“Everything would be easy if it weren’t for people.”
“Well – I’m not sure that I feel the same way” I thought to myself while sitting in my second-level supervisor’s office. What about technical problems? Surely, I thought, tasks such as data analysis and solving technological problems would never be easy, even without people; What challenges could people possibly present that are difficult to solve in a similar sort of way? As I’m sure you already suspect, I have come to realize that these questions & reasonings were naïve.
It’s been about a year since this conversation happened, and it’s been a little more than that since I started working here. To say that I’ve received a masterclass on the broad topic of “people” is an understatement. Though, I would like to note that although my original conclusion was naïve, I do not think it’s fair to deem it as completely incorrect. It was, like anything, based my understanding of “the facts” and how I reasoned with them. My reasoning for doubting the challenge of ‘people’ was as follows: answering scientific/engineering questions is seldom easy. This makes sense, as anything left unanswered is likely challenging, especially in an established and long-standing industry such as mining. The core tenets of managing people have been long developed and commiserated, but science is still evolving. However, what I’ve learned that it is not really fruitful to compare the entities that are ‘technological challenges’ and ‘people’ in this sort of way. They are different, obviously.
Looking back, I’m not sure why I ever supposed that contemporary technological challenges would decidedly be more difficult than people. As a scientist, I know we have general methods and systems in place to analytically evaluate physics problems (based on what is currently accepted as the scientific method). The scientific method is certainly imperfect and ever-evolving, but it has some semblance of structure and is helpful identifying the things we do not understand. We come up with a question, we form a hypothesis, we develop a method to test our hypothesis, we observe & analyze, and then we confirm or deny our hypothesis using evidence. Our hypotheses are informed by our theoretical models and analysis. At work, I find myself using the heuristics informed by the scientific method (as it pertains to physics) to understand technological challenges – but rarely do they ever apply and prove to be effective methods for understanding people.
Of course, there is a science dedicated to the study of people – psychology. But I am not a psychologist, far from it; I am an engineering physicist, or something like that. However, as of late I’ve been doing more thinking on the topic of psychology, and I’ve come to realize that psychology and physics are very methodologically different sciences. In physics, there’s this joke about a spherical cow – it’s a metaphor which refers to how physicists reduce a problem to the simplest form available in order to make calculations more feasible, even though the simplifications render the model far less applicable to reality;
Milk production at a dairy farm was low, so the farmer wrote to the local university, asking for help from academia. A multidisciplinary team of professors was assembled, headed by a theoretical physicist, and two weeks of intensive on-site investigation took place. The scholars then returned to the university, notebooks crammed with data, where the task of writing the report was left to the team leader. Shortly thereafter the physicist returned to the farm, saying to the farmer, “I have the solution, but it works only in the case of spherical cows in a vacuum”
Physicists love to “spherical cow” everything for good reason – it is often an effective way of initially characterizing an unsolved problem. Once the simple model is complete, it can then be elaborated on and made more detailed as necessary. This can be thought of in the same way as how an artist will begin drawing a person with a faceless, naked stick-figure, then draw all the complicated & messy details such as hair, clothes, and face afterwards. For instance, consider the everyday electrochemical cell (battery). The way I learned about the applications of the electrochemical cell was by breaking it down to the smallest component. This manifested as one of my most frequently asked questions at work – “what are the electrons doing?”. This is likely not the best example – as the more I learn about electrons, the less I’m convinced that they actually exist. However, considering the behaviours of electrons (such as asking where they want to go and why) is a helpful way of turning a conglomerate of electrochemical substances into something tangible. After that, it was easier to consider the implications of the broader substances from the perspective of electrons – such as solid electrolyte interphases and corrosion of cathodes.
Spherical-cow philosophy may seem indolent and lacking rigor, but the discipline of physics would not have gotten this far without it. Identifying sound and reasonable approximations is a tremendously difficult thing to gauge, but a lot of physical systems are forgiving. Of course, there are systems that aren’t – classical simplifications don’t work for quantum mechanical systems, linear approximations tend to not work well in fluid dynamics, Euclidean space is a bad model when considering interactions near the edge of black hole. What has become increasingly clear to me is that people are similar to quantum mechanics, fluid dynamics, and black holes – they are not ideal candidates for traditional “spherical-cowification”.
In that case, let’s do the next best thing and try to spherical-cow the “why” of this. It becomes clear very quickly why people cannot become spherical cows upon asking the first question – what is the simplest mechanism that informs the behavior of people? Well, I’m certainly not qualified to answer this in any meaningful way, but I would suppose that a simple mechanism doesn’t exist in this case. Perhaps you could consider neurons sending electrical signals to each other as the most rudimentary mechanism of the brain (truly, “what are the electrons doing”) – but this becomes infinitely complex when you consider that there are tens of billions of neurons of all different sorts in the brain, which all interact amongst each other – Moreover, their configurations are dynamic and no two brains are the same. How on earth does one even begin to spherical-cow that? There are disciplines such as Artificial Intelligence dedicated to replicating human behaviors & intelligence in this sort of way, but even with all of the world’s computing power and expertise, we have not yet found a way to completely model the brain.
From my understanding, most of what we know about human behaviour has been outcome-based. It is most useful to study the behaviour of a large amount of people and infer future/existing behaviours from the outcomes of previous results – Which, as someone with a physics background, seems to set off some alarms to do with the induction problem and blah blah blah. It is prudent in this case to remind myself that perhaps the induction problem is something worth ignoring in the case of human behaviour – I suspect humans haven’t changed much in recent years. Regardless, the behaviours of a collection of humans cannot be inferred from the behaviour of one – and the behaviour of one is not something worth trying to model analytically. The only way to know more about a person is to just spend time with them – and even then, you may be surprised.
Perhaps you may think that I’ve analyzed my second-level supervisor’s comment to an unnecessary degree, but it’s a point that I think about quite often that is increasingly pertinent. What is baffling to me is that there are people who I feel are good at understanding others. How could anyone be good at understanding anybody else when we are not able to be analytically modelled in any meaningful way? How can I ever manage people effectively if I do not understand them? Is it possible for me to move up in the company without managing or interacting with people, ever? I would hope so – but something tells me that this isn’t feasible. People are complicated which is equal parts exciting and terrifying – although, it is encouraging to remember that I have never shied away from a problem on the basis of it being complicated.
(July 12th, 2021)
astronomine 