Carolyn Woodard explores why statistical analysis and evaluations are never neutral with Heather Krause, mathematical statistician and founder of We All Count.

Heather built her career doing statistical consulting, evaluation, and causal analysis in the global south, work that eventually convinced her that the widespread belief in value neutral quantitative analysis is a myth. In this conversation, she and Carolyn dig into why every statistical task, even something as simple as calculating an average, is really a series of choices, and why those choices are never neutral.

Using a deceptively simple classroom size example, Heather shows how the same data can produce two different, equally correct answers depending on whose experience you are measuring for, and why that matters far beyond the classroom. She and Carolyn also talk about a dairy cooperative project in Bangladesh, the discomfort people feel when the myth of neutrality gets challenged, and why transparency, not dumbed down science, is the real fix.

The conversation wraps with a candid look at how AI fits into all of this: it is not value neutral either, and understanding its hidden choices may be one of the most useful data literacy skills nonprofits can build right now.

Heather and Carolyn discuss:

Why statistics and the application of statistics are not the same thing, and how every calculation, like choosing an average's denominator, embeds a value judgment and takes a perspective.
A classroom size example showing how measuring from a teacher's perspective versus a student's perspective produces two different, defensible answers, and why the choice matters.
A dairy cooperative project in Bangladesh that illustrates how whose worldview gets built into a statistical model shapes what the evidence ends up being used to say.
Why transparency about the assumptions behind a data project, explained in plain language, builds more trustworthy evidence than technical jargon or hedged science.
Why AI models are not value neutral, how they can hide the choices they make, and how nonprofits might use AI to build more transparent, equitable data practices.

Resources Mentioned:

We All Count - Heather Krause - https://weallcount.com/
Bangladesh Women Milking Example and Equity in Evaluations - YouTube - https://youtu.be/8gYtTYc2M0U?si=AryCMmUsNTYq7YoW

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