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How would the government decide who's a startup investor? The same way they decide what counts as a university for student visas. We'll establish our own accred

How would the government decide who's a startup investor? The same way they decide what counts as a university for student visas. We'll establish our own accreditation procedure. This part scares me. Accreditation boards are a bug, not a feature. Perhaps, like pg's idea, they started out as well intentioned. But today, their primary purpose is to erect arbitrary barriers of entries, thus propping of the salaries of professionals and the tuition of the schools. The tech industry is great because it is so isolated from politics and bureaucracy. I'd hate for that to change.

pg 18y ago
That is a worry. It would have to be super transparent. Originally I proposed a straightforward algorithm for deciding: to use Erdos numbers with Ron Conway as the seed. I took this out because I thought it was better not to go into this level of detail in the essay, but I'd advocate using something like this to decide who was a startup investor.
- indiejade 18y ago
  By definition these 10,000 founders wouldn't be taking jobs from Americans: it could be part of the terms of the visa that they couldn't work for existing companies, This is a good idea because the expected outcome of adding 10,000 new people to the "pool of workers" by existing companies would be to see an increase in unemployment claims (even though not all unemployed people would file). So by adding 10,000 Founder Visas to the pool of workers and then tracking the rate of decrease (or increase) of unemployment, a metric of immigrant-based job-creation startup foo could probably be determined.
- bradgessler 18y ago
  Sooner or later super transparency would turn into super opaque.
- bokonist 18y ago
  The point is you don't get to control the algorithm. When I interned in the Massachusetts State House, I sat through a meeting discussing the algorithm that decides how much state money each local school district receives. Now I'm sure you or I could come up with a quite elegant algorithm. But the actual algorithm was a complex beast that no staffer at the meeting could begin to understand. It was the evolved product of years of power struggles. In politics, the organized faction always trumps the general interest. Say Faction A is 1% of the population. The faction wants to preserve a barrier to entry that costs every voter $100 and nets each faction member $10,000. The members of Faction A will be single issue voters over the barrier to entry. But to the rest of the public, the issue is lost in the noise. Average Joe does not even realize how much the barrier to entry costs him, because no interest group will fund ads to tell him. Thus the politician always supports the faction in order to prevent the 2% swing. ( I've spent time in both the state house and Congress, and this is exactly how the decision making process works). The life cycle of any government policy ends up being the following: 1) Program is created to benefit the public good 2) The program inevitably directly benefits a small group - employees of the agency, contractors, etc. 3) The beneficiaries become dependent on the program. They organize in order to protect themselves politically. 4) In any policy battle where the interests of the beneficiaries collide with the public interest, the beneficiaries generally win. 5) As the beneficiaries win battles over time, the program ends up serving the beneficiaries at the expense of the public. This is basically the life cycle of every program that has ever come out of Washington. The once mighty NASA now only exists to provide employment to NASA engineers. The school system exists mainly to provide employment to teachers. The AMA exists to erect barrier to entries to the medical profession. Etc, etc. Your algorithm proposal is amusing because it is basically the same solution to the problem of corruption/factions that the progressives tried during the 20th century. The idea was that "scientific policy" based on algorithms and formulas, designed by academics and civil servants, could replace control by politicians. Needless to say, it was a miserable failure. A classic example of policy via algorithm is the creation of Nationally Recognized Statistical Rating Organization's who used algorithms to dictate which loans regulated funds were allowed to invest in. It did not take too long for Wall St. to figure out a way to structure the riskiest loans imaginable in ways that would pass through the algorithm. The rating agencies are a high profile example, but there are hundreds of other similar failures. In practice "scientific public policy" ends up being the worst of both worlds. It combines the downsides of algorithms (lack of intervening personal judgment when the algorithm gets gamed) with the downsides of politics (corruption/factional power struggles).
