68. Steve Phelan Explains Why Entrepreneurial Intelligence Beats Artificial Intelligence
Artificial Intelligence promises cognitive augmentation for business practitioners. Professor Steven Phelan’s research reveals that Entrepreneurial Intelligence is far more important and far more likely to influence business success. He explains Entrepreneurial Intelligence and why it will always beat Artificial Intelligence on this week’s episode.
Key Takeaways & Actionable Insights
What is Entrepreneurial Intelligence?
For Steven Phelan, “It’s all about the spark” — the moment of inspiration in combining disparate elements together to develop a new solution. Humans draw on “the fringes of consciousness” to create new constructs.
Entrepreneurs also take risks, investing time, talent and treasure in their venture in hopes of gain, yet understanding that they could lose something of value to them in the endeavor.
How do we contrast Entrepreneurial Intelligence and Artificial Intelligence?
First, we need to differentiate between the narrow and general forms of AI. Narrow AI is software that can solve problems in a single domain. For example, a Nest thermostat can raise the temperature or lower it in a room according to a pre-set rule. “If this, then that” is the general rule for this kind of intelligence. The parameters are designed by the programmers.
For the unstructured problems of life and business, a truly intelligent computer would have to figure out for itself what is important. Part of the problem is that understanding or predicting human motivations — as entrepreneurs do — requires a “theory of mind”, an understanding of what makes humans tick. Entrepreneurs need empathic accuracy — unavailable to AI — to anticipate the needs of consumers. A sentient computer would need self-awareness or consciousness to truly empathize with humans, and have a set of values with which to prioritize decisions.
What’s the role of machine learning?
If you work in a business that generates a lot of data, it can be mined by data scientists for patterns, and those patterns might indicate a better way to respond to customer needs. The richest source of data is behavioral — like choosing songs to listen to on Pandora. Machine learning can detect a pattern of what kinds of sings a user chooses most. A human interpreter can translate those patterns into preferences — in other words, motivations are embedded in behavior and machine learning can help entrepreneurs extract them.
So, the entrepreneur’s best resource is entrepreneurial intelligence.
The psychologist Howard Gardner helped us to recognize many types of intelligence, including math, language, spatial, musical and social. There are two types that might be indicative of entrepreneurial intelligence: EQ (Emotional intelligence) might be associated with intensified empathic skills and empathic accuracy; CQ (Curiosity Intelligence) is linked to the kind of creativity that finds solutions by combining elements on the “fringes of consciousness”, as Hubert Dreyfus puts it.
Can entrepreneurs and business owners assess their own entrepreneurial intelligence?
There are scales to measure EQ and Creativity. Here’s a link to an entrepreneurial quotient assessment: Mises.org/E4E_68_QA
And here is a more action-oriented self-assessment we developed for E4E: Mises.org/E4E_68_SA
The bottom line:
Entrepreneurs need knowledge of how to profitably satisfy customer preferences given the resources at hand. This is not a trivial requirement. It is not possible to pre-state all of the uses for a given resource nor to compute the payoff for a given application. Current computational methods are thwarted without a complete list of entrepreneurially valid moves and the payoffs from such moves. No amount of growth in processing power, data communication, or data storage, can solve this problem.
The late Steve Jobs is often held up as the epitome of a successful entrepreneur. His founding of Apple, ousting by his own board, and subsequent return to rescue the company, and then make it the most valuable publicly traded company in the world is the stuff of legend. One of the apparent secrets of his success was to understand that “people don’t know what they want until you show it to them. That’s why I never rely on market research. Our task is to read things that are not yet on the page.”
This ability to “read things that are not yet on the page” lies at the heart of the concept of empathic accuracy. Empathic accuracy is “the ability to accurately infer the specific content of other people’s thoughts and feelings”. Until AI can do this, Entrepreneurial Intelligence is a better tool for the innovating entrepreneur.
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