Artificial intelligence, entrepreneurs, and evolution all relate to creativity. Computers cannot be creative by themselves. They need code written by humans. In the same way, organisms can adapt wonderfully but do not merely evolve creatively. Successful entrepreneurship also requires creative innovation.
Humans can be creative and—as evidenced by the awesomeness of nature—so can the creator. But artificial intelligence and computers, in general, cannot be creative. Computers can do only what they are told. They can be programmed to sort through a set of trillions of problem solutions. The final offering chosen from among these solutions may be unexpected but the answer is undeniably within the solution set created by the programmer. Humans, by contrast, display non-algorithmic and therefore uncomputable properties. These properties include creativity.
Microsoft’s CEO Satya Nadella agrees: “One of the most coveted human skill is creativity, and this won’t change. Machines will enrich and augment our creativity, but the human drive to create will remain central.” In a parallel development, pure undirected Darwinian evolution continues to fall from favor as a prevailing theory of evolution. The idea that the creativity observed in nature’s design could arise ex nihilo (from nothing) through mere evolution (change over time) is being exposed as preposterous.
Biologists in the mid-twentieth century were excited by the advent of computers that could simulate evolution. Millions of generations could be simulated in a few seconds. But evolution simulation on a computer is algorithmic. It requires computer code. Creativity is non-algorithmic and therefore uncomputable.
Many biologists claimed to have written code to simulate evolution. But the popularization of the No Free Lunch theorems showed that the computer programmer must infuse guiding information into the evolutionary program to make it work. To explain the diversity of creativity, an evolution process must be directed.
Design theorist William Dembski and I built on the No Free Lunch theorem, showing that the creative information added to an evolution program could be measured in bits.1 Computer simulations of popular evolutionary algorithms at EvoInfo.org demonstrate that evolutionary programs need this active information. The programmer must contribute creativity to make the code work.
Creativity is likewise crucial to a successful entrepreneurial economy. In an interview with publisher Steve Forbes, tech philosopher George Gilder explains “why entrepreneurship can’t just be automated.” The reason is that the creativity of the entrepreneur lies beyond the capacity of algorithmic automation. Entrepreneur Peter Thiel agrees. In his book From Zero to One, he warns against forming a business that only competes. He believes that it is better to introduce a new and innovative business to the market. Thiel, who helped found PayPal and was an early backer of Facebook, understands clearly that innovation requires creativity.
There are those who model the economy using a competitive Darwinian philosophy that does not factor in creativity. Theirs is a dog-eat-dog world where, as with Darwinian evolution, only the fittest survive. But why confine yourself to a kennel fight with the dogs when you can soar like an eagle borne up by entrepreneurial creativity?2 Think PayPal, Uber, Amazon, Dragon Software, Facebook, Google Maps and iHeart radio. All were creatively innovative and initially faced no serious competition. These businesses are part of the landscape today but all are the result of highly creative entrepreneurship.
Programs for AI and evolution share the limitation that nothing creative happens without the guidance of a programmer. And a thriving economy based on creative entrepreneurship is one of the things that cannot be automated.
Creativity is the thread connecting the beads of AI, evolution, and entrepreneurship.
1 A high-level explanation of “active information” is offered in our book coauthored by Winston Ewert: Robert J. Marks, William A. Dembski, and Winston Ewert, Introduction to Evolutionary Informatics World Scientific, 2017. The original paper is here.
2 Jay Richards also nicely supports this view in his book The Human Advantage: The Future of American Work in an Age of Smart Machines. Crown Forum, 2018.