How it all ends - The Manpollo Project

This video-article is part of an advanced listening activity for advanced learners of English.

  

The video on Youtube:

Note: The script below is from the author at Manpollo.org and other site (on this second site, the author asks for help translating the topics to Spanish for DVDs, etc.) The script doesn't correspond 100% to the video and still needs checking over.

[DESK] This video is called “The Manpollo Project” and is part of the expansion pack accompanying the original video “How It All Ends.”
This video is to address the concerns of all those who feel that I’ve oversimplified something inappropriately in my risk management approach to climate change represented by the grid in the video “How It Alls Ends,” and that that oversimplification can’t be ignored, because it would qualitatively change the outcome of our analysis.
Generally, I get accused of being either incompetent or manipulative by simplifying. So here, we’ll answer that. So if you think I oversimplified inappropriately, here we’ll make sure we don’t do that, by taking the full complexity head on, and not shirking a single detail. So buckle your seatbelt.
Regarding the grid, I’ve often heard objections such as: “It’s not that simple. What about the intermediates between no action and all-out action? What if climate change is happening, but we’re not the ones doing it? What if climate change is happening, and we’re the ones doing it, but our actions don’t stop it? Or they make it worse? Don’t we need more columns and rows to account for all of those possibilities?”
Okay, those are all valid, but before we explore them, I’ll point out that if you first watch the videos “The Mechanics of Climate Change,” “Scare Tactics,” and “The Solution” you’ll probably see how unfeasible those last three scenarios are—that is, how clear it is that we are the ones doing it, and that action would be only beneficial—and you might no longer be concerned with the need to include them as rows before using the grid to draw a conclusion about what to do.
Also independent of whether the science I explained in those three videos allays your concerns, the video “Risk Management” points out that the top scientific organizations in the world have publicly and explicitly said: yes, the globe is warming, yes, humans are the ones doing it, and yes, our actions will have an effect, but we’d bettter get on it quick. So the short answer to the objections is: who are you and I to argue with the top scientists about the science?
But, some of you still don’t trust the objectivity or competence of those scientific authorities, so we’ll take on all those “what if’s” head on, and include them in our pathetically oversimplified grid. Here we go.

[At BOARD, big GRID] Holy sh*t, it exploded!

Across the top we’ve got five columns representing five different degrees of action, from all-out to status quo. Down the side, GCC stands for global climate change, A stands for anthropogenic, or “caused by humans.” T and F are for AGCC ending up being true or false, and we’ve got the effects of our actions on the climate—positive, negative, and no action.

So we’ve got scenarios that range from:
GCC false, but our actions negatively affect the climate
GCC false, climate not affected
GCC false, climate positively affected
GCC true, but not A, and actions cannot affect climate
GCC true, but not A, can be negatively affected
GCC true, but not A, can be positively affected
GCC true, A, can not be affected
GCC true, A, actions negatively affect climate
GCC true, A, and our actions positively affect climate

