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Takeaways from Douglas Rushkoff’s Team Human by Dr. Peter Lorange



This book deals with the same fundamental challenge discussed in The Boys in the Boat (see my previous review); namely, how to develop teams in our society to enhance our happiness and societal performance. Still, in Team Human, Douglas Rushkoff takes a different approach by attempting to tackle this challenge in a much more abstract, philosophical way, offering 100 propositions for remaking society as “Team Human.” At the center of the author’s arguments is a criticism of how our technology, our sense of markets, and our expectations regarding institutions currently isolate us and repress us. We humans are essentially social creatures, and we achieve what is best for us when we work together. But this effort to work in teams is undermined by an antihuman infrastructure. Being human is no longer a team sport.


Rushkoff is recognized as one of the world’s most influential thought leaders. He is an authority on understanding human autonomy in the digital age. While this book might be a hard read at times, too abstract and with overly complicated arguments, I still recommend it as essential reading. Its message for us to reassert our human spirit of communication and teamwork is essential to all of us in our attempt to create better businesses for the future. In particular, a healthy skepticism toward much of what modern technology seems to offer can help preserve human connections in business and society.


Rushkoff first makes the argument that social media and technology-driven networks are isolating us from others rather than bringing us together. This is the main theme of the book, clearly spelled out from the book’s beginning. We humans are social animals, and our brains allow us to bond through language and develop strong intuition. We are able to create human networks! But control over social media by dictators, monopolies, and other social power groups can hinder us on our way to a healthy evolution.


One of the most difficult factors creating evolutionary dysfunctionality has to do with original subjects becoming new objects. One example might be computer games, originally a form of entertainment but now simulations based on clear sets of logic. The Internet’s search engines were originally developed to promote scientific advantage, but now the largest of them has become the world’s biggest advertising agency. The social media platforms, initially designed to help people, became the world’s biggest data collectors.

Mechanomorphism takes place when humans can be seen as machines or computers, entirely driven by algorithms. Multitasking represents an example of this: Computers can do simple multitasking; we humans seem to move backward when we attempt to multitask. However, we can deal with broader set of tasks than a computer. The evolutionary problem arises when we are no longer in a position to address more complex problems. At that point, computer algorithms will have taken over.


Growth has always been the key to ever-increasing value creation in society. New technology typically brings about value creation and is often scalable, but this may make us humans even more dependent on new algorithmic digitalization.


It is a well-known fact that robots are gradually taking over jobs from us human beings. Good algorithms are at the core of this, complemented by the ability to analyze large sets of data to find patterns of behavior. In the context of artificial intelligence/robotics, ‘the Singularity’ is the moment when computers make people obsolete.


However, the realm of artificial intelligence (AI) clearly has its limits, too: We human beings can better handle unique and unusual scenarios. We can better tolerate, even embrace, ambiguity, whereas AIs cannot because it relies on specific algorithmic rules. Art is built on this ambiguity, in contrast to computer games with clear rules. Entrepreneurs, at their best, build on anticipating the non-obvious “to hit a home run,” which requires much more than following predetermined paths.


It is not only new technology, such as AI, powerful algorithms, and the emerging power of being able to analyze large data sets that might diminish team thinking and increase isolationism among people. We have already pointed out the key factors of growth, but paradoxically, this rather simple notion may make it harder for us humans to bond, to follow more spiritual beliefs. Overcoming such established orders, such as over-focusing on growth, may make it harder for us to escape individualistic entrapment. The rating norms of Silicon Valley or of networking may represent other phenomena leading to simplistic individualistic thinking.


The author comes up with what seems to be a good way of combining “me, me, me” and “we, we, we.” We should neither attempt to dominate nature nor withdraw from civilization, but find a balance. Good science can help us to find such middle grounds.


The recent U.N. report on how agriculture and food production seems to significantly impact our global warming problems and climate challenges might give us another example of the power of new science. Using fertilizers indiscriminately might lead to an ultimate depletion of agricultural soil, with the unintended consequence of more CO2 emissions, now also from the soil. But, is replanting and withdrawing from farming the answer? Probably not. Science and the fertilizer industry have come up with computer-based support to regulate the amount of fertilizer used based on humidity, temperature, soil types, etc. Modern meteorological forecasting is key here. This is an example of when algorithms can be put to work pragmatically.


This example also illustrates the virtue of renaissance (i.e., the rediscovering of old values). Continuous renaissance can function like a long-term revolution; that is, finding new ways and totally discarding the old (e.g., heavy dependence on fertilization for short-term gains in agricultural outputs). The world is full of such evolutionary examples, such as going from 2D to 3D and now to 4D in arts, rediscovering the virtue of innovations in arts, or rediscovering the value of exploring, going from a “flat world” to a “round world,” and now into space. We may perhaps even say that renaissance implies rediscovering the power of individuals thinking in groups!


How is this done? The author is a strong proponent of bottom-up thinking about our communities, from local to national. This is inclusion—but what about those who prefer not to be included? There should be enough tolerance in Team Human to allow for this. But, again, too much “me, me, me” might be dysfunctional. The power of dialog in face-to-face meetings is heralded.


In conclusion, the author makes a strong point: While we must not refuse new technology, we should be prepared to intervene to make machines consistent with our human values of love, connectivity, justice, distributed prosperity, etc. (i.e., an intelligent balance of both “me, me, me” and “we, we, we”). Team Human can achieve this by finding common values. Find the others!


As noted initially, I found this book to be a difficult read at times – unnecessarily complex, too many exotic words, and too few examples from business. Still, the book is a must read. Rushkoff analyzes better than anyone else the critical role of emerging technology that is becoming out of focus. While serving individualistic needs, the bonding that used to take place is suffering. There is less and less human interaction. The team dimension is suffering, and there is no longer a healthy balance between an individual and a team. There is indeed a lot to learn for many of us.

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