The article "ideas are harder to find" is based not on ideas but on the final economic implementation of ideas that impact the economy (where they get the total factor productivity numbers). That is Ideas + economic feasibility + resource availability ($$$) + permissions (regulatory) + defeating political attacks from those who fear or…
The article "ideas are harder to find" is based not on ideas but on the final economic implementation of ideas that impact the economy (where they get the total factor productivity numbers). That is Ideas + economic feasibility + resource availability ($$$) + permissions (regulatory) + defeating political attacks from those who fear or are threatened by the innovation. Any one of these series steps can be the rate-limiting step. Even if you have an infinite number of scientific ideas, the rate of economic growth and apparent innovation will be limited by one of the other factors.
The authors also misuse R&D spending by companies to obtain progress as a metric for saying that R&D productivity is declining without noting that the actual areas being researched are changing over time. In an evolving technology area like chips or GMO, the researchers borrow from other areas of technology, which at that moment, are more advance than their new area. The cost of the R&D in that spill-in area of technology is on someone else's books. For example, initial semi-conductor manufacturers used clean rooms from hospital suppliers, vaccum systems from the space program, everything from saws to grinding/polishing systems from metallurgy, etc. When the feature size of chips evolved to the point where a virus looms as a mountain of impurity, they were compelled to do R&D on clean rooms. That technology advance then spilled-back to hospital clean room technology. The required R&D was then on the Chip companies books, being counted as declining R&D productivity.
The spill-in and spill-out of R&D benefits for modern multi-factor innovations is very complex and results in areas like biotech obtaining a huge spill-in of technology from computer/chip area. For analyzing DNA by looking at a color of light for each letter being added (only 4 letters) onto the sample DNA they needed holes in the 70 nm range that utilized a spill-in from semi-conductor technology. Some of these biotechnology areas are growing even faster than Moore's Law as they adapt the R&D from both semi-conductors and computers.
Meanwhile, the new semi-conductors with 2 nm line widths need very hard UV light close to soft X ray light sources. Light sources use a small drop of tin hit with a laser beam to a high temperaure plasma state, but this technology probably has a massive R&D spill-in from the billions spent on inertial confinement fusion, where a small pellet containing hydrogen isotopes is compressed to temperatures of our sun for fusion, also using converging laser beans. A few billion in R&D spill-in is good.
The "low hanging fruit" mental model or even the "tree of knowledge" model don't work very well. The very low hanging centuries old fruit of Maxwell's equations, General Relativity, and the Schrödinger equation has long gone to seed and produced trees whose branches meld with every branch of the founding tree of human knowledge they cross. When every point of crossing branches effectively starts a new tree, the tree model ceases making sense, and network models more useful images. Your i-phone utilizes Maxwell's equations, General Realtivity and Quantium mechanics to make it work. Those are not elements of Apple's research budgets.
As the overall "knowledge network" grows, more possible ideas and technologies are created at a rate much faster than the economies in the deleveloped world economies (probably up around 10%/yr). Clearly, we can conclude that the slow step controlling economic growth is not lack of "Ideas". Science has a meaning of the word "idea" that excludes economic/political factors outside the idea itself.
The regulatory and permission areas are expanding rapidly and getting slower. Imagine, if Apple had to build the i-Phone in California and needed 100,000 employees in a new facility utilizing hazardous materials, highways, etc. This is a state where trying to get permission for desalinization of seawater, in water-short Southern California, has proved impossible after decades of trying and tens of millions of dollars spent in the effort. Meanwhile Israel now obtains 50% of their water supply from desalization using RO technology, that was developed at UCLA in the '50s. Good ideas abound. It is not a lack of ideas, but obtaining permission to make use of the ideas which is the sadly limiting factor which is preventing the United States from fulfilling its potential, to the detriment not only of our country, but of the world.
To me, the whole "idea shortage" concept is a convenient excuse to blame innovation stagnation on something other than the true "rate controlling" step, which has been put into place by government regulation. With the web of knowledge now being so large, people like the authors of this article (Bloom, Jones, Van Reenen, and Webb) may not have the basic knowledge required to see the real complexity and only see what is in the sub-network of economics. Just viewing the economics (accounting numbers), we can get accounting artifacts that say R&D productivity is decreasing when the R&D is just covering more breadth.
