ACE Hides Evidence, Resulting in Unfalsifiable Metrics

Accurate as of: Jul 18, 2026

Note: The events discussed at the start of this article involved Vetted Causes, the organization that preceded Strategies First.

On November 8, 2024, an article was published that highlighted key problems with Animal Charity Evaluators' (ACE's) cost-effectiveness models. The article demonstrated that ACE's cost-effectiveness formula allowed charities to achieve a better cost-effectiveness rating by spending more money to achieve the exact same outcome. This rewarded inefficiency and penalized efficiency, which is the complete opposite of what cost-effectiveness is supposed to measure.

The main charity discussed in the article was Legal Impact for Chickens (LIC), who had received a high cost-effectiveness rating from ACE despite the fact they had zero favorable legal outcomes (and hundreds of thousands of dollars in expenses).

ACE's Response

Several weeks later, ACE admitted multiple key issues the article had identified. But rather than simply fixing their methodology, ACE started blocking more information from public access.

This prevents independent analysis of ACE's work, and makes many of their metrics unfalsifiable.

Example: ACE's 2025 Cost-Effectiveness Model for LIC

In 2025, ACE created a new cost-effectiveness model for Legal Impact for Chickens (LIC). According to this model, ACE's "Conservative" estimate is that LIC's work impacts 30.36 animals per dollar spent.

However, ACE provides no information about how this metric was calculated, claiming that it is "confidential."

This results in a noteworthy dynamic: before, the public could see ACE's cost-effectiveness model for LIC, and significant issues were identified. Now, the public can't see the model, so it is impossible for issues to be identified.

Closing Thoughts

When ACE hides evidence, their cost-effectiveness metrics become unfalsifiable, and donors are left relying on blind trust rather than evidence. In our view, this is even worse than ACE having transparently broken models, because hidden dangers are worse than obvious ones.

To receive updates when we publish new articles, subscribe to our newsletter below for free.