Cause-blind solutions and the puritan sense of fairness

In social affairs, it very difficult to untangle multiple causes of a problem. Here is a recent example. Our DWF rates have risen during the pandemic. The causes are many and their relative weight is unclear. It could be that online modality is generally bad, or it could be that many of our faculty have not mastered it yet. It could be also what was happening in student lives: illness, family care, job losses, stress. Most likely, the decline in course completion rates is probably a confluence of these and other unknown factors. Disentangling the causes is a lengthy, and sometimes impossible process. True experimental studies are often impractical. The thing is – we will probably never know for sure.

Yet one can already hear opinions that, it was FOR SURE the modality, and we should all go back to what it was before. They assume that once you get students back to f2f classes, success rates will automatically improve. But we do not know if they will. We know anecdotally that some students have terrible time in online classes, while others actually prefer to stay online. We do not know how many are in each group, why they prefer one modality over the other, and whether their own explanations of their success or failure are correct. It may be the case that a student was depressed but blames Zoom for it. Or, a student aced all the courses online, but only because she or he stayed with parent, did not go out, and did not have to work at their part-time job as much. So, subjectively, they feel like the online instruction fits their style, while in reality it was something else. This is why surveys are not always helpful. We have no idea whether actual learning online is more or less robust than in f2f, and for which subjects, for which age groups, etc. The depth of our ignorance is so great that one actually has to study social sciences to appreciate it.

What happens if we jump into conclusion that is too closely tied to a presumed cause? We risk creating interventions that do not work. For example, we knew for decades that student engagement in campus life correlates with their academic success. Increasing extra-curricular activities seemed like a sure path to success. However, it is more likely that students who are more likely to engage are also more likely to be successful in classes. It is the king of all errors - confusing correlation and causation.

We should have robust hypotheses about causality, even thought we cannot test them properly. Having the menu of possibilities will help us design solutions that are cause-blind, which is to say, they are likely to work regardless of what primarily caused the problem. For example, designing more extensive incomplete policies would be an example of such a solution. It helps all students regardless of why they could not finish – because they were stressed, lost their job, could not cur it academically, were evicted from their apartment, or got high and lazy. These kinds of solutions will remove us from a moralistic assumption that only people who suffer at no fault of their own deserve help. Paradoxically, the intense interest in causality is fueled by the puritanic sense of fairness. The other approach is to help everyone, whether they deserve it or not. While in prevention, causality is important, in mitigation – not so much. Stop obsessing about the “why.”

Designed to Fail or A little Taylorism is OK, really

Let’s say you have a campus with 1200 non-academic staff. You want to launch a process where every one of them submits a form, and you approve it. Even if you think a most cursory review, plus 3-4 clicks, it should be at least 5-10 minutes for each. Assume an average of 7 minutes, although it Is better to pilot just a few and time yourself to see how long it takes in the field. We then have 140 hours of non-stop work. Further, let’s estimate that 10 percent of them forms will be problematic and need some communication, further review, or an email exchange. If you assume none of them will be problematic, you probably do not need a review at all, right? Well, let’s allow 180 hours just to be safe. People take breaks, they have to answer other emails, or take care of left-over business. Do you have five people and time on their hands? Will you make sure their schedules are completely cleared of everything else? If yes, congratulations, you are a good manager! If not, you just created another Designed to Fail (DTF) processes. Hope is not a strategy. You are likely to find yourself burning midnight oil, just frantically clicking through without reading, seething and looking for someone else to blame. If only those damned 10% idiots paid attention!

Or here is another example. You plan an event where about 200 people are expected. So you set up a check-in procedure, with about 5-minute worth of checking in. You know, with finding names on the list, giving some swag, and showing where to go. 5 minutes tops per person. If 50 of them show up at the same time, and you only have two check-in persons, we can expect a two-hour long waiting line. Either have a lot more checkers or cut out something from your check-in sequence. If event is open, let them grab the swag and make better signs. Later during the event, send around the list, and ask to self-check. Do something, don’t hope it will somehow will sort itself out, because it never does.

Here is an example especially for faculty. If you have three sections of undergrads, at 30 students in each, and assign a 10-page final paper, with average of 20 min of grading for each, do your math. It is 30 hours of non-stop work, even without detailed written feedback. Grading is almost impossible to do for more than 8 hours a day; even that can give your brain an inflammation. It is because all papers tend to be similar and concentration eventually becomes very difficult. Even if you add music, wine, frequent breaks, etc. – do the honest, not hopeful math. Do you have four full days free from all earthly cares to do this work? If you, the DTF philosophy will get you to the same midnight oil, deep in regrets about your choice of career and a resolution to quit and go back to your happy barista days. You are not a hero you may think you are. You did not plan well.

Many people think Taylorism was a joke, a pseudo-science. OK, think what you want, but a little bit of it is a good thing. It is not rocket science. Do the honest math, do a realistic estimate of how much time a process takes. It is better to design a less rigorous but done well procedure than to put out some DTF monster. The latter is likely to make you look bad in the end and not accomplish its ambitious goas. Let’s use a little of the scientific management, just enough to keep us out of trouble.

Living with the virus, living with mortality

It seems highly unlikely that COVID will be eradicated like smallpox or polio. The current debate about continuing the restrictions or trying to live with the virus, is only a debate about when, not about whether. Some people believe it is now, while others think it is later. I don’t hear anyone arguing that the virus will simply go away on its own.

The problem is that it does not fit into our proud narrative of continuous progress. While we all understand temporary setbacks, the humanity does not know how to deal with permanent losses. For example, life expectancy in developed world has dropped. This feels a little like defeat, or perhaps a lesson on humility, or a reminder of our mortality. Not only individual people die, but there is no guarantee for our species to survive indefinitely. Many other species came to this world, and are now gone – what makes us think we are somehow an exception? For now, we are still kicking and doing well – a little less smug, a bit humbler, and not as many of us than before. At least 5,5 million people died because of the virus, 310 million are sick right now.

Learning to live with the virus is not just a pragmatic arrangement – which restrictions, for how long, etc. It is, to some degree, an adjustment of our attitude, a revision of the belief in steady progress, and some tempering of arrogance. Let’s learn to live with the virus.