The article "ideas are harder to find" is based not on ideas but on the final economic implementation of ideas that impact the economy (where they get the total factor productivity numbers). That is Ideas + economic feasibility + resource availability ($$$) + permissions (regulatory) + defeating political attacks from those who fear or are threatened by the innovation. Any one of these series steps can be the rate-limiting step. Even if you have an infinite number of scientific ideas, the rate of economic growth and apparent innovation will be limited by one of the other factors.
The authors also misuse R&D spending by companies to obtain progress as a metric for saying that R&D productivity is declining without noting that the actual areas being researched are changing over time. In an evolving technology area like chips or GMO, the researchers borrow from other areas of technology, which at that moment, are more advance than their new area. The cost of the R&D in that spill-in area of technology is on someone else's books. For example, initial semi-conductor manufacturers used clean rooms from hospital suppliers, vaccum systems from the space program, everything from saws to grinding/polishing systems from metallurgy, etc. When the feature size of chips evolved to the point where a virus looms as a mountain of impurity, they were compelled to do R&D on clean rooms. That technology advance then spilled-back to hospital clean room technology. The required R&D was then on the Chip companies books, being counted as declining R&D productivity.
The spill-in and spill-out of R&D benefits for modern multi-factor innovations is very complex and results in areas like biotech obtaining a huge spill-in of technology from computer/chip area. For analyzing DNA by looking at a color of light for each letter being added (only 4 letters) onto the sample DNA they needed holes in the 70 nm range that utilized a spill-in from semi-conductor technology. Some of these biotechnology areas are growing even faster than Moore's Law as they adapt the R&D from both semi-conductors and computers.
Meanwhile, the new semi-conductors with 2 nm line widths need very hard UV light close to soft X ray light sources. Light sources use a small drop of tin hit with a laser beam to a high temperaure plasma state, but this technology probably has a massive R&D spill-in from the billions spent on inertial confinement fusion, where a small pellet containing hydrogen isotopes is compressed to temperatures of our sun for fusion, also using converging laser beans. A few billion in R&D spill-in is good.
The "low hanging fruit" mental model or even the "tree of knowledge" model don't work very well. The very low hanging centuries old fruit of Maxwell's equations, General Relativity, and the Schrödinger equation has long gone to seed and produced trees whose branches meld with every branch of the founding tree of human knowledge they cross. When every point of crossing branches effectively starts a new tree, the tree model ceases making sense, and network models more useful images. Your i-phone utilizes Maxwell's equations, General Realtivity and Quantium mechanics to make it work. Those are not elements of Apple's research budgets.
As the overall "knowledge network" grows, more possible ideas and technologies are created at a rate much faster than the economies in the deleveloped world economies (probably up around 10%/yr). Clearly, we can conclude that the slow step controlling economic growth is not lack of "Ideas". Science has a meaning of the word "idea" that excludes economic/political factors outside the idea itself.
The regulatory and permission areas are expanding rapidly and getting slower. Imagine, if Apple had to build the i-Phone in California and needed 100,000 employees in a new facility utilizing hazardous materials, highways, etc. This is a state where trying to get permission for desalinization of seawater, in water-short Southern California, has proved impossible after decades of trying and tens of millions of dollars spent in the effort. Meanwhile Israel now obtains 50% of their water supply from desalization using RO technology, that was developed at UCLA in the '50s. Good ideas abound. It is not a lack of ideas, but obtaining permission to make use of the ideas which is the sadly limiting factor which is preventing the United States from fulfilling its potential, to the detriment not only of our country, but of the world.
To me, the whole "idea shortage" concept is a convenient excuse to blame innovation stagnation on something other than the true "rate controlling" step, which has been put into place by government regulation. With the web of knowledge now being so large, people like the authors of this article (Bloom, Jones, Van Reenen, and Webb) may not have the basic knowledge required to see the real complexity and only see what is in the sub-network of economics. Just viewing the economics (accounting numbers), we can get accounting artifacts that say R&D productivity is decreasing when the R&D is just covering more breadth.