As I’ve resumed listening to Brian Christian and Tom Griffith’s Algorithms to Live By (audiobook), I got to thinking about how to approach the timely topic of racism from a computer science (CS) perspective.
One of the big questions in the field of CS is whether a given problem is computable–i.e., solvable via algorithm. Subjecting racism to this approach might yield the following:
- Become aware of ethnic prejudice and bias
- Reverse said prejudice and bias
Of course, the devil would lie in the details of such a simple method. But basically, this is the “algorithm” (if any) that we should expect to follow to solve racism.
One note about 1: ethnic substitutes for racial given the science of race. This science suggests that humans differ genetically more within than across populations. (I can’t find the article I found in 2015 detailing this study; this Wikipedia page is representative.)
People have recently taken to Audible and social media to learn all about racism–how not to be racist; what racism is…it is commendable. However, we shouldn’t ignore the biological underpinnings of the current social reality. Genetic race across ethnic/national groups has largely been concluded to not exist.
For anyone who believes microbiology is more fundamental than sociology, the mass’ current approach cannot work. What ought to be addressed instead is gut reactions (likely generational) to differing phenotypes from our own within certain, crucial contexts. If these reactions are understood, we can learn to convert them into more compassionate responses.