What Is Audit Bias?

A December 2020 poll showed 77% of Republicans believe widespread fraud occurred during the election; 35% of independent voters also said they believe widespread voter fraud took place. (Quinnipiac Poll)

False Claims of a “Rigged” Election. For months prior to the election, Trump primed his supporters to believe false and baseless claims about voter fraud, repeating falsehoods about mail-in ballots and declaring shortly before the election, “the only way we can lose, in my opinion, is massive fraud.” (FactCheck.org)

What Is Audit Bias?

That audit in Arizona, the one that assumes the election was stolen, when there is no evidence of voter fraud, the audit based on a conspiracy theory that has been discredited because there is no evidence to confirm a massive conspiracy to steal the election. You know, the audit that is paid for by taxpayers and mysterious private sources at the behest of Republicans?  That audit is likely suffering from confirmation bias—the tendency to interpret information in a way that confirms preconceptions—can seductively slip into an audit and derail its proper execution. Five pragmatic steps can help auditors avoid this pitfall and can improve decision making in other areas of the audit as well. (Babson College)

1. Take It All in; Don’t Jump to Conclusions

Treat the initial data-gathering stage as a fact-finding mission, without trying to understand the specific causes of any identified fluctuations.

2. Brainstorming: The Rule of Three  

If possible, identify three potential causes for each unexpected data fluctuation that is identified.

3. Flag It

When identifying potential causes of a financial fluctuation, take note of the specific information that triggered a hypothesis. Present those data to a colleague to see whether he or she comes up with similar explanations. If the explanations are different, the colleague has assisted you in expanding your hypothesis set. 

4. Prove Yourself Wrong

Once an initial set of hypotheses has been developed, it’s natural to seek out evidence that confirms these explanations. However, accepting evidence as support ignores the fact that the same evidence could also indicate a different explanation. In a similar fashion, it’s also common to subconsciously ignore contradictory evidence. 

5. Circle Back

After identifying your initial hypotheses, the next required step is to investigate the data further to determine which (if any) is the actual cause of the data fluctuation. While performing this investigation, additional information will invariably be analyzed to confirm or disconfirm these explanations.

And all of this is closely related to Confirmation Bias, the tendency to interpret new evidence as confirmation of one's existing beliefs or theories.