Image: Kya Sands/Bloubosrand by Johnny Miller used with permission.

This is a guest post by Artem Kaznatcheev, a researcher in the Department of Computer Science at Oxford University and the Department of Translational Hematology and Oncology at the Cleveland Clinic. Artem also blogs as part of the Theory, Evolution, and Games Group. I’m pleased to have this post, which pushes back in a very interesting direction against one of my posts from last year. Read on!

At the end of last year, Stephen Heard wrote that he doesn’t work for the people that pay him. He wrote in his usual positive tone and focus. A positivity that has me coming back to this blog regularly. In particular, he pointed out that his work as an ecologist has a positive impact all over the world. Thus he is not working for the taxpayers of New Brunswick, but for people all over the world. He generalized this to all of scientific progress:

There’s an implicit global contract, I think, that having science progress is good for us, and that having universities helps science progress. Also part of this implicit contract is the idea that this is best done by everyone funding universities and setting scientists loose – rather than by New Brunswick funding a university with scientists who work only on New Brunswick problems, and likewise for other jurisdictions. The phenomenal progress of modern science, and its international connectedness, suggest that this implicit contract has worked very, very well.

He concluded with a reflection on the dangers of taking this global focus away from universities. And that he is unapologetic about not working for the people that pay him. Stephen was positive about the good that science does for the everyone, not just those that pay him.

But in this case, he found this positive tone by focusing on geographic divisions and geopolitical boundaries. He suggested that science often transcends these. I think this is probably correct, but — given my curmudgeon nature — I don’t think it is the most relevant division. I think the division that science tends to reinforce is class division. We tend to work (directly or indirectly) for the rich, and much less so for the poor or even ‘average’ (whatever that means). And as Johnny Miller’s Unequal Scenes project highlights (in the header image of this post), huge wealth and class inequalities can exist in the same geopolitical region with only a high wall, road or a patch of wetland as a boundary.

I wrote a long comment on this, and Stephen invited me to turn it into this guest post.

So here I’ll explain why I fear that although we don’t work for the geopolitical unit that pays us, we might work for the Class that pays us.

I am not familiar with the broader impacts of research in ecology, so I’ll draw from my own experience for an example. I don’t think my experience is that atypical, especially if weighted by the amount of funding handed out by granting agencies (i.e. taxpayers).

I work on mathematical oncology and the foundations of machine learning. Clearly, none of what I produce (if I produce anything at all) is geographically restricted. Anybody can get cancer, and computers are pretty widespread. Yet, much of the improvements to cancer treatment that are possible (way down the line) from my work, will be implemented in countries like the US; where access to treatment is clearly divided along class lines. The rich are usually able to receive these best treatments, while the poor cannot afford them. Or, more often than not, are killed by other diseases before cancer. So although my research might help cancer patients in Florida, Texas, Ohio, or Virginia… it will tend to help the rich more than the poor in all of those locations. And I don’t even have to mention the fact that this help usually ends up coming through the intermediaries of large pharmaceutical companies (although I try my best to avoid pharma-relevant work), that profit greatly from misery.

And the case can be even worse in less rich countries than the US. Here, Canada and much of Europe might serve as counter-examples to inequality in healthcare access; but if we’re going global then why should we only focus on western countries? To what extent​ is my work on cancer research helpful to people in less wealthy nations? Compared to say much less funded work on malaria, infectious disease, and air quality.

My contributions to foundations of ML are even more favouring to the rich. It is easy to convince ourselves that our ideas can be used to better humanity as a whole; that is what techbros advocate. But usually improvements in technology are first taken up and exploited by private companies for their interests. This way they can serve as a bottleneck through which funds are funneled to profit their shareholders. These companies tend to produce weapons of math destruction that often profit the rich and privileged at the expense of the poor and marginalized. We can pretend that indirectly the rising tide of knowledge lifts all boats; but that just seems to be an endorsement of trickle-down economics by other means.

Things don’t seem to be that much better when I turn my attention to teaching. Currently, I teach at Oxford, which is dealing with a lot of inequality of access. If you’re rich and privileged, it is about ten times more likely for you to get into this school than if you aren’t. I imagine this might be even worse at top private schools in the US; but at least they can try to hide behind being private and not funded directly by taxpayers (although they often clearly are funded by taxpayers, just indirectly). But even outside of top-schools, it feels like we’re creating an education bubble where everybody has to have (and pay) for a higher degree; instead of reforming secondary education to better prepare citizens for the world.

This isn’t made that much less depressing if I turn to indirect impacts of university education: the knowledge that my students bring to others in the community. I teach computer science, so many of my students will end up working for tech companies that make toys for rich people, or collect data on and find ways to exploit marginalized people; or they’ll work building code to help financial companies more ‘efficiently’ concentrate wealth. Of course, they’ll do this across the rich world; so we won’t see geographic boundaries, just class ones. And the few students that do achieve upwards mobility from the education that I help facilitate, will still deposit the indirect benefits of their mobility to the well-off, since those will be the people they are most in contact with once they’re at work.

Of course, the above might be particular to my discipline. As Stephen suggests in a comment response, other research areas — like climate change research — might be examples that don’t benefit the rich. That is certainly a possibility. And David Basanta adds that I shouldn’t be so fatalistic because my “job as a scientists is not only to add to [my] chosen field but to shape it”. In this way, I hope that my depressing comment does shape my field — or your field. If we critically reflect not only on the geographic regions we serve, but also on the class interests that we might be serving then we can be better equipped to transform our work for the better.

As scientists, we can be prone to think that science is good. Nobody wants to do bad. But I want to check if this belief in the good of science is a justified true belief. And if it isn’t — if the belief is a comfortable delusion — then maybe by recognizing that, I can find ways to do science in a way that is good.

© Artem Kaznatcheev August 27, 2018