  - pg 18y ago
    I'm suggesting accreditation be decided by the investors themselves, not the government. Works fairly well for universities.
    - bokonist 18y ago
      Visas are issued by the government. All my criticisms still apply, even if the government delegates the decision to the investors. And no, it works terribly for universities ( or rather, it works great for the universities, terribly for the public). For example, the number of medical schools in the country has actual gone from 162 in 1906, to 129 today, despite a three-fold increase in population. The artificial barrier to entry created by accreditation constricts the supply of medical schools, resulting in higher tuition and higher medical costs. Or consider law schools. The cheapest law school in Massachusetts costs 38K per year for tuition. If you wanted to create new a law school as a startup, think you could create one just as good for much cheaper? I bet you could. It's not like law schools need expensive equipment. But you're not allowed to, thanks to accreditation laws. Accreditation started off innocently enough - it was just a good housekeeping seal of approval. But then the professional organizations managed to make it illegal to practice at all without a degree from the accredited institution. The bar associations lobbied for laws that made it impossible to practice law if you simply studied on your own and passed the bar, or if you went through a correspondence course. In 2008, Abe Lincoln is out of luck. Now he has to take on 150K of debt in order to practice law. History shows the slow is indeed slippery. What if your startup accreditation body follows the path the law schools, and in 30 years ends up lobbying Congress to ban all non-accredited startups?
      - pg 18y ago
        The corruptness of the university accreditation system only makes the threshold unnecessarily high. If that happened with startup investors, it would still be a great improvement over the current situation. Currently, there are zero investors whose money gets you you a visa. Expanding from zero to an unnecessarily small group would still be an improvement, even it if wasn't optimal.
- psranga 18y ago
  You rank applicants to the visa program by Erdos numbers? Is this the same Erdos number as http://en.wikipedia.org/wiki/Erd%C5%91s_number http://en.wikipedia.org/wiki/Erd%C5%91s_number? Or do you rank investors? In either case, you're ranking people based on WHO they know, not what they know. Worst kind of ranking possible (it keeps competent outsiders out).
  - pg 18y ago
    It's the investors who'd be ranked by Ronco numbers, not the visa applicants. And even there it wouldn't be based on anyone knowing anyone. If you invest in a startup that Ron Conway later invests in, you have a Ronco number of 1, whether he likes it or not.
  - deleted 18y ago
    [deleted]
Raplh 18y ago
Rather than ranking the proposal against some version of protection, I evaluate it in terms of: would more good stuff happen with the proposal than without it? Clearly it would. Clearly having SOME additional number of people admitted who are at least doing SOME version of a startup would be a positive step. The number of things that have to go wrong to make this proposal a net negative are unrealistically perverse and pessimisitc. If EVERY policy proposal is held to a standard of "we will only do this if there is NO CONCIEVABLE WAY of ever making it be bad," then no policy proposals would ever be implemented. Think of it like a business. It is better to do something that is approximately right in a non-optimal fashion then it is to do nothing until you are exactly right or, as the poet says, to optimize too early.

