baazaa
They're pretty close to completely de-anonymising the internet for UK citizens. Say they introduce an Australian-style social media ban for under 16s, then requires all social media to link their accounts to digital IDs for this verification.
Naturally the only remaining loophole is if a UK citizen manages to avoid being flagged as British ever by using a VPN, so I expect they will focus on that going forwards. Keep in mind the UK already arrests and imprisons vast numbers of people for speech offences, there's no slippery-slope argument here because the UK is already at the bottom of the slope as an ultra-authoratitarian anti-speech nation.
A) you're working on one of the hardest engineering problems in the world.
B) you've a track-record of failing to deliver with merely competent engineers.
But in the second case it's invariably incompetent management that's the problem.
I'd only lean towards intermediate variables if a) there's lots of smaller conditionals being aggregated up into bigger conditionals which makes line-by-line comments insufficient or b) I'm reusing the same conditional a lot (this is mostly to draw the reader's attention to the fact that the condition is being re-used).
If you look at the venn diagram of 'things people want to send' and 'things people are willing to spend years of approvals and networking headaches to send' you quicky realise why emailed (or sometimes even on a USB) CSVs are the lingua franca of government data.
They have a great faith in AI (which is understandable), but they're constantly realising that:
a) they don't understand any of the problems enough to even being prompting for a solution
b) the AI can explain our code but the manager still won't understand
c) the AI can rephrase our explanations and they still won't understand.
Traditionally middle-managers probably consoled themselves with the idea that the nerds can't communicate well and coding is a dumb arcane discipline anyway. But now that their machine god isn't doing a better job than we are of ELI5ing it, I think even they're starting to doubt themselves.
Unless you first diagnose why people dislike socialising nowadays you're unlikely to fix the problem. Enjoining people to 'invest' in relationships is entirely missing the point, people used to hang out with their friends because they enjoyed it not because they thought it was an investment.
Where I live there were long covid lockdowns and most people expressed relief about not having to go to parties and make painful small-talk with strangers. They were already forcing themselves to go to social engagements because they didn't want to be seen as a loser, but they weren't enjoying it. This is historically unusual, people didn't see socialising as a chore necessary to maintain one's mental health a century ago.
Every article on the issue though takes as its starting point that socialising is obviously great and there must just be small obstacle which prevents people doing more of it. IMO there wouldn't be an epidemic of self-diagnosed social anxiety / high-functioning autism / 'introverts who get drained by social interactions' if people were actually enjoying their social engagements.
As for why impartial news does so poorly in practice, it's often because it's utterly uninformative. 'Car bomb goes off in Kabul' is worthless info to 100% of the population, whereas the moment you try to contextualise it 'Car bomb goes off in Kabul, which is becoming more frequent, which suggests administration is lying about how well the occupation is going' then you're no longer impartial.
Journalists and editors have spent the better part of a century stripping all useful information out of their articles in an effort to be impartial. It would be much better if they instead aimed for a diversity of opinions than a mythical objectivity devoid of ideological bias.
Sounds like an educational system problem.
I find it very odd the need to blame phones for everything. POTUS probably can't read a serious novel cover to cover, few of the senior managers at my work can, these kids are all going to pass college despite not being able to do it, it's a basic question of incentives.
But I think if you look at modern light-rail projects there really has been such insane cost-inflation it wouldn't be worth covering the city with trams even with a much bigger budget. Also because such a large fraction of the price is admin etc., it creates a bias towards more expensive infra (heavy rail) because the paperwork overhead is similar either way so you get more bang for your buck.
But consider an example which can't be blamed on that. My city (Melbourne) has a big century-old tram network. The network used to cover the city, now it covers only the inner city because it hasn't ever been expanded. We can't expand it because it's too expensive. Why could we afford to cover the whole city a century ago when we were 10x poorer? With increasing density it should be even more affordable to build mass-transit.
Obviously people blame the latter example on declining state capacity, but I'm not sure state capacity is doing any worse than Google capacity or General Electric capacity.
Where I work in government we've stopped paying for important data from vendors (think sensors around traffic etc.) because the quotes are eye-wateringly expensive. But I've worked in data long enough to know the quotes probably reflect genuine costs, because data engineers are so incompetent (and if it's a form of pricing gouging it's not working because gov isn't paying up). So it looks like we're choosing to be in the dark about important data, but it's not entirely a choice.
Saying we can do stuff but it's unaffordable is imo just another way of saying we can't do stuff.
Whenever people see old systems still in production (say things that are over 30 years old) the assumption is that management refused to fund the replacement. But if you look at replacement projects so many of them are such dismal failures that's management's reluctance to engage in fixing stuff is understandable.
From the outside, decline always looks like a choice, because the exact form the decline takes was chosen. The issue is that all the choices are bad.
I live in Melbourne like the author and I certainly don't speak for the entire industry. But here's it's mostly government and banks and other enterprise where data is just a cost-centre so middle-management could say they were big on data science, which has since transformed into being big on AI.
