Lately I’m thinking about the re-emergence of ideas over time. I’d like to get a better handle on that process, hopefully with a model, and so try to better anticipate when such a thing may occur.
Let me explain.
Most of the time we think of new ideas starting from nothing, then growing through widespread adoption into occupying a significant position in civilization. For example, powered human airflight: after years of work the Wright Brothers invent a working airplane by themselves, and air travel takes off (ahem) within a generation.
There’s a nice visualization of this pattern in an early chapter of HG Well’s Food of the Gods (1904), where two scientists model biological growth. In a chart they represent the horizontal access as time, and the vertical for size:
Some of my readers will be familiar with a variation on this, Gartner Research’s famous hype cycle. That starts off with a rapid growth pattern, changes to a dramatic drop-off, followed potentially by a less impressive, less hyped second growth phase. I really enjoy this model for its cynicism and actual utility (except for Apple products, which never fall from the peak):
Yet what I have in mind today is a different pattern, one of initial growth, dieback, then a period of larger growth. In this model some innovations spark then misfire, go dark, then come roaring back years later.
Virtual reality was what triggered this thought for me. Some of you will remember the excitement around VR in the 1990s. There was a huge amount of hype, from carnival-style rides to movies to DIY projects. In 1997 two of students at the University of Michigan built a VR level for a class project in my Gothic cyberspace seminar. Then VR collapsed into a big bust in the late 1990s. (I think this is one reason for Jaron Lanier’s peculiar career as techlasher and bad writer.) Now VR has come back in a second growth phase, bigger than ever before.
Once I saw this pattern, other examples came to mind.
Computer gaming rose rapidly in the 1970s, then suffered a famous crash in the mid-1980s, at least in North America. Now gaming is one of humanity’s leading culture industries. AI has gone through multiple hype spikes followed by “winters,” and now is starting to really shake the world
Apart from technology, there are social and cultural examples. Think of gay rights in America. After Stonewall the 70s saw a gay and lesbian people start claiming space in popular culture and more openly in everyday life, only to get beaten down in the early 80s, with the double attack of AIDS and a right-wing president.
Yet gay rights has made steady progress since, from decriminalization of gay sex to the gradual legalization of same-sex marriages.
What powers this particular dynamic? The history of innovation and cultural change offers a rich trove of examples and many different forces. An idea can be ahead of its time, and only blossoms once social conditions change. An invention can overpromise and underdeliver, either for internal of external reasons.
Popular taste might shift. Geoffrey Moore’s Crossing the Chasm (originally 1991) offers many cases of an initial idea failing to go mainstream, primarily by not winning over mainstream populations.
A first wave of growth, followed by a crash, then triumph: what are the best frameworks for thinking about this kind of trajectory?
Economics uses boom-bust-boom as a description of the normal business cycle. Here’s one typical visualization:
Here’s a Wikipedia image for rolling recession:
More abstractly, the shape that keeps coming up in my visually challenged brain is of a U-shaped curve.
Maybe a U-bend, as in plumbing. Textually, I don’t have a good term yet. Jeffrey Markert tweaked my “boom-bust-boom” phrasing to suggest a lovely alternative, “bloom-bust-boom.”
If this pattern is a real one, I’d like to figure out how to use it in the futures way. How can we determine if a rising idea or innovation is the first in a two-boom cycle? Better yet, which busted ideas are getting set to come roaring back? Which failures can we understand as awaiting a rebirths down the road?
One way is to follow the money. In her important Technological Revolutions and Financial Capital (2002) Cartlota Perez shows how investment capital drives new tech. It’s not sexy, but tracking where the money is being sunk should give us a good hint.
Another it to look for changing conditions that an innovation depends on. For example, if the early 1980s’ spike in Cold War tensions helped quash gay rights, then Gorbachev’s rise and the USSR’s dissolution took that condition away, helping the second phase of gay liberation occur. On the technological front, VR demands a lot from tech (graphic rendering, memory, bandwidth); the digital ecosystem is now a more congenial space than it was in the 1990s.
Are there other examples of such U-shaped development trajectories?
