The epistemic dominance of positivism within the Effective Altruism paradigm constrains its truth-seeking potential by marginalizing non-positivist forms of knowledge.
Positivism asks: What is true, measurable, and generalisable? Within this frame, Effective Altruism privileges phenomena that can be quantified, compared, and optimised. What cannot be measured is not merely sidelined but often treated as epistemically inferior or irrelevant.
German theoretical physicist Werner Heisenberg, Nobel laureate for his foundational work in quantum mechanics, explicitly rejected positivism:
“The positivists have a simple solution: the world must be divided into that which we can say clearly and the rest, which we had better pass over in silence. But can any one conceive of a more pointless philosophy, seeing that what we can say clearly amounts to next to nothing? If we omitted all that is unclear we would probably be left with completely uninteresting and trivial tautologies.”[1]
Heisenberg’s critique points to a basic flaw in positivism: when clarity is achieved by cutting away what cannot be neatly expressed or measured, the result is not deeper truth but a thinner, more trivial understanding of the world.
Non-positivist traditions are plural (anti-positivism, post-positivism, postcritique, etc.) rather than unified. They include interpretivism, hermeneutics, constructivism, critical theory, historical/genealogical analysis, indigenous or situated knowledge, and many more.
What they share is a rejection of the idea that reality becomes fully knowable once it is rendered measurable. Knowledge is understood as partial, situated, historically contingent, and shaped by language, institutions, and power. Measurement is treated as one way of knowing among others, not as a privileged filter that separates “real” knowledge from the “other”.
This also helps explain why I think EA tends to shy away from politics and direct activism. These domains are hard to measure cleanly. You can’t easily run counterfactuals on democratic backsliding, elite capture, or institutional decay. So within the EA paradigm, they end up looking messy, speculative, or methodologically unsafe.
But to me, this avoidance is a real loss. If you only optimise within existing systems and never confront how those systems are structured, you risk reinforcing them. It’s hard not to see this as part of the reason democratic institutions, especially in places like the US, have been hollowed out while plutocratic power keeps consolidating.
One text that really shifted how I think about linear things like “technology” is Langdon Winner’s Do Artifacts Have Politics? Winner’s point is simple: technologies are never just technical.
The epistemic dominance of positivism within the Effective Altruism paradigm constrains its truth-seeking potential by marginalizing non-positivist forms of knowledge.
What is positivism and what are some examples of non-positivist forms of knowledge?
This is probably a simplification but I’ll try:
Positivism asks: What is true, measurable, and generalisable?
Within this frame, Effective Altruism privileges phenomena that can be quantified, compared, and optimised. What cannot be measured is not merely sidelined but often treated as epistemically inferior or irrelevant.
German theoretical physicist Werner Heisenberg, Nobel laureate for his foundational work in quantum mechanics, explicitly rejected positivism:
Heisenberg’s critique points to a basic flaw in positivism: when clarity is achieved by cutting away what cannot be neatly expressed or measured, the result is not deeper truth but a thinner, more trivial understanding of the world.
Non-positivist traditions are plural (anti-positivism, post-positivism, postcritique, etc.) rather than unified. They include interpretivism, hermeneutics, constructivism, critical theory, historical/genealogical analysis, indigenous or situated knowledge, and many more.
What they share is a rejection of the idea that reality becomes fully knowable once it is rendered measurable. Knowledge is understood as partial, situated, historically contingent, and shaped by language, institutions, and power. Measurement is treated as one way of knowing among others, not as a privileged filter that separates “real” knowledge from the “other”.
This also helps explain why I think EA tends to shy away from politics and direct activism. These domains are hard to measure cleanly. You can’t easily run counterfactuals on democratic backsliding, elite capture, or institutional decay. So within the EA paradigm, they end up looking messy, speculative, or methodologically unsafe.
But to me, this avoidance is a real loss. If you only optimise within existing systems and never confront how those systems are structured, you risk reinforcing them. It’s hard not to see this as part of the reason democratic institutions, especially in places like the US, have been hollowed out while plutocratic power keeps consolidating.
One text that really shifted how I think about linear things like “technology” is Langdon Winner’s Do Artifacts Have Politics? Winner’s point is simple: technologies are never just technical.
https://en.wikipedia.org/wiki/Physics_and_Beyond