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RS 205 - Michael Webb on “Are ideas getting harder to find?”

Release date: April 1st, 2018

Michael Webb

This episode features economist Michael Webb, who recently co-authored a paper titled "Are ideas getting harder to find?" It demonstrates that the number of researchers it takes to produce a technological innovation has gone up dramatically over time. Michael and Julia discuss various possible explanations for why this is happening, along with several challenges to his paper.

Paper Co-Authored by Michael: "Are ideas getting harder to find?"

Michael's Pick: "Truth and Power: An Interview with Michael Foucault"

Edited by Brent Silk

Music by Miracles of Modern Science


Full Transcripts 

Reader Comments (8)

Oh, really the fresh ideas are very hard to find nowadays..Thus, the info provides for us a great variety of options.
Michael Webb seems like a really capable economist. As Michael points out, technologies that have measurable metrics have almost necessarily reached a point of diminishing returns. Mega flops per Second for a CPU and the number of transistors per square inch on integrated circuits (Moore's Law) relate to a now well established technology with obviously diminishing returns. Corn seed yield relates to a genuinely ancient technology that also has obviously diminishing returns. Many FDA trials amount to bureaucratic nonsense, and fail to represent any metric of actual progress. The PhD time and Patent Application times also have much more to do with bureaucracy than actual technological complexity.

As Michael mentions, a technology that creates a paradigm shift would have much more effect on a given industry. However, can anyone really measure the difficulty of discovering a technology that creates a paradigm shift? For instance, optical computing would probably far surpass an previous achievement from semiconductors, and a new food source could obsolete corn entirely. No method exists, however, to measure the difficulty or probability of someone making such discoveries.
April 2, 2018 | Unregistered CommenterJameson
Yet another example of why economic models are of limited use. Near as I can tell, the underlying assumption is that knowledge develops along a what might be called a factory model, there is a direct correlation between "inputs" and "outputs." So, there should be a direct relationship between the "amount of effort" and the "range of outcomes."

This maybe good economics if you are making some sort of widget. But, do we really believe that science is merely making widgets? What I know of this history of science, the history of ideas, is that ideas develop in fits and starts. And, there is no linear relationship between effort and outcome. There is no predicting where the next break through will come from. And, there is no predicting how those break throughs will effect either current practice and or future developments.

There is no evidence that streaming this process will work, no matter how rational the arguments for streamlining might appear. It is more likely that "streamlining" will in fact lead to a dismantling of the scientific enterprise.
April 5, 2018 | Unregistered CommenterKen Taylor
Super-intelligent AI to the rescue!
April 5, 2018 | Unregistered CommenterMax
The example of Moore's law is a poor one for this argument because it's an example of requiring exponential effort to achieve ongoing *incremental* improvement, which is the case in many areas when you're improving an existing solution rather than truly coming up with a new idea. Of course many new ideas are required to solve all the issues in stepping Moore's law forward, but in each generation you have already squeezed out all the obvious (and many un-obvious) ideas from all the previous generations, so it's not surprising that "oh, let's just double it again" becomes exponentially hard.

It would be much more informative i think to look at the explosion of ideas that follows at the heels of each opening of a new frontier. Some examples of this today would be mobile device applications where you could look at the number of games developed for iOS and Android, the new successes in Machine Learning (since AlphaGo) and the explosive growth of new applications of these technologies, and the many new ideas in medicine and Synthetic Biology that are being developed with each new discovery about how cells work.

Unique ideas are more difficult to find simply because the number of creative people has gone from a few privileged elite to potentially billions of people around the world.

I also think talking about "ideas" is hazardous, since in many areas ideas are worth nothing until you research/develop/implement them, so the economics of ideas are much more complex than what the image of "getting an idea" suggests. Even incredibly great ideas are very often ignored even when you shout them to the world, and until you at least develop a proof-of-concept to show people, you won't get much value out of the idea itself. Genius being 90% perspiration and all that.

Another great example of the modern explosion of ideas is in art, especially that created using computers, as the internet means that anyone in the world can be on an equal footing to compete in this field. It's instructive to look at a forum like the CG Awards at cgsociety to see the incredible diversity in artists and where they come from.

April 5, 2018 | Unregistered CommenterGavin Scott
Definitely depends on the domane. Transistor count & biology have stagnated. Space travel is lightyears beyond what it was 10 years ago, with far fewer people employed on the task.
April 5, 2018 | Unregistered Commenterlion
Actually, Michael Webb's model does work really well to predict streamlining. Furthermore, if we the number of scientists and engineers overall, don't we also increase the probability of a genuinely new breakthrough technology.

Max, great comment !
April 6, 2018 | Unregistered CommenterJameson
The second pick was “images of organisation” by Gareth Morgan.
April 23, 2018 | Unregistered CommenterPaul

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