pg 18y ago

That is a worry. It would have to be super transparent. Originally I proposed a straightforward algorithm for deciding: to use Erdos numbers with Ron Conway as the seed. I took this out because I thought it was better not to go into this level of detail in the essay, but I'd advocate using something like this to decide who was a startup investor.

indiejade 18y ago
By definition these 10,000 founders wouldn't be taking jobs from Americans: it could be part of the terms of the visa that they couldn't work for existing companies, This is a good idea because the expected outcome of adding 10,000 new people to the "pool of workers" by existing companies would be to see an increase in unemployment claims (even though not all unemployed people would file). So by adding 10,000 Founder Visas to the pool of workers and then tracking the rate of decrease (or increase) of unemployment, a metric of immigrant-based job-creation startup foo could probably be determined.
bradgessler 18y ago
Sooner or later super transparency would turn into super opaque.
bokonist 18y ago
The point is you don't get to control the algorithm. When I interned in the Massachusetts State House, I sat through a meeting discussing the algorithm that decides how much state money each local school district receives. Now I'm sure you or I could come up with a quite elegant algorithm. But the actual algorithm was a complex beast that no staffer at the meeting could begin to understand. It was the evolved product of years of power struggles. In politics, the organized faction always trumps the general interest. Say Faction A is 1% of the population. The faction wants to preserve a barrier to entry that costs every voter $100 and nets each faction member $10,000. The members of Faction A will be single issue voters over the barrier to entry. But to the rest of the public, the issue is lost in the noise. Average Joe does not even realize how much the barrier to entry costs him, because no interest group will fund ads to tell him. Thus the politician always supports the faction in order to prevent the 2% swing. ( I've spent time in both the state house and Congress, and this is exactly how the decision making process works). The life cycle of any government policy ends up being the following: 1) Program is created to benefit the public good 2) The program inevitably directly benefits a small group - employees of the agency, contractors, etc. 3) The beneficiaries become dependent on the program. They organize in order to protect themselves politically. 4) In any policy battle where the interests of the beneficiaries collide with the public interest, the beneficiaries generally win. 5) As the beneficiaries win battles over time, the program ends up serving the beneficiaries at the expense of the public. This is basically the life cycle of every program that has ever come out of Washington. The once mighty NASA now only exists to provide employment to NASA engineers. The school system exists mainly to provide employment to teachers. The AMA exists to erect barrier to entries to the medical profession. Etc, etc. Your algorithm proposal is amusing because it is basically the same solution to the problem of corruption/factions that the progressives tried during the 20th century. The idea was that "scientific policy" based on algorithms and formulas, designed by academics and civil servants, could replace control by politicians. Needless to say, it was a miserable failure. A classic example of policy via algorithm is the creation of Nationally Recognized Statistical Rating Organization's who used algorithms to dictate which loans regulated funds were allowed to invest in. It did not take too long for Wall St. to figure out a way to structure the riskiest loans imaginable in ways that would pass through the algorithm. The rating agencies are a high profile example, but there are hundreds of other similar failures. In practice "scientific public policy" ends up being the worst of both worlds. It combines the downsides of algorithms (lack of intervening personal judgment when the algorithm gets gamed) with the downsides of politics (corruption/factional power struggles).
- pg 18y ago
  I'm suggesting accreditation be decided by the investors themselves, not the government. Works fairly well for universities.
  - bokonist 18y ago
    Visas are issued by the government. All my criticisms still apply, even if the government delegates the decision to the investors. And no, it works terribly for universities ( or rather, it works great for the universities, terribly for the public). For example, the number of medical schools in the country has actual gone from 162 in 1906, to 129 today, despite a three-fold increase in population. The artificial barrier to entry created by accreditation constricts the supply of medical schools, resulting in higher tuition and higher medical costs. Or consider law schools. The cheapest law school in Massachusetts costs 38K per year for tuition. If you wanted to create new a law school as a startup, think you could create one just as good for much cheaper? I bet you could. It's not like law schools need expensive equipment. But you're not allowed to, thanks to accreditation laws. Accreditation started off innocently enough - it was just a good housekeeping seal of approval. But then the professional organizations managed to make it illegal to practice at all without a degree from the accredited institution. The bar associations lobbied for laws that made it impossible to practice law if you simply studied on your own and passed the bar, or if you went through a correspondence course. In 2008, Abe Lincoln is out of luck. Now he has to take on 150K of debt in order to practice law. History shows the slow is indeed slippery. What if your startup accreditation body follows the path the law schools, and in 30 years ends up lobbying Congress to ban all non-accredited startups?
    - pg 18y ago
      The corruptness of the university accreditation system only makes the threshold unnecessarily high. If that happened with startup investors, it would still be a great improvement over the current situation. Currently, there are zero investors whose money gets you you a visa. Expanding from zero to an unnecessarily small group would still be an improvement, even it if wasn't optimal.
psranga 18y ago
You rank applicants to the visa program by Erdos numbers? Is this the same Erdos number as http://en.wikipedia.org/wiki/Erd%C5%91s_number http://en.wikipedia.org/wiki/Erd%C5%91s_number? Or do you rank investors? In either case, you're ranking people based on WHO they know, not what they know. Worst kind of ranking possible (it keeps competent outsiders out).
- pg 18y ago
  It's the investors who'd be ranked by Ronco numbers, not the visa applicants. And even there it wouldn't be based on anyone knowing anyone. If you invest in a startup that Ron Conway later invests in, you have a Ronco number of 1, whether he likes it or not.
- deleted 18y ago
  [deleted]

Raplh 18y ago

Rather than ranking the proposal against some version of protection, I evaluate it in terms of: would more good stuff happen with the proposal than without it? Clearly it would. Clearly having SOME additional number of people admitted who are at least doing SOME version of a startup would be a positive step. The number of things that have to go wrong to make this proposal a net negative are unrealistically perverse and pessimisitc. If EVERY policy proposal is held to a standard of "we will only do this if there is NO CONCIEVABLE WAY of ever making it be bad," then no policy proposals would ever be implemented. Think of it like a business. It is better to do something that is approximately right in a non-optimal fashion then it is to do nothing until you are exactly right or, as the poet says, to optimize too early.