It's just the author acknowledging all the code written belongs to some company or organization, and often, can't even be used as a showcase. It was work for money, plain and simple, but may become a hard sell later.
However, it's not necessarily true. Working with large codebases, working on language design questions, committees, everything grows experience that can be used later. It's just not clear now how, as requirements and work in other companies or in FOSS may be very different than that C++ development.
The author mentions Go as a positive experience. If the ego could be left at the door, Go could be a good language to make a new home in. Either that or Haskell, though with much more investment in all layers.
The language and tooling can have very much to say for overall development and maintenance. Also architecture and design matters, as well as changing requirements. It's all very simple or complicated, depending on unknowable X-factors that often need to be decided up-front.
It's complicated. CO2 and other greenhouse gases raise evaporated water concentrations and initial warming, which trigger several one-way thresholds that we can never undo. It gets complicated/impossible after each threshold breakage, as warming will mostly drive itself and chaotic flux from there on.
Depends what it is. If it's something creative, this can become pretty much like writer's block. Ie. you know there's something you want or need to write, but it's such a huge task, it's hard to get down to it. This can lead to overindulgence in research and distractions.
One solution is to set yourself a goal to just do this one thing, to get started, and do that thing. No matter how bad, just make that draft, POC, whatever. Start breaking up things into smaller pieces, and set yourself to accomplish one piece at the time, no matter the state of results. Iterate on this to improve quality and scope, and keep your focus on the smaller, managable things, while getting more clear about the whole over time. If something is too much, just break it up.
Another take is how to manage your expectations and associations. If every time you visit the dog is to give it medicine, it'll become suspicious of you. So every time you visit your projects, make sure to leave room for some cuddle time, while making sure it's also supporting progress on that same thing. For very difficult goals, transform it into a spike and celebrate it no matter what the results. No matter what, you learned something new. You want to associate with progress.
Ideology fits pretty well, as the term is used in modern times.
In case of Linux, GPL is regarded as a good fit.
In case of games, it'd be surprising now, to see GPL as a good fit. Open source and GPL are not used predominantly, thus never disrupted much in that space. However, this is based on a kind of hindsight bias as well.
In many ways, Free Software is regarded a means by itself: To keep software Free. So the goals of the ideology might not ressonate with the goals of every game developer.
During crisis decade post 1999, many shifted to better pastures, not content with being played like pawns and having bleak outlooks. Now, many developers having regretted biting the bullet for two f. decades are thinking the same, after quite a bit of introspection during COVID. Not saying everyone will jump on the same: Some went to work in kindergartens, just sick of everything java. However, this situation is exactly the spark that'll make people seek more of what they truly are meant to do in this life.
The best advice I can give is, treat other people as you yourself would want to be treated, or how you think they wish to be treated. Be kind and seek the best in others.
1) Companies wants work done for free and managers heard some rumor "setting goals is good". Anyway, there's no choice for every party involved: Mythical work gets added in addition to work where employee is supported. This lets employees that are already supported to have another bragging list, while employees who are not supported are held down by yet another instrument.
2) Managers never heard of or actually been part of agility and teamwork.
Bribes functions as oil in the machinery of society, and empowers strong men against rampant decadence. So is working for good when it is sanctioned and goes to the right people and their agendas, comprising of: terrorist attacks, slavery, eugenics, facism, child labour, and of course sexism.
The best rebuttal so far has been to decline to comment.
However, without revealing names the paper outlines internal company matters, presenting opinions and tautology that do not fit proper format of professionally published research. Instead of reworking a flawed paper, the researcher escalated and exposed individual opinion, publicly. Such company representation is out of scope for research positions. As Google could not agree to terms of email, it was taken as resignation notice.
Modern ethical AI / ML, is both that and beyond that. Issues range vastly in how complex algorithms can be used, misused and misinterpreted. There are also issues of uncovering hidden biases, unfairness, manipulative effects, privacy issues, risk and impact analysis, explanatory AI, who is accountable for accidents and malicious acts, etc. The list goes on covering both the legal and the political. This may not be unique to ML / AI, but is harder to quantify and prove, with more prevalent usage of complex algorithms.
My strongest argument is AGAINST managers at Google getting to micromanage, censor and to revenge-fire a researcher, just because they personally disagree with their published AI Ethics Research. A job said researcher was tasked with and leading.
Such behaviour, unless corrected, undermines Google's entire AI/ML and cloud operations.
Anybody may be susceptible to such ideology and short-circuited bias. However, technical people are often so focused on their details, we are probably even more vulnerable to this than most.
We haven't heard any arguments, only that management can do as they please when they don't like results of AI Ethics Research. We'll likely not get anything substantial, ever, either.
As I've stated in other post, this is very, very troublesome for AI and Google.
OTOH, Google has much emphasis on ethics in AI/ML otherwise. But the whole company, especially management, need to put actions in alignment with their words on this matter.
However, it's not necessarily true. Working with large codebases, working on language design questions, committees, everything grows experience that can be used later. It's just not clear now how, as requirements and work in other companies or in FOSS may be very different than that C++ development.
The author mentions Go as a positive experience. If the ego could be left at the door, Go could be a good language to make a new home in. Either that or Haskell, though with much more investment in all layers.
The language and tooling can have very much to say for overall development and maintenance. Also architecture and design matters, as well as changing requirements. It's all very simple or complicated, depending on unknowable X-factors that often need to be decided up-front.