Into each of these 45 boxes we put our different economic, environmental, social, political, and public health scenarios. If you recall our “expected value” discussion from the video “Risk Management,” you might think we would then assign to each box a number to represent the consequence if that scenario happened—in this case, the cost to us. Not just the economic cost, but some sort of quantified measurement of the various forms of suffering or benefit.
[DESK] But if you remember in that video, I pointed out how each box actually contains a range of possible consequences, and that to simplify our expected value calculation, we purposefully neglected to take into account that range, and instead just took the feasible worst-case scenario. This led a number of people who looked at the simplified grid to claim that column B was the better bet, because they forgot that was just a simplification, and therefore they assumed that choosing column A doomed us to economic harm, no matter how the truth of global climate change played out.
But, now that we’re unpacking that simplification, it’s clear from what I shared in the videos “Risk Management” and “Get What You Want,” choosing column A only brings with it the POSSIBILITY of economic harm, not the certainty. As you saw in those videos, long and conscientious searching on my part turned up exactly zero economic doomsday scenarios from credible sources. All the economic doomsday stories turn out to be simple conjecture from people at the very bottom of our credibility spectrum. And in fact, a number of quite credible sources, including industry leaders in the US Climate Action Partnership, assert that column A quite likely leads to economic growth. So, that should get us over our economic phobias surrounding column A and the boogeyman of government action.
[BOARD, BIG GRID] So if we’re sincerely trying to not oversimplify here, what we need to do gets a little complicated. Fortunately for us, the tool of expected value is scalable, and can be applied recursively. So we’ll go into each box, look at the full range of possible consequences—say in here from global depression all the way to wild economic boom—assign numerical values to each of those possible consequences.
To stay backwardly compatible with our previous oversimplification, let’s still represent consequences that cause suffering as positive numbers—the greater the magnitude, the greater the suffering or impact—and let’s set zero as neutral—no deviation from the norm. Counterintuitively, that gives us negative numbers for good consequences, like an economy boosted by innovation, but we can handle that. That’s why we’re here, instead of stopping at the oversimplified four-boxer.
So next, we’ll multiply each of the possible consequences in a box by the individual probability of that consequence happening, to give us an expected value for each possible consequence. Then we’ll sum up all those expected values of the different possible consequences in just that box to get the expected value of that box as a whole.
That will give us a single number we can then use as the consequence of that box (of course you’ll recognize that it’s really the expected value of the box itself). This replaces the assumed worst-case scenario we used before, which had confused some people into thinking that choosing column A doomed us to economic harm. So we’ve taken care of that problem.
Then we’ll calculate the expected value for the whole column, by multiplying the consequences of each box (again, really the calculated expected value of each box) by its probability, taken from the row, and sum up those nine products to get the expected value of the column. You’ll recognize that’s the exact same process of taking the sum of a series of products that we did in each box, illustrating the very slick recursive nature of the expected value.
Then we’ll move over and do that same process for each column, and the next, and so on. That will eventually give us an expected value assigned to each level of potential action, and we finally get the satisfaction of simply looking at five numbers and asking: which one is the closest to negative infinity? Because that will tell how how much suffering we can expect if we choose that column.
Recall that to stay consistent with our original four-boxer grid-for-the-masses, zero is neutral, positive numbers are suffering, and negative numbers are actually benefits, so the greatest benefit comes from the number that is farthest to the left on a number line. And remember, there are no guarantees, because there were probabilities of probabilities layered in here. But expected value is a well-proven tool, used by businesses all the time, and it’s the best we’ve got here. Okay, let’s get started. [Fake a start.]
Oh, and you’ll recognize, of course that the probabilities of all of our rows are going to need to sum to exactly 1, if we’re trying to be thorough and not neglect any scenarios. That one of course represents the fact that we a have 100% chance of something being true. So the absolute probabilities we distribute across these columns will also handily function as relative probabilities, as in “How much more likely is this row than this one?” [Fake a start.]
Oh, and one more thing. You know how we did that process for the whole range of possible economic consequences for a single box? We’ll need to do an identical process for each of the other factors besides economic, because there are probably things beside economic numbers that we might want to factor into our happiness, don’t you think?
But for our first time through, I’d suggest we limit the factors to economic, environmental, social, political, and public health scenarios, since those will be the easiest to quantify, and probably have the greatest bearing on our standard of living. At the end, if we have a close tie between two columns, then we can go back in and add some other factors to refine our answer.
So, let’s get going with assigning those numbers, because if we break each range of possibilities for each factor in a box into a reasonable 5 cases, that gives us five cases times five factors, times 45 boxes, or a little over 1100 numbers we’ve got to agree on to quantify consequences, and an equal number of probabilities to assign. You might want to go get an energy drink, cuz this may take a while. Ready?

A Manpollo Project’s mission would be to study the science, study the political economy, study the history, to not only come up with the whole range of possible scenarios, but to actually quantify each one. To come up with numbers for consequences—both positive and negative—and for probabilities, so that an expected value could be calculated that would end this tumultuous, ineffective political bedlam that surrounds the issue, which really should be decided by analysis, and not political rhetoric. The project would have to be well-respected enough by all that the public would place such confidence in it that we would all agree ahead of time to follow its recommendations, even if we didn’t like them. We would all feel confident that the answer recommended was the one most likely to get us what we want, regardless of our individual political opinions.
Because the physical world—which, in the end, is what this all is about—isn’t influenced by our opinions. It is only our actions which have impact. And currently, our actions are firmly in column B. If that’s going to remain the case, don’t you want to know—with as much confidence as you can—that that is the best place to be? Wouldn’t you rather be assured by a huge team of highly competent and unbiased experts, rather than going on your own armchair evaluation of what you’ve read or heard?
In WWII, if Germany’s threat threat to the world justified the Manhattan Project, why wouldn’t global climate change’s threat to the world justify a similar effort now? Just because it doesn’t have a mustache? Look, Hitler himself was undeniably real, but him developing the atomic bomb—which I understand is the threat we were reacting to with the Manhattan Project—was just a possibility. No one—no scientist or policy maker—knew for sure that such a bomb was possible. The scientific issue was uncertain. Yet we took action, in spite of that uncertainty, because the risks of not taking action seemed far greater. Just the possibility that Hitler might get the bomb was enough to justify all-out action. Why not here? Paying for a Manpollo Project is not going to be the end of the world as we know it. But not paying for one, might be.
Let’s get to it.

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