There's no end-use for most of the work, there's no stakeholders, often the product being delivered will be a 'platform' of some sort and everyone outside the data area is afraid of sounding stupid by asking what that means (it doesn't mean anything). The result is entire services can go down for months at a time and no-one notices (and then when someone does realise management covers up the fact no-one noticed because it's embarrassing).
I'm trying to pivot out of data which IMO is a scam industry and thought I'd consider automating white-collar work. After all, there's a huge amount of excel-monkey work that can be trivially automated with scripts and I've done stuff like that before. But then I realise there's not even a job title for this sort of work, nor are there any firms in my country doing stuff like this. There's simply no demand whatsoever for process automation (I'm expressly not talking about automation engineers in manufacturing etc.)
It's not hard to see why. No-one's going to automate themselves out of a job, nor are managers going to automate all the people they manage out of a job because then they're also redundant. Often labour-saving innovations are brought-in by upstarts but business dynamism is low so there's not a lot of that happening. I can almost guarantee that a bank circa 2050 will look a lot like a bank now, short of some runaway superintelligence completely reconfiguring society.
'We're going to force workers into the office and hope they do some work out of boredom' is taken as a serious strategy because the average manager is mind-bogglingly incompetent. If you know how productive people are (i.e. your managers aren't morons), and you have incentives set-up (e.g. pay, promotions and hiring/firing is dictated by productivity), then there's no problem to solve. Workers who are more productive in the office will be forced into the office to meet standards, you don't need blanket rules.
One reason they persist in their insanity is everyone is an expert in giving excuses why their own team is too tied up with work to assist. Sure this reduces conflict over telling middle-management why their ideas are stupid, but in the long-run it's detrimental to the organisation to avoid explicitly hashing-out disagreements. Creating a culture where everyone lies to avoid hurting one another's feelings is not good.
I really don't see anything preventing someone who's been catastrophically incompetent at every job they've ever held becoming CEO or heading a department. This might explain why cognitive ability correlates much less with earnings judging by NLSY etc. than in the past.
Anyway it's very far removed from the Peter Principle.
I've never even worked at a place that does promotions. Sure if your boss leaves you can apply for their job but it'll be offered to externals as well and then you'll be compared to them as an external applicant, i.e. with resume + interview. Job performance doesn't matter, HR makes no effort to even measure performance beyond PIPing people who don't show up.
Weirdly when I mention this to colleagues, who know for a fact that's how things work here, they're surprised because they never noticed. Like everyone has a mental model of 'good workers get promoted' which is seemingly impervious to direct experience.
I've realised over time that everyone else who prefers the design-doc approach refuse to do work like this. There's just a whole class of problems that are too hard without prototyping.
A lot of data projects are moving and transforming data no-one cares about. They can fail completely silently, a manager can lie and say 'we've successfully built the data platform which is going to enable AI analytics' and it'll be like a misconfigured S3 or something. No-one's checking the end-product or even understands what it's meant to be.
Like why didn't anyone catch the issue with the logs? Because it doesn't matter, every data team is a cost-centre that unscrupulous managers use to launch their careers by saying they're big on AI. So nothing works, no-one cares it doesn't work, most the data engineers are incapable of coding fizzbuzz but it doesn't matter.
People always wonder why banks etc. use old mainframes. There's like a 0% success rate for new data projects. And that 0% includes projects which had launch parties etc. but no-one ever used the data or noticed how broken it was. I don't think a lot of orgs which use data as core-infra could modernize, the industry is just so broken at this point I don't think we can do what we did 30 years ago.
On another note, I've seen in government that there is an exponential growth in not just glue people but glue teams. Here the problem is obvious, the bigger an organisation is, the harder it is to ensure adequate communication between teams working in similar areas because there's so many teams to keep track of. Whenever a communication failure occurs, someone puts their hand-up to make a glue-team, a manager thinks 'this will fix this problem', and thus a new team is born.
Of course, the issue is that the glue-team that might now have resolved the miscommunication problem between teams a and b has now added yet another team to the org chart. The consequent increase in organisational complexity begets more glue-teams elsewhere, you have glue-teams to link to other glue-teams, the solution makes the problem worse, which leads to even more of the solution.
To avoid this run-away explosion in glue-teams I'd suggest two things. Firstly, the fact that cross-team communication is hard means it should be minimised, organisations should be as modular as possible. This is what bureaucracy originally meant, e.g. the delegation of power to Persian satrapies which meant they could act autonomously. Management schools often teach the reverse, thinking that the way to solve communication failure is to make it a strength by maximising the amount of cross-team communication resulting in endless proliferation of glue people and teams. If your organisation requires good information flow from everywhere to everywhere, it's built to fail.
Secondly, glue should be the last resort. How many communication failures are actually because teams don't have well-defined roles and so things slip through the cracks etc.? How many could be fixed by simple process changes (e.g. monthly catch-ups between related teams)? I'm with Schmidt, the less glue the better.
Instead the atmospheric and oceanographic modellers managed to identify their extremely fallible models with climate change as a thesis, and now half the population trusts those models far too much, and the other half is far too skeptical of global warming generally.