And which boom-and-busts can you think of that are awaiting their glorious next boom? A few possibilities:
- Peer to peer computing (big boom in early 2000s; crushed by copyright and security)
- Green politics (huge strides in the 60s and 70s; quashed and marginalized effectively by the GOP in the 80s; rising now among the youth)
- Virtual worlds (think of the meteoric Second Life rise and fall)
- EDITED TO ADD: Psychedelics had a rapid boom and bust in the 1960s and 70s. They might be enjoying an uptick now, partly due to the gradual decriminalization of cannabis, partly due to some new activities, like Michael Pollan’s public interest.
What others are out there?
PS: my son offers another take on this U-shaped innovation, one aimed more at an innovator’s morale and general inspiration:
Don't know the name, but we have to avoid giving up, and not be satisfied with what little we get. Reconstruction was another example of the problem.
— Owain Alexander (@captainreddy123) September 2, 2019
(U-shape photo by ivydawned; thanks to Bill Seitz and Harold Jarche for Twitter conversation; thanks to Eric Hoheisel and Jim Burke for futures reflection)
I admire the search for a good metaphor, but I wonder if you should be thinking about J-curves rather than U-curves. (See https://www.futuretimeline.net/forum/topic/16810-the-j-curve-understanding-revolution/ for one slightly idiosyncratic take on the J-curve of rising expectations, which partly inspired the Gartner model.) The challenge with all of the curved metaphors is to find something merely descriptive; too many upward swoops are deterministic or just wishful thinking. And then there is a matter of scale; a Medieval historian might not consider a recurring pattern from the 1990s and 2010s as something discontinuous or even repetitive.
Phil, thank you very much for the J-curve pointer. That’s enormously appealing. I like the way it has an initial spike followed by a much larger rise.
I don’t know Bremmer’s book.
Scale is a key problem in futures work. We can identify patterns, but get the timeline wrong.
there’s a lot of elements in this stew i think. Think it’s mostly about what society is focused on (money, civil rights, pleasure, entertainment, etc.). But, as I understand it, video games took a dive in the early 1980s due to shady business practices (like, someone realized all the console makers were using a chip that was only made in 4 places, so they maxed those places out with orders and nobody else could jump in. until Nintendo came along). (saw this on some documentary clip within a video game collection of classic titles).
– what this mostly makes me think of is : generational knowledge transfer. I know it’s not exactly what you’re getting at, but methinks it’s related and important to consider. Jonathan Blow gave a great talk about how those that invent things fail to teach the next generation all the things that went into it, so technology inevitably degrades and societies collapse. would recommend watching: https://www.youtube.com/watch?v=pW-SOdj4Kkk
Warren, that’s a good way to flesh out this model. Corruption definitely plays a role.
Looking forward to listening to Blow’s talk-
Bryan, it may be unpopular and I’m not necessarily wanting this to happen, but I think another likely example is the for-profit university. We will hit the next recession and higher ed will face many of the same conditions that it did int he last recession, which saw a for-profit book. The question is which side of that equation, traditional non-profit or for-profit, learned more and will adapt the most in the next downturn.
Peter Diamandis in his book Abundance (and others around him at Singularity University, in the book “Exponential organizations”) look at the “exponential growth model”, where very little progress is made over a significant period of time, until the minuscule accumulative progress finds itself in a position to grow exponentially. Startups refer to this as “hockey stick growth”, and see it as desirable. Interestingly, it seems that exponential growth happens in nature (think microbial growth) and in markets (when a tech or provider comes and “wins” the market over). The Renewables energy developments make for an interesting example in my mind: Very little visible over a long period of time, and in the last 3-5 years the realization that they’re actually cheaper than established methods of energy production.
Taking the exponential growth model beyond the intensive growth is interesting as well: will the phenomenon
1) stabilize at a certain size (restrained by its environment)?
2) enter a period of instability?
3) decay immediately?
4) stabilize for a while and then find new opportunities for growth?
About that U-shaped process, see Otto Scharmer’s “theory U”.
Where would we find data to see if the pattern emerges? https://www.zylstra.org/blog/2019/09/bloom-bust-boom/