It is easy to make decisions when we know how two temporally successive events will pan out, i.e., when one event (cause) will necessarily lead to a predictable outcome (effect). We call it causality; more appropriately, linear causality. It’s also easy to predict the outcome.
Take, for instance, an AK-47.
After we have chambered the round, the rifle is cocked and locked. When we squeeze the trigger, the hammer releases and strikes the firing pin. The firing pin punctures the bullet primer, ignites the propellent charge and releases the bullet. As the bullet travels through the muzzle’s rifling, expanding gases force the gas piston backwards. The bolt carrier is forced back and in the process ejects the bullet casing through the ejection port. Then it moves forward, pulls a new round from the magazine and chambers it. In the same action, the bolt also resets the hammer to its starting position and puts the rifle in battery. In the semi-auto mode, the sear keeps the hammer in place until the bolt carrier returns to position.
All these mechanical actions are about linear causality, one leading to another in temporal succession.
Most decision-making, unfortunately, doesn’t work like this, especially when decision-makers are dealing with unknowns (uncertainty), multiple variables or a public policy problem.
As should be obvious from the increasing corpus of writings since the Covid-19 pathogen went on the rampage, it’s easy to understand mechanical causality as in the example above than figure out the best approach to deal with a problem with (a) many unknowns, (b) multiple variables, (c) unintended outcomes of policy approaches.
I have written about the dilemma here, as have others across the globe: flatten the curve or flatten the economy. Both of these throw up their own problems. Some experts are increasingly talking about a smart approach: smart testing, smart lockdowns, tracing and tracking, finding clusters and dealing with them et cetera. One writer, as I mentioned in this space last week, phrased it a hammer-and-dance approach.
Yet, for all the mathematical modelling, there’s an element of hope in these approaches. Making a choice is also about choosing the less painful option. But which option is less painful is again a moot point. It’s like the joke about the Chaudhry of a village who decides to punish a menial labour but gives him a choice: eat 100 onions or be thrashed 100 times. The poor man chooses to eat onions but after eating a few realises that he can’t any more and asks to be thrashed instead. After being thrashed and writhing in pain, he reverts to eating onions and keeps choosing, alternately, between eating onions and getting thrashed, both choices being equally bad.
In a 1973 paper for Policy Sciences titled “Dilemmas in a general theory of planning,” Horst Rittel and Melvin Weber critiqued the scientific bases for confronting problems of social policy:
“The search for scientific bases for confronting problems of social policy is bound to fail, because of the nature of these problems. They are ‘wicked’ problems… Policy problems cannot be definitively described. Moreover, in a pluralistic society there is nothing like the undisputable public good; there is no objective definition of equity; policies that respond to social problems cannot be meaningfully correct or false; and it makes no sense to talk about ‘optimal solutions’ to social problems unless severe qualifications are imposed first. Even worse, there are no ‘solutions’ in the sense of definitive and objective answers.”
In other words, our problem begins with defining the problem, “of knowing what distinguishes an observed condition from a desired one.” This is intrinsically linked with situating the problem in complex causal networks. Predictably, it leads to the problem of identifying the actions that could narrow the gap between what-is and what should be.
Take the example of someone solving a maths problem. Even when he is working with variables, and even if he can’t solve it, he is working in an environment that follows a pattern, a structure and a logic. He doesn’t have to contend with anything or anyone outside of the problem. Whatever the degree of difficulty, it inheres in the problem.
Not so with public policy issues. Let’s take an example that brings maths and humans together: a freeway. We have knowledge and expertise on how to build one. The engineers and their maths for building a freeway and its bridges is almost banal now. But the problem has externalities, for instance, if you want to do it in Balochistan. That’s the human side of the problem with its political and socioeconomic dimensions. Building a freeway may be efficient, but it might prove to be poor politics and thus poor public policy — unless, one were to change the dynamics of the circumstances in which that decision could be made to stick.
Put another way, to use Rittel and Weber’s terminology, some problems are tame or benign while others are wicked.
I have previously noted the criticism this government is contending with in dealing with the Covid-19 threat. Granted, this might not be the most efficient government in this country’s history, but the only way to determine if another government could have done better than this one would be to have two governments, each working this problem and one finding better outcomes than the other. That experiment is obviously impossible. But it also tells us that we do not have any reference point against which to judge this government’s efficiency or otherwise in the face of this threat.
I understand that two arguments can be presented to counter what I have said: one, the Sindh government is doing better; two, one can intelligently analyse and see the performance of the current government. I will only partially concede both arguments. Here’s why.
One, the Sindh government is operating in a smaller area than the federal government and its political tributaries. Two, it is being lauded primarily for insisting on — and continuing with — a lockdown. That’s a choice and those who are in favour of it are mostly — if not all — those who are either opposed to this government or are predisposed to a lockdown because they can earn without the requirement of stepping out to earn bread. Sweden, for example, is staying open, even though it’s mortality as a percentage of total infected cases is higher than entire Pakistan’s. Is that a better choice than Sindh’s. I don’t know.
As for intelligently analysing the government’s performance, even discounting our heuristic disposition, the best we can do is to look at what’s being done or not and comment on that. There’s no way in hell that any commentator, the present writer included, can guarantee the outcome. All one can do is to take our own preferred approach and either agree or disagree with the government.
That does not mean the government might not be screwing up. It most probably is. But could we have done better both in terms of defining and situating the problem and finding the best-possible course of action?
I doubt it; hell, I know it. Which is why I’d much rather deal with the linear, mechanical operation of the AK-47 than with a public policy problem dealing with a damn invisible pathogen!
