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The book

Book Excerpt

I’m not worried about artificial intelligence giving computers the ability to think like humans. I’m more concerned about people thinking like computers without values or compassion, without concern for consequences.
— Tim Cook, CEO of Apple

In the words of an Apple commercial from the late twentieth century, “Here’s to the crazy ones. The misfits. The rebels... The troublemakers. The round pegs in the square holes. The ones who see things differently. They’re not fond of rules. And they have no respect for the status quo.” The commercial features images of Bob Dylan, Gandhi, Amelia Earhart, creating a bond between these cultural figures and Apple: “Think Different.” This reveals a core belief held by many in Silicon Valley: that technologists and entrepreneurs are the heroes or heroines of our time, for creating world-changing products. This belief – that technology changes the world for the better –  created many success stories in the valley, and as always, behind every great success story, there is a vastly different narrative.

If we look back at history, both Professor Frederick Terman and William Shockley were credited with the founding of Silicon Valley, yet each man held a very different belief system. Professor Terman believed in giving credit, while Shockley believed he had to take in order to get. Professor Terman was the Dean of Engineering at Stanford between 1944 and 1958. He believed in creating a culture of cooperation and information exchange that has since defined the region. He was known to remind others not to take credit for their success, and he never once gave himself credit for the development of Silicon Valley. Shockley was the manager of a research group at Bell Labs that received the Nobel Prize for inventing the transistor. He was furious when he learned that his name wasn’t tagged on the discovery’s patent along with John Bardeen and Walter Brattain. Eventually, Bell Labs added his name to the patent. After the initial discovery, he worked tirelessly to improve the invention further and came up with an even better transistor by himself. Why is it that Professor Terman didn’t have to fight for any credit while Shockley had to fight hard in order to get ahead during the same time period? Which one is the correct approach to success? It turns out they both were right from their perspective, and each of us can choose to inhabit either of their worlds. Doing good under Professor Terman’s world was about giving, whereas doing good under Shockley’s world required taking. They both ended up with enormous success by making significant contributions to Silicon Valley and to the rest of the world.

Seven decades later, we have far more data and research available today to help us understand these two very different worlds. Reid Hoffman alluded to this problem in his blog post “Why Relationships Matter: I-to-the-We”. We have essentially two very different operating systems, where one is more about “I” and the other one is more about “We”. I will show you later how the Terman-Shockley narratives are related to the I vs We problem and how it impacts what we see because of our “operating system(s)” in encouraging one system of behavior or another. In his groundbreaking book Give and Take, Wharton professor Adam Grant upended decades of conventional thinking, by showing that giving to others can lead to one’s own success. His research, based on science and data, demonstrates that we can achieve great success like Professor Terman, even under the operating system to which Shockley is accustomed.

Through the experience of entrepreneurs, I would like to take us on an intellectual journey and how the very algorithm that propelled Silicon Valley to great success will hamper our entrepreneurial edge going forward. I will draw wisdom from one of the wisest leaders, Chip Conley, Founder of Joie de Vivre Hospitality and strategic advisor for Airbnb, using Maslow’s theory to help us understand our mental models across different operating systems.

Based on science and research, we can reconcile the two operating systems into one, as Hoffman did cleverly with the equation, “I to the superscript We”. We can collectively create a better environment where all of us, including machines, can thrive together for the greater good. But, “WE” need to come together as one humanity.

 
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Reid Hoffman, “Why Relationships Matter: I-to-the-We” Blog

While we know how to build highly functional organizations in Silicon Valley, we are still struggling mightily to build effective teams. This is a real problem for the tech industry, which is known to have the highest turnover rate of any business: 13%. We need to go deeper using science and technology to help us rethink our current approach in management and leadership.

Based on my experience as an immigrant and as a tech entrepreneur who has worked with some of the smartest in the world, my thesis for solving the I-vs-We problem in Silicon Valley is through compassion. We tend to believe that we can’t be compassionate and be competitive, we can’t be nice and be successful as competitive entrepreneurs, or we can’t get ahead by giving unselfishly. Marc Benioff, CEO of Salesforce, is known to be one of the most compassionate leaders in tech. His three books - The Business of Changing the World, Compassionate Capitalism, and Behind the Cloud - make countless arguments on why doing good for others should be integrated with making profits as a company. Appropriately, the founding DNA of Salesforce was built on integrated philanthropy from day one.

If Benioff is able to succeed by pushing for compassionate capitalism, isn’t it time to push for compassionate engineering and science? Should we talk about compassion when we talk about artificial intelligence? Artificial intelligence with compassion is essential for the unity of humans and machines. In the era of AI, compassion is no longer optional.

I invite you to join this important conversation. I believe this is an important time to add a “C” to STEM, especially as artificial intelligence is advancing. The way we see the world is producing the very algorithms behind artificial intelligent systems and our human biases are being used as training data for these systems. Do we want to train our robots to think in terms of “I” or “We”? Think again.

If you are interested in learning more, please reach out.