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The Nonlinear Library

The Nonlinear Library

Education

EA - Taking Uncertainty Seriously (or, Why Tools Matter) by Bob Fischer

EA - Taking Uncertainty Seriously (or, Why Tools Matter) by Bob Fischer

2024-07-19
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Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Taking Uncertainty Seriously (or, Why Tools Matter), published by Bob Fischer on July 19, 2024 on The Effective Altruism Forum.
Executive Summary
We should take uncertainty seriously. Rethink Priorities' Moral Parliament Tool, for instance, highlights that whether a worldview favors a particular project depends on relatively small differences in empirical assumptions and the way we characterize the commitments of that worldview.
We have good reason to be uncertain:
The relevant empirical and philosophical issues are difficult.
We're largely guessing when it comes to most of the key empirical claims associated with Global Catastrophic Risks and Animal Welfare.
As a community, EA has some objectionable epistemic features - e.g., it can be an echo chamber - that should probably make us less confident of the claims that are popular within it.
The extent of our uncertainty is a reason to build models more like the Portfolio Builder and Moral Parliament Tools and less like traditional BOTECs. This is because:
Our models allow you to change parameters systematically to see how those changes affect allocations, permitting sensitivity analyses.
BOTECs don't deliver optimizations.
BOTECs don't systematically incorporate alternative decision theories or moral views.
Building a general tool requires you to formulate general assumptions about the functional relationships between different parameters. If you don't build general tools, then it's easier to make ad hoc assumptions (or ad hoc adjustments to your assumptions).
Introduction
Most philanthropic actors, whether individuals or large charitable organizations, support a variety of cause areas and charities. How should they prioritize between altruistic opportunities in light of their beliefs and decision-theoretic commitments? The CRAFT Sequence explores the challenge of constructing giving portfolios.
Over the course of this sequence - and, in particular, through Rethink Priorities' Portfolio Builder and Moral Parliament Tools - we've investigated the factors that influence our views about optimal giving. For instance, we may want to adjust our allocations based on the diminishing returns of particular projects, to hedge against risk, to accommodate moral uncertainty, or based on our preferred procedure for moving from our commitments to an overall portfolio.
In this final post, we briefly recap the CRAFT Sequence, discuss the importance of uncertainty, and argue why we should be quite uncertain about any particular combination of empirical, normative, and metanormative judgments. We think that there is a good case for developing and using frameworks and tools like the ones CRAFT offers to help us navigate our uncertainty.
Recapping CRAFT
We can be uncertain about a wide range of empirical questions, ranging from the probability that an intervention has a positive effect of some magnitude to the rate at which returns diminish.
We can be uncertain about a wide range of normative questions, ranging from the amount of credit that an actor can take to the value we ought to assign to various possible futures.
We can be uncertain about a wide range of metanormative questions, ranging from the correct decision theory to the correct means of resolving disagreements among our normative commitments.
Over the course of this sequence - and, in particular, through Rethink Priorities' Portfolio Builder and Moral Parliament Tools - we've tried to do two things.
First, we've tried to motivate some of these uncertainties:
We've explored alternatives to EV maximization's use as a decision procedure. Even if EV maximization is the correct criterion of rationality, it's questionable as a decision procedure that ordinary, fallible people can use to make decisions given all their uncertainties and limitations.
We've explored the problems and prom...
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