bias | Campus Safe Words

TERM: bias
RISK LEVEL: High

Why It’s Risky

The term “bias” is heavily associated with DEI initiatives, especially in training programs focused on implicit bias, systemic racism, or institutional discrimination. Conservative-led laws like Florida’s Stop W.O.K.E. Act and Texas Senate Bill 17 explicitly prohibit public universities from compelling belief in or promoting concepts that suggest individuals are inherently biased based on race or other identity categories. Using “bias” in course outcomes, HR training, or campus communications may be perceived as ideologically driven and politically non-neutral.

Common Critiques

Critics argue that “bias” is often framed as a moral flaw or inherent trait, particularly in the context of race or gender, which they view as coercive and unsupported by conclusive evidence. Legislators have expressed concern that implicit bias training and related content presume guilt or perpetuate divisive narratives. Some see the term’s use as a tool for advancing a progressive worldview under the guise of institutional reform.

When It’s Still Appropriate

“Bias” remains appropriate in academic research or instruction when referring to methodological bias, confirmation bias, or documented social psychology findings. It is also suitable in law, journalism, or statistics when discussing impartiality, conflict of interest, or sampling errors. In these cases, the term should be clearly defined and used within disciplinary frameworks rather than as a call for behavioral change.

Suggested Substitutes

1. Perspective or viewpoint (when discussing opinions or judgments)

2. Influence or predisposition (for psychology or behavior-focused contexts)

3. Methodological error (in research or statistics)

4. Partiality (in legal or ethical discussions)

5. Preconceived notions (for general communication or education)

Notes:
Avoid using “bias” in employee training, institutional values, or student development goals without academic justification. When the term is necessary, clearly define its scope and grounding in scholarly or technical usage. Refrain from implying that bias is universal or identity-based unless directly citing research and including alternative viewpoints. Note that “bias” is commonly and appropriately used in non-political contexts such as statistical analysis, experimental design, and data interpretation—these applications are not politically sensitive and generally do not invite scrutiny.