The writer is a former News Editor of The Friday Times. He reluctantly tweets @ejazhaider
Take, for instance, an AK-47.
After we have chambered the round, the rifle is cocked and locked. When we squeeze the trigger, the hammer releases and strikes the firing pin. The firing pin punctures the bullet primer, ignites the propellent charge and releases the bullet. As the bullet travels through the muzzle’s rifling, expanding gases force the gas piston backwards. The bolt carrier is forced back and in the process ejects the bullet casing through the ejection port. Then it moves forward, pulls a new round from the magazine and chambers it. In the same action, the bolt also resets the hammer to its starting position and puts the rifle in battery. In the semi-auto mode, the sear keeps the hammer in place until the bolt carrier returns to position.
All these mechanical actions are about linear causality, one leading to another in temporal succession.
Most decision-making, unfortunately, doesn’t work like this, especially when decision-makers are dealing with unknowns (uncertainty), multiple variables or a public policy problem.
As should be obvious from the increasing corpus of writings since the Covid-19 pathogen went on the rampage, it’s easy to understand mechanical causality as in the example above than figure out the best approach to deal with a problem with (a) many unknowns, (b) multiple variables, (c) unintended outcomes of policy approaches.
I have written about the dilemma here, as have others across the globe: flatten the curve or flatten the economy. Both of these throw up their own problems. Some experts are increasingly talking about a smart approach: smart testing, smart lockdowns, tracing and tracking, finding clusters and dealing with them et cetera. One writer, as I mentioned in this space last week, phrased it a hammer-and-dance approach.
Yet, for all the mathematical modelling, there’s an element of hope in these approaches. Making a choice is also about choosing the less painful option. But which option is less painful is again a moot point. It’s like the joke about the Chaudhry of a village who decides to punish a menial labour but gives him a choice: eat 100 onions or be thrashed 100 times. The poor man chooses to eat onions but after eating a few realises that he can’t any more and asks to be thrashed instead. After being thrashed and writhing in pain, he reverts to eating onions and keeps choosing, alternately, between eating onions and getting thrashed, both choices being equally bad.
In a 1973 paper for Policy Sciences titled “Dilemmas in a general theory of planning,” Horst Rittel and Melvin Weber critiqued the scientific bases for confronting problems of social policy:
“The search for scientific bases for confronting problems of social policy is bound to fail, because of the nature of these problems. They are ‘wicked’ problems… Policy problems cannot be definitively described. Moreover, in a pluralistic society there is nothing like the undisputable public good; there is no objective definition of equity; policies that respond to social problems cannot be meaningfully correct or false; and it makes no sense to talk about ‘optimal solutions’ to social problems unless severe qualifications are imposed first. Even worse, there are no ‘solutions’ in the sense of definitive and objective answers.”
In other words, our problem begins with defining the problem, “of knowing what distinguishes an observed condition from a desired one.” This is intrinsically linked with situating the problem in complex causal networks. Predictably, it leads to the problem of identifying the actions that could narrow the gap between what-is and what should be.
Take the example of someone solving a maths problem. Even when he is working with variables, and even if he can’t solve it, he is working in an environment that follows a pattern, a structure and a logic. He doesn’t have to contend with anything or anyone outside of the problem. Whatever the degree of difficulty, it inheres in the problem.
Not so with public policy issues. Let’s take an example that brings maths and humans together: a freeway. We have knowledge and expertise on how to build one. The engineers and their maths for building a freeway and its bridges is almost banal now. But the problem has externalities, for instance, if you want to do it in Balochistan. That’s the human side of the problem with its political and socioeconomic dimensions. Building a freeway may be efficient, but it might prove to be poor politics and thus poor public policy — unless, one were to change the dynamics of the circumstances in which that decision could be made to stick.
Put another way, to use Rittel and Weber’s terminology, some problems are tame or benign while others are wicked.
I have previously noted the criticism this government is contending with in dealing with the Covid-19 threat. Granted, this might not be the most efficient government in this country’s history, but the only way to determine if another government could have done better than this one would be to have two governments, each working this problem and one finding better outcomes than the other. That experiment is obviously impossible. But it also tells us that we do not have any reference point against which to judge this government’s efficiency or otherwise in the face of this threat.
I understand that two arguments can be presented to counter what I have said: one, the Sindh government is doing better; two, one can intelligently analyse and see the performance of the current government. I will only partially concede both arguments. Here’s why.
One, the Sindh government is operating in a smaller area than the federal government and its political tributaries. Two, it is being lauded primarily for insisting on — and continuing with — a lockdown. That’s a choice and those who are in favour of it are mostly — if not all — those who are either opposed to this government or are predisposed to a lockdown because they can earn without the requirement of stepping out to earn bread. Sweden, for example, is staying open, even though it’s mortality as a percentage of total infected cases is higher than entire Pakistan’s. Is that a better choice than Sindh’s. I don’t know.
As for intelligently analysing the government’s performance, even discounting our heuristic disposition, the best we can do is to look at what’s being done or not and comment on that. There’s no way in hell that any commentator, the present writer included, can guarantee the outcome. All one can do is to take our own preferred approach and either agree or disagree with the government.
That does not mean the government might not be screwing up. It most probably is. But could we have done better both in terms of defining and situating the problem and finding the best-possible course of action?
I doubt it; hell, I know it. Which is why I’d much rather deal with the linear, mechanical operation of the AK-47 than with a public policy problem dealing with a damn invisible pathogen!
The writer is a former News Editor of The Friday Times. He reluctantly tweets @ejazhaider