'Fair & transparent' and 'blind' are two different things, and neither are subsets of each other. A 'blind' hiring process _can_ be akin to, faced with a dense

'Fair & transparent' and 'blind' are two different things, and neither are subsets of each other. A 'blind' hiring process _can_ be akin to, faced with a densely connected graph, focusing only on the most immediate causal relationships. I do agree that 'fudge factor's are clumsy at best, where all candidates are hired, and then an arbitrary number is added to candidates based on race/gender/etc. However, 'fudge factors' have already existed in history. For a completely different example outside of hiring practices: redlining[1] was an explicit practice of denying services/mortgages to city neighborhood based on its racial makeup. So, what now? There have been decades of racist 'fudge-factoring' in real estate and urban development. Is the right approach to fudge-factor the other way? Or is it to be 'blind' and to look purely at the financials of each individual/organization? Obviously this is a different scenario than hiring, and cannot necessarily be directly applied back onto hiring practices. However, we can separate out a) one way to correct for historical/systematic 'fudge factors' from b) whether or not this can apply to hiring. I would argue that yes, you need fudge factors to correct previous problems. It should be fair and transparent, I agree, but it will not be very clear-cut. In complex systems (densely connected graphs of causality), the only clear-cut processes are creating problems, or ignoring them. Fixing complex problems are always messy. [1] https://en.wikipedia.org/wiki/Redlining https://en.wikipedia.org/wiki/Redlining