On the one hand, applying valid generalizations is not bias. On the other hand, when dealing with individuals, one rarely has to rely on generalizations. On the gripping hand [1], treating individuals fairly can <i>look</i> like bias when iterated over a large enough sample size.<p>The solution: be rigorous about treating individuals fairly, be willing to apply valid generalizations <i>cautiously</i> and <i>only when necessary</i>, and remember that seemingly biased results might simply be reflecting real differences between groups. (This last point can be grokked by meditating, Zen koan–like, on the question &quot;Are women underrepresented in the NBA?&quot;—a question to which both the answers &quot;yes&quot; and &quot;no&quot; are defensible.)<p>[1]: <a href="http:&#x2F;&#x2F;catb.org&#x2F;jargon&#x2F;html&#x2F;O&#x2F;on-the-gripping-hand.html" rel="nofollow">http:&#x2F;&#x2F;catb.org&#x2F;jargon&#x2F;html&#x2F;O&#x2F;on-the-gripping-hand.html</a>