Men and women are fundamentally different. So are white people and black people and autistic people and gay people and transgender people and conservatives and liberals and every other human being along every imaginable axis of discrimination. Some of these differences are cultural. Others are genetic. Others depend on environmental factors. These differences mean that some of us are inherently better at certain tasks than others. On average, men are better at spatial temporal reasoning, women are better at reading comprehension and writing ability, and psychopaths can sometimes be excellent CEOs.
Whenever I meet a programmer who insists on doing everything a certain way, the chances I'll hire them drop off a cliff. Just as object-oriented programming didn't fix everything, neither will functional programming, or data-oriented programming or array-based programming or any other language. They are different tools that allow you to attack a problem from different directions, much like we have different classes of algorithms to attack certain classes of problems. Greedy algorithms, lazy evaluation, dynamic programming, recursive-descent, maximum flow, all of these are different ways to approach a problem. They represent looking at a problem from different perspectives. A problem that is difficult from one angle might be trivial when examined from a different angle.
When I stumbled upon this anti-diversity memo written by a Google employee, I wonder just how dysfunctional of an engineer that person is. Problems are never solved by being closed-minded. They are solved by opening ourselves to new possibilities and exploring the problem space as an infinitely-dimensional fabric of possible configurations. You do not find possible edge-cases by being closed-minded. You find them by probing the outer edges of your solution, trying to find singularities and inflection points that hint at unusual behavior.
You cannot build a great company by hiring people who are good at the same things you are. Attempting to maximize diversity only comes at a perceived cost of aptitude if you are measuring the wrong things. If your concept of what makes a "good programmer" is an extremely narrow set of skills, then you will inevitably select towards a specific ethnicity, culture, or sex, because the tiny statistical differences will be grossly magnified by the extremely narrow job requirements. Demand that all your programmers invert a binary tree on a whiteboard and you'll filter out the guy who wrote the software 90% of your company uses.
If you think the field of computer science is really this narrow, you're a terrible programmer. Turing completeness is a fundamental property of the universe, and we are only just beginning to explore the full implications of information theory, the foundations of type theory, NP-completeness, and the nature of computation itself. Disregarding other people because they can't do something without ever considering what they can do will only hurt your team, and your company. Diversity inclusion programs shouldn't try to hire more women and ethnic groups because they're the same, they should be trying to hire them because they are different.
When hiring someone to complete a job, you should hire whoever is the best fit for the job. In a vacuum where there is a single task that needs to be completed, gender and ethnicity should be ignored in favor of a purely meritocratic assessment. However, if you have a company that must respond to a changing world, diversity can reveal solutions you never even knew existed. An established company like Google must actively seek to increase diversity so that it can explore new perspectives that may give it an edge over its rivals. They cannot select on a purely meritocratic basis, because all measures of merit would be based on what the company is already good at, not what it could be good at. You cannot explore new opportunities by hiring the same people.
Intelligent people value feedback from people who think differently than them. This is why many executives will deliberately hire people they disagree with so they can have someone challenge their views. This helps avoid creating an echo-chamber, which is the ultimate irony of a memo that's called "Google’s Ideological Echo Chamber", because scrapping the diversity inclusion programs as the memo suggests would itself create a new echo-chamber. You can't remove an echo-chamber by removing diversity - the author's premise is self-defeating. If they had stuck with only claiming that conservative ideologies should not be discriminated against, they would have been correct. Unfortunately, telling everyone they shouldn't discriminate against your perspective, which itself involves discriminating against other perspectives, is by definition a contradiction.
We aren't going to write better programs by doing the same thing we've been doing for the past 10 years. To improve is to change, and those who seek to become better software engineers must themselves embrace change, or they will be left behind to rot in the sewers of forgotten programs, maintaining rancid enterprise code for the rest of their lives. If we are unwilling to change who is writing the programs, we'll be stuck making the same thing over and over again. A business that thinks nothing needs to change is one ripe for disruption. If you really think only hiring white males who correctly answer all your questions about graph theory and B-trees will help your business in the long-term, you're an idiot.