You are taking diversity of thought comment, which I mentioned as an attribute of a team and trying to apply to an interview, which is not what I intended. Your interview processes need to ensure that you do not hire based on biases, so that you will have a diverse team.
Also interview processes are not just interviewer protecting against his/her bias, but also against bias of interviewee which seems to be somehow lost in these discussions.
Lack of diversity of thought is easy to spot IMO. Bigger point is - you should ensure your processes are setup to at least try to achieve the kind of diversity you would like to achieve. Those processes may still fail, just like anything else.
> Did this result in poorer job performance for the DevOps team, or any other negative business results that were specific to that team? If not, who’s to say which interviewing method was better or worse?
It did. And even if it had not in this particular case, it will hurt the company in the long run. There is not even a shred of doubt in my mind that diversity (of thought) is the best investment that leads to success.
I have been using scripted interviews, the same method I mentioned in original comment, for more than 5 years now, hiring more than 200 engineers in three continent and I am super happy with my results.
Having unscripted conversations is one of the best way to be swayed by unconscious bias in interviews.
Even though this advice sounds awesome, I will be cautious of putting it into practice without thinking through the bias problem.
I do remember reading multiple research papers on this, but unable to find them at the moment. From anecdote - In the last company I worked in London, only one team (DevOps) did not follow scripted interviews. It was the least diverse team, not just in terms of representation, but in terms of diversity of thought. Most of it was comprised of "tech-bros".
Scripted interviews do not mean you ask through a basket of questions. It just means that you stay within the guardrails of a set of topics and you go through all the topics. With in a topic, you have fair amount of flexibility. For example if you are hiring for a mid level Java programmer your topics may include - Java 8, Testing pyramid, Functional programming, type safety, developer safety(CI/CD/Rollbacks/Code reviews/Pair programming etc), some domain specific knowledge and so on.
I have tried using fakes over mocks, but it becomes cumbersome if it is a large-ish code base with handful of developers contributing to it. Keeping expectations on what a particular Fake does gets contentious. Mocks however usually allow a developer to encapsulate entire mock behavior within the boundaries of a unit test.
I am curious to know if you ran into similar problem, if you did how you managed to overcome it?
As a counter point, I was almost fired for not choosing to build a SPA for an internal app which was going to be used by 3-5 people, 5-10 times a month, if that many.
I worked at large accounting software provider, and internal billing system used static pricing which was changed once a year. The company wanted to move to a more flexible system where pricing can be setup based on few rules like customer type. For this the ui and backend system needed to be developed. Design I proposed was a single "monolithic" service which did everything including UI and UI was supposed to be a old style mustache templates and some minor jquery. Instead they went with pub-sub systems, 4 different microservices, a react based UI, api which used json-schema, even to send data back to UI. When I left a team of 6-7 people was working full time on this and they were about 20% done.
At least as per the wikipedia page[1], there is a lag of 2 years between product and company, and there prior history of him working on similar products. So I think it is reasonable to give benefit of the doubt that open source product was created in good faith and commercial interests only got explored later.
Most open source to commercial success stories like Kafka, Mongodb, and Elastic do seem to follow similar path.
Interesting but I doubt it. Vaanaras do not appear prominently in any of epics/puranas following Ramayana. Only Hanuman is present in Mahabharata and he is clearly living a solitary life when he meets Bheem.
I paid for bumble during the pandemic mostly to meet people closer to me who were looking for lock down buddies. Not a romantic or sexual relationship, but a platonic one using the BFF mode it offers. I did meet few interesting people around with that.
That is a fair question/comment. In my original comment "Limit use of automated content moderation only for easy to solve cases like child pornography." . It is reasonable to extent that list beyond just child pornography. I did not intend to give impression than this list is exhaustive.
In case of spam - Emails do show you spam emails, just hide them behind a spam folder. So instead of outright removal, it is possible to use similar techniques. And let users decide whether they ever want to see spam comments.
That link is pay/auth-walled for me, but I do get your point. Perhaps easy to solve was underestimate the technical problem as I was more thinking in terms of political problems. From that perspective no one, other than pedophiles themselves, disagrees with removing that kind of content. But completely agree on tech side of it.
I am only commenting on this in the context of community standards and user generated content and should not be extrapolated to all content in all other contexts.
My suggestion is to not indulge in any content moderation which is not illegal. Only take down content which is required by a court order. Limit use of automated content moderation only for easy to solve cases like child pornography.
Why?
It is fairly clear at this point that content moderation at internet scale is not possible. Why? A. Using other users to flag dangerous content is not working. Which users do you trust to bestow this power with? How do remove this power from them? How do you control it becoming a digital lynch mob? Can you have users across political, gender, other dimensions All mostly not solvable problems.
B. Is it possible to use machine learning? To some extent. But any machine learning algorithm will have inherent bias, because test data will also be produced by biased individuals. Also people will eventually figure out how to get around those algorithms as well.
The causality between content published on the internet and action in real world is not immediate. It is not like someone is sitting in a crowded place and shouting fire causing a stampede. As there is a sufficient delay between speech and action, we can say that the medium the speech is published in is not the primary cause of the action, even if there is link. Chances of direct linkage are fairly rare and police/law should be able to deal with those.
Content moderation, at least the way Twitter has been trying to do, has not been effective, created lot of ways for mobs to enforce censorship, and there is absolutely no real word positive impact of this censorship is. Only use of this moderation and censorship has been for right to claim victimhood and gain more viewer/readership to be honest.
Also note that these are internet companies and do no include myriad other software companies, including enterprise tech. So I am not sure if I agree with your concern on tech being reduced to 5-10 big companies.