It's 5 years. Outlined in the link below
Reasonable seeming concerns, but you have to start somewhere to learn anything.
It's less costly than rushing into BI. It's one of those social programs that once introduced can NEVER be taken away.
You might think that, because no country has implemented BI, then considered it a failed project, then scraped that system for something better, yet. But one of the countries on this planet might be the first to try that. It's one of those "nobody done it yet thus it can't be done by anyone" ideas that reality so often find is false.
It may work, it may not. But what we're (the US) doing now isn't working.
[1] Though from the same people you'll hear that work provides so much meaning to life that if people aren't working because they can live without it that they'll just be miserable. Which seems to contradict itself, either work is so meaningful that without we're miserable so we'll work even if we don't have to. Or it's not that meaningful and we'll be fine without it.
Yes, you do. BI will change mating patterns and child-rearing patterns and the consequences of those changes will not show up for a generation or two.
This is a dangerous thing to experiment with when you have a huge nation of 318+ Million population.
It's far safer to let smaller nations, like Finland (whose entire population is less than New York City), test this idea out for a few generations. It's far easier to "bail out" a city's worth of people than it is a large nation, if things don't go as planned.
I don't think a city in the US is a good sample, since people are more likely to move in and out of the city during a generational (or multi-generational) test case. In addition, city lines/boundaries are "fuzzy" a lot of the time, often with one side of a street being incorporated and the other side not, etc. City boundary lines may also shift over time, etc.
In addition, if it's known anyone with an Oakland address gets BI, some (or many) people will attempt to move there, which will cause other unintended economic consequences for the city, skewing the test results.
A [small] nation is a better sample, since it tends to have fewer of these issues over a long time span.
I think that is the point of this pilot -- find the problems that crop up.
Your own argument is that it should not be done wholesale until we know what the effects are at a smaller level: that's what's being done here.
Start small. Fix smaller problems. Ratchet up. Rinse and repeat.
- The sample subjects are incredibly biased, in that they are already founders and presumably motivated individuals. Not a representation of the general population, not even close.
- The study has a time limit (5 years). So no test subject is going to make life-long or life-altering decisions based on this limited trial.
So, this study doesn't seem to accomplish any of the basic tasks needed to study ramifications of such an idea in practice.
All we will know after this study is concluded, is how founders treat monthly cash given to them for 5 years. In reality, it sounds a lot like YC is just paying them a salary to build their business.
YC is testing the outcome of paying their founders a salary in order to achieve greater gains down the road... something any business will attest to being beneficial. This is not a BI study.
I agree, start small, work up. This is why I said let a small nation conduct this test (such as Finland, who is already planning to convert into a BI economy full-scale, from my understanding).
> But you are just guessing at what the problems might be.
No, the issues listed in my previous post are clearly issues with conducting this test at a city level. Part of preparing a study is to examine complications that may impact the findings... and these are obvious complications.
So you are implementing a lottery.
Why not examine existing lottery winner stats? It's essentially identical to what you are doing.
I still fail to see what anyone gains by this "experiment", except for some good PR for YC.
Not to mention, you opted to use a brand new PhD, instead of (or under the supervision of) someone more established and experienced. For this work to be taken credibly, it must have weight behind the research.
If this thing was really just about gathering data, you would have just done it... not wrote-up a blog post about it, posted it to HN, and then spent hours defending it.
It would be interesting to see how many people are lazy for the first 4 years and then get their shit together in the 5th year.
It will be more something like "sabbatical" in academia - you can devote a time to some side projects (whether career related or pure leisure), but everything you'll do you'll do with considerations of how your life will proceed once the sabbatical is over and there is no more safety net (assuming rational actors).
What happens after the money ends? They have to re-train, search for a job, apply, interview, explain a 5 years gap, climb the office/workshop ladder from the bottom again...
Situation changes radically if the income is guaranteed for life, if they are guaranteed to never have the necessity to work again.
Since a study limited to 5 years can't, by design, satisfy this last condition, it won't be significant at predicting how many people will leave a "hard" job.
Perhaps, when no longer totally living hand-to-mouth, during those 5 years they can e.g. take evening classes and eventually qualify for a better job.
Five years is much better but fundamental issue is still there - "there is a deadline after which the utopia ends".
Did you consider maybe using fewer participants but possibly much longer time-frames (e.g. for the same budget 10x less people but 50 years of BI, or even 20x less participants and 100 years of BI to have safe margin)?
I'm aware this would be hard / impossible to personally see to the full fruition (see e.g. Up series [1]), but even just that 5 years window frame for the observation and research (which you already prepared yourself for) but with participants who could have "piece of mind for the rest of their lives" could radically alter the results of the experiment.
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