It's light on content, but it's true and relevant. AI alignment must take inspiration from powerful human agents such as politicians and from superhuman entities such as corporations, governments, and other organizations.
The bank doesn't "keep" your house, they foreclose on it and sell it. Once they sell your home, any liens and associated costs are satisfied and the remainder of the money is given to the borrower.
No, any value outside of what is owed to the bank.
If you take out a 300k mortgage and pay it down to 150k principle then default, the bank sells it for 250k and gives you 100k (minus associated costs).
My "basis" is that reporting on the labor market in it's current form is flawed as the Fed themselves have stated that it's a lagging indicator on numerous occasions.
So is the fed wrong, or is this another sensationalized article in an attempt to garner clicks?
Big (and small) companies routinely make "data-driven decisions" based on obviously-faulty data collection, bad models, or misapplication of statistics. It rarely takes some crack scientific mind to spot it, either. But they want a decision now and doing it right might take a lot longer or cost more, or the correct model might be a lot fuzzier and that makes them uncomfortable, or they've got some notion in their heads already and they'll be damned if mere numbers are going to get in the way of that, so everyone in the room's just supposed to nod along when the blatantly-biased graphs come up on the Power Point suggesting (erroneously) that we do X.
The business world runs at least as much on bullshit as the most cynical among us might think, I'd say. It's not half as clever or competently-run as one might hope, certainly.
It's a cliche that front-line workers have a better understanding of customers and products than the c-suite and that this leads to predictable blunders, because that's often true.
(I'm also not sure I'd call Reddit a "giant corp", but that's beside the point [EDIT] and anyway, to be fair, this particular discussion isn't just concerned with Reddit)
Reddit is far from giant in terms of employees or revenue, and you'd be surprised at how many dumb decisions and how much money is wasted by startups that have raised hundreds of millions of dollars. You really shouldn't assume competence in situations like these, especially when Reddit has recently been making a bunch of terrible long term decisions to try and juice their numbers in the short term for IPO
I think the problem is that people read the analyses that companies share publicly (e.g., in a press release or earnings call), and they assume that that's all they did.
You should assume that any numbers shared publicly are just the tip of a giant-ass iceberg and that there were probably 10x more analyses going on internally that weren't shared.
The thing that ultimately gets shared publicly is whatever avoids using advanced stats or internal jargon; They want a single soundbite, not a scientific paper with a full methods section.
Story time: Worked at a large multinational, and 6-7 years ago they decided they had to ape into the whole “data science” gold rush. They spent millions of dollars on hardware, software, salaries, and consulting.
After a year with not much to show for it, the VP for the silo starts to put out kudos for the team for break-even revenue impact. However, behind the scenes, the insight they were taking credit for was a common sense idea that had already been in the e-commerce team’s backlog.
Nothing surprises me when a company says that they’ve run the numbers.
i think that many business get lured into doing data-science because they think that math/stats powers grant borderline-mystical powers and that they can be used to peer into a data warehouse and create ideas/business strategies that no mere mortal (i.e., people with domain expertise in business) could have dreamt up.
But... most businesses aren't that complex, and people can usually come up with really good common sense ideas for how to make improvements.
Data-science is often most effective when it serves less as a visionary idea-maker and more as translator that helps common-sense ideas become real (optimizing values, figuring out the best roll-out strategies, building forecasts).
Me too. Reddit almost certainly ran those numbers.
They might have chosen to ignore them. They might have fed biased assumptions into their calculations. Project management might have messed up and deprioritized the features meant to placate that section of the userbase. Institutional churn might have resulted in the corporation forgetting that they ever did run those numbers or why they are now heading down this path.
Having worked at some quite large companies: yes, it happens for real that they do not do stuff like that. It is likely that some team obviously has ran the numbers but that does not mean they made it to the people who made the decision.
People really think a giant corp acts a monolithic entity with perfect distribution of knowledge and ability and the stupid actions of dumb individuals will always be stamped out rather than amplified.
Same here. The fact that a usually "tasteful" company like Apple decided to demonstrate VR intruding into our life in this way, makes me somewhat worried about the future.
By comparison I suddenly find something like the Valve Index and the emphasis on gaming, much more benign.
I really see it as an evolution of the problem with cell phone cameras. People will pay good money to sit at a concert, recording the concert on their phone (in crappy quality), rather than to actually live and experience the moment.
