There&#x27;s certainly times when a certain demographic gets in more. Although, your second contrived example (Hooters) fails too as many are A-cups that use pushup bra&#x27;s. Learned that from many ladies that worked at many of them and the ones with smaller tits often outperformed. Once again, you&#x27;d have a less qualified (and profitable) worker if you judged Hooters girls by actual Hooter size. I can&#x27;t even remember a good one with D size at last one I went to. The best were cute but got results on straight-up personality: making it fun for their customers and making them feel like the center of the universe. Customer service 101.<p>Anyway, back to what I think your point is. There are two ways of looking at the quota perspective. One is that it&#x27;s wrong because you get unqualified people and it doesn&#x27;t change anything. The other is that a version of it is necessary because otherwise nothing will change. I still go back and forth on the issue myself other than a few points: clearly don&#x27;t hire unqualified or way less qualified people just for a quota; ensure people get why it exists to reduce inevitable fighting internally; have reasonable cut-off points for applying it (eg 30% women is OK).<p>All that said, we&#x27;ve had many decades of attempting the default method you mention. The result was&#x2F;is systematic discrimination across the board. The OP&#x27;s Silicon Valley numbers of potential vs hired is a good example. Navy was a perfect example. I also remember a clever experiment where the same great resumes were sent to companies in cities all over the us. Identical resumes different only by the name: one obviously white and one black. The whites got calls 70% of time on a good resume. Rednecks were expecting Blacks to get maybe 60% or something with a little discrimination. Try <i>30%</i>. We&#x27;re talking same great skills and background... <i>just the name</i> was enough to disqualify. At this level of bias, the solution isn&#x27;t going to be popular, clearly not spontaneous, and will likely involve quotas or something. It has to be rather forced because there&#x27;s no attempt to do it willingly. Quite a statement in itself given talent they&#x27;re denying.<p>The overall result is that people aren&#x27;t finding whose best for the position. There&#x27;s actually little evidence to support that they ever did. The data shows that people, maybe you or maybe not, pick who they feel is the best fit for their organization and the best for the position. If your white or male, the &quot;best&quot; candidate is likely to be the same even if the others would objectively outscore them &amp; do a good job. This goes on even when we present objective criteria proving a superior candidate, skill, etc: they just make excuses for decision. Preaching didn&#x27;t work. Showing the extra profit and competitiveness didn&#x27;t work. Showing companies that did this were <i>ON TOP</i> didn&#x27;t work. What&#x27;s next outside initiatives such as quotas <i>FOR QUALIFIED PEOPLE</i> in other demographics? (Emphasis to be clear if I haven&#x27;t as I don&#x27;t want unqualified people at all.)<p>Self-driven model doesn&#x27;t work because few will do it. So, we need something else. It&#x27;s why I&#x27;m exploring data-driven methods as a potential alternative to straight quotas. I&#x27;m also calling out Silicon Valley on being able to systematically, analytically, and technologically solve everything except getting people from a talent pool without discrimination. There&#x27;s gotta be good tactics in those bright minds. If nothings happening, it&#x27;s because whoever is in charge doesn&#x27;t WANT it to happen.