The Evolution of Cooperation

Last night I had a spirited discussion with some friends about US politics. One of our friends was expressing a concern that historically the US has been too “nice”, hopeful, helpful. We have created a culture people want to enjoy, but now we will be taken advantage of and ultimately destroyed. We need to be tougher and not be pushed around. I am not sure I would characterize the US as being “too nice”, but I contest that being collaborative is a liability.

My counter argument is that people are made to collaborate, and maximum value comes when people work together rather than engaging in a winner take all competition. It’s possible for a nation to be collaborative but still thrive even when facing bad actors.

Brief Update (2021): I recently finished Adam Grant’s book Give and Take which I think is excellent. He argues that often we are not in a zero sum game. and that cooperation can often “increase the size of the pie”. He has a nice section where he describes how effective givers can minimize the impact of people who attempt to take advantages of their cooperative nature.

The theoretical underpinnings of this viewpoint comes from game theory which is extensively discussed in the book The Evolution of Cooperation by Robert Axelrod. For people who aren’t into books, Leon Seltzer’s article The prisoner’s dilemma and the “virtues” of tit for tat provides a good summary. My super short summary: in a world ruled by selfishness with no central authority or rule, enlightened self interest can lead to effective cooperation in any situation where the participants believe that they will need to interact with each other in the future. In situations where there will be multiple interactions Tit for Tat ends up having the best long term payout. The algorithm is simple. Start by cooperating, and then mirror back the behavior of your competitor. That means “discipline” bad actors, but also “forgive” them if they are willing to cooperating. [A slight variation has a small random probability of cooperating even if the competitor has defected which can break retaliation cycles which out performance pure tit for tat.] Axelrod found that when facing numerous other algorithms, some of which were designed to take advantage of “cooperative” partners, that tit for tat consistent had the best over all returns when playing in multiple round competitions.

I believe that silicon valley culture is a great example of how this works. In the mid of the 20th century, there were several places that arguably were better positioned than silicon valley to dominate the technology landscape. For example, the Boston area had more capital and a larger educated workforce. Unfortunately for Boston, they also had non-compete employment contracts and people and institutions which were not inclined to collaborate with competitors.

The former dean of Stanford’s School of Engineering Fred Terman was instrumental in shaping the Bay areas technology landscape to be an open system which welcomes people in, encourages collaboration, and allows many people to succeed base on their merits.

A great example of this culture can be seen in the early days of semi-conductors. Competitors gathered weekly at the Wagon Wheel to swap stories and brag about their successes. Sharing took away some competitive advantage, but everyone benefited because really hard problems only had to be solved once, and everyone could move on to the next challenge. One of the best stories from those days was went Intel was having a serious issue. They were betting the company on a new chip. The chip looked good in prototype form but when they went to mass production the yield rate was extremely low. They spent several months trying to figure out what was going wrong. They couldn’t figure it out. In desperation they shared their difficulties with others at the Wagon Wheel. Engineers from Fairchild, arguably Intel’s biggest competitor of the day offered to help if Intel would provide the beer. The engineer sat down discuss the issue. In the end the engineer’s from Fairchild laughed and then said “Find out who on the line is using hairspray, and get them to stop”. Intel did as requests and their yield rates became viable. It turns out Fairchild’s engineers had chased almost an identical problem for a year before they finally narrowed it down when their yields became acceptable when one of their workers was away from the line for several days. The hair coverings both teams were using weren’t fine enough to contain the micro particles from the hairspray escaping.

For more stories and analysis, check out Steve Blank’s secret history of silicon valley. Technology Review Article Silicon Valley Can’t Be Copied is one of the best articles summarizing what has made the bay area so unique and the home of so many successful startups and Anna Lee Saxenian’s book Regional Advantage identified many of the same characteristics nearly twenty years earlier. Booz-Alan’s analysis identified a Culture of Innovation as being a differentiator, and Accenture attempted to Decode Contradictory Culture Aspects in Silicon Valley.

1 Comment

  1. Hi Mark,

    I don’t think that anyone at the table debates the effectiveness of collaboration, especially in a controlled environment. Nor does anyone reject the notion or value of symbiosis. I do not doubt the effectiveness of the “Tit for Tat” algorithm (TFTA). What I do doubt is it’s potential implementation or efficacy in the wild.

    Lets look at what an algorithm is; Boolos, Jeffrey & 1974, 1999 offer an informal meaning of the word in the following quotation; “No human being can write fast enough, or long enough, or small enough† ( †”smaller and smaller without limit …you’d be trying to write on molecules, on atoms, on electrons”) to list all members of an enumerably infinite set by writing out their names, one after another, in some notation. But humans can do something equally useful, in the case of certain enumerably infinite sets: They can give explicit instructions for determining the nth member of the set, for arbitrary finite n. Such instructions are to be given quite explicitly, in a form in which they could be followed by a computing machine, or by a human who is capable of carrying out only very elementary operations on symbols.”

    The argument for enlightened self interest suggests that the TFTA will function based upon it’s own inherent value. Great. Except humans are not computers and don’t always follow instructions. You have also expressed puzzlement that the bad actor in question has supporters that have placed him in power contrary to their own self interest, and will continue to support him even in face of such knowledge. That seems to be cognitive dissonance, on the part of both TFTA proponents, and supporters of the bad actor. Although my heart longs for a world of peace and order that follows the TFTA, my mind functions best based on empirical observations and data driven conclusions. This leads me to believe that human nature will always include self destructive behaviors due to the multitude of forces at work, including but not limited to greed, lust, gluttony, propaganda, and politics. For instance, Donald Trump’s victory in the U.S. presidential election is partially attributed to two “algorithmic” failures: First, Facebook’s emerging as an influential news provider and its algorithm’s failure to filter out “fake news”. Second, the failure of most election forecast institutions to predict the result of the U.S. election even when using state-of-the-art algorithms performing aggregation, big-data analysis and forecasting.

    My own “Wagon Wheel” type experience was as someone who grew up in Silicon Valley, and attended the same high school electronics classes as Steve Jobs and Steve Wozniak. I can concur with your assessment of the value of sharing and cooperation. It’s how I broke into the field, learning from people far more gifted. These folks lived the open source philosophy before it was a well known thing. Thanks to people like Homestead High electronics instructor John McCollum, and my old lab partner Dave Duffield, (who carried me thru some of the thorniest academic electronics exercises) my IT career rose over the years to the heights of a Senior Director in a Fortune 100 company. I certainly owe a debt of gratitude to all of the openness and assistance I found while hanging out in my Silicon Valley nerd bubble during the 70’s, 80’s, and 90’s.

    I also concur that the east coast, and many other parts of the world that could have been tech powers, were hamstrung by their own cultures. Thankfully, this allowed Silicon Valley to shine, and rise to a level that is the envy of the world. However, envy is a tricky thing, and by one way or another it led to the area becoming attractive to people from those aforementioned hamstrung cultures. Those folks have flooded the Valley and brought their self destructive or limiting behaviors and cultures with them. The seminal Northern California culture of organic sharing and collaboration, has given way to an unfettered, false, elitism. “Disruption” , “Changing the World”, and NDA’s, which translate to money, ego, and power, rule the day. Conclusion: even if a TFTA like algorithm organically originates, and temporarily functions in place like Silicon Valley, it can just as easily devolve…

    Good luck getting anyone to tell you the Hairspray is the problem these days, or achieving societal implementation of the TFTA.

    If you play by the rules on a slanted field, prepare to be a cat herder. Or, adjust your perspective FTW.


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