that substitute for formal laws are how a population can learn to tolerate certain conditions without resorting to the need for a formal law. A large part of that tolerance to some misbehavior can come from a community consensus to request conformance to some rule while tolerating a certain level of transgressions as long as the transgressor does not draw attention to the fact and that fact is easy to overlook. He describes a balance of formal and informal laws but both having similar permanence. In contrast, government by data and urgency uses formal laws only temporarily in order to change people’s behavior to a level that they can tolerate the transgressions. While he describes this tolerance as agreeing not to see what others pretend not to be doing, government by data and urgency allows recognition that the transgression continues, but society has higher priorities than to prosecute it.
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