It’s not the case that forecasting/prediction markets are merely in their infancy.
Counterargument: the internet had its theoretical underpinnings start approximately 1959-1960, with first grants for ARPANET in 1966-1969.
The whole thing was then not very useful until the 1990′s.
You could pick earlier dates for theroetical underpinnings of the internet if you wanted, too.
I think prediction markets are more similar to the internet than to cryptocurrency: they require a mix of technology and infrastructure but also a change in human habits. Theoretically, you’d always expect this type of very different systems technology to be a multi-generational thing before there’s widespread societal payoffs on it.
It’s not exactly a 1-for-1 comparison, but the similar date for prediction markets in a comparison to the internet is probably 1988 with the Iowa Prediction Markets. So, it’s been 38 years. It seems to me that it’s right on schedule to be a useful systems technology for society. We’re now in the “Wild West” days of it and it’s going to be messy, like when the internet was emerging into the mainstream.
I do agree about the “feels useful but isn’t” criticism — I got very into finding mis-priced bets and arbitrages on PredictIt a few years back. It can be a terrible time sink due to being so interesting and intellectually engaging. And the type of person who can do a good job at this (I’m one of them, not on your level but also pretty good) — is certainly capable of doing much more high impact work with that same type of cognition.
So I agree with that criticism on an individual level, but I don’t think it’s right to extrapolate that to the emerging systems technology. A cautionary note that if you’re a skilled forecaster it might be a dangerous time sink I’d fully agree with, but I don’t think it makes sense to throw the baby out with the bathwater as to whether this will have societal-level impact over time.
The utility of email, FTP, and remote login (Telnet) during the 1970s and 1980s repaid the original government grants in three primary ways:
1. Elimination of Duplicate Hardware Costs In the 1960s and 1970s, computers were multi-million-dollar mainframes. Prior to ARPANET, ARPA frequently had to purchase separate, identical computers for different research institutions. The network allowed a researcher at UCLA to log into and utilize a specialized mainframe at MIT. The cost of developing and laying the network infrastructure was significantly lower than the cost of buying duplicate hardware for every university the Department of Defense funded.
2. Accelerated Scientific and Defense R&D Email and FTP collapsed the time required for complex collaboration. Instead of mailing magnetic tapes or waiting months for academic papers to be published and circulated, researchers shared datasets, software code, and peer reviews instantly. This rapid iteration sped up advancements in computer science, aerospace engineering, and defense logistics, delivering immense strategic value to the military and government.
Counterargument: the internet had its theoretical underpinnings start approximately 1959-1960, with first grants for ARPANET in 1966-1969.
The whole thing was then not very useful until the 1990′s.
You could pick earlier dates for theroetical underpinnings of the internet if you wanted, too.
I think prediction markets are more similar to the internet than to cryptocurrency: they require a mix of technology and infrastructure but also a change in human habits. Theoretically, you’d always expect this type of very different systems technology to be a multi-generational thing before there’s widespread societal payoffs on it.
It’s not exactly a 1-for-1 comparison, but the similar date for prediction markets in a comparison to the internet is probably 1988 with the Iowa Prediction Markets. So, it’s been 38 years. It seems to me that it’s right on schedule to be a useful systems technology for society. We’re now in the “Wild West” days of it and it’s going to be messy, like when the internet was emerging into the mainstream.
I do agree about the “feels useful but isn’t” criticism — I got very into finding mis-priced bets and arbitrages on PredictIt a few years back. It can be a terrible time sink due to being so interesting and intellectually engaging. And the type of person who can do a good job at this (I’m one of them, not on your level but also pretty good) — is certainly capable of doing much more high impact work with that same type of cognition.
So I agree with that criticism on an individual level, but I don’t think it’s right to extrapolate that to the emerging systems technology. A cautionary note that if you’re a skilled forecaster it might be a dangerous time sink I’d fully agree with, but I don’t think it makes sense to throw the baby out with the bathwater as to whether this will have societal-level impact over time.
I don’t think this is true. Emails and FTP were established in 1971 and used a lot by academics, scientists, and the military[1]
From Gemini:
The utility of email, FTP, and remote login (Telnet) during the 1970s and 1980s repaid the original government grants in three primary ways:
1. Elimination of Duplicate Hardware Costs
In the 1960s and 1970s, computers were multi-million-dollar mainframes. Prior to ARPANET, ARPA frequently had to purchase separate, identical computers for different research institutions. The network allowed a researcher at UCLA to log into and utilize a specialized mainframe at MIT. The cost of developing and laying the network infrastructure was significantly lower than the cost of buying duplicate hardware for every university the Department of Defense funded.
2. Accelerated Scientific and Defense R&D
Email and FTP collapsed the time required for complex collaboration. Instead of mailing magnetic tapes or waiting months for academic papers to be published and circulated, researchers shared datasets, software code, and peer reviews instantly. This rapid iteration sped up advancements in computer science, aerospace engineering, and defense logistics, delivering immense strategic value to the military and government.