What CEOs need to know to outwit artificial intelligence

My 10-year-old daughter recently made a statement as we drove to her piano class the other day that's going to be on the minds of CEOs and discussed in boardrooms soon, if not already: "If there is artificial intelligence, then we won't need to think," she said.

Her words left me speechless.

I tried in vain to remove from my mind a sticky image from the movie based on the cult classic novel by Douglas Adams, "The Hitchhiker's Guide to the Galaxy." In it, a supercomputer called Deep Thought rendered the answer to the Ultimate Question of Life, the Universe and Everything, after 7.5 million years of calculations: the number 42.

Michelangelo hand with human hand
Hans Neleman | Getty Images

Quirky cult movies aside, the impact of artificial technology is immense, and the implications are phenomenal. And it has divided much of the technology world into two opposing camps.

There are dystopian terminator-like views backed up by warnings from renowned scientists like Stephen Hawking. Even Tesla and SpaceX founder Elon Musk appeared on CNBC's "Closing Bell," cautioning about the potential risks of this technology. (Meanwhile, Musk announced last week that Tesla is rolling out a software update that will allow its current Model S cars on the road to operate on a self-driving protocol, setting off fears about A.I.)

On the other side of the coin, Jeff Hawkins, scientist, serial entrepreneur (Palm, Handspring) and founder of the Redwood Center for Theoretical Neuroscience, vehemently argues "the Terminator is not coming." His company, Numenta, is reverse-engineering the human neocortex for A.I. purposes.

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While we debate how close A.I. is bringing us toward a life-extinction event, we have families to care about and businesses to run, so what is this technology going to do to us in the short term, and more importantly, as a CEO, what should I do about it?

More than just one more disruption

CEOs and management at companies can think of A.I. as yet another technology disruption—an enormous, multipronged and pervasive one. First we had data and databases. Then came the Web and then came Google indexing it. The past decade has been about mobility and smartphones.

Fast-forward to the new millennium, and we are in the dawn of the modern Big Data era. Open-source software to process and analyze large data sets like Hadoop are being used by Silicon Valley companies, including Cloudera, while data analytics striving to find meaningful insights and patterns in data through algorithms is evolving into predictive analytics and machine learning (also referred to as intelligent applications) synonymous with Silicon Valley-backed firms like Palantir Technologies.

Arguably, A.I. is a much bigger disruption than the Internet.

"Remember the classic Atari games from the '80s? We were dragged into endless hours of fun and play to master Pong, Breakout or Space Invaders, right? Now, an A.I. machine with no other input than raw pixels and a reinforcement learning algorithm is capable of beating the most expert of human players."

To some extent, A.I. is already embedded—in many cases unnoticed—in thousands of narrow artificial intelligence applications:

  • Natural language processing (virtual assistants; i.e Siri)
  • Finance (stock trading, credit score analysis)
  • Toys and games (from Furby to Aibo)
  • Publishing and writing (i.e computer-generated news)
  • Robotics, genetics, research, law and transportation

Another way to size up the potential of A.I. technology is to look at how existing predictive analytics methods have disrupted the business world.

The most famous example is probably the marketing analytics used by Target. Based on purchase history, the retail chain could predict if someone was pregnant—and in one case clued in a teenage girl's father to her pregnancy after Target started sending coupons for baby items to her. It turned out Target was correct in its prediction. Creepy, isn't it?

According to Yahoo CEO Marissa Mayer, credit card companies can predict a divorce two years before it happens with 98 percent accuracy, based solely on your purchase decisions.

Apocalyptic IQs

We humans underestimate the incredible biological machine otherwise known as our brain.

It takes 82,944 processors and 40 minutes for a supercomputer to simulate a single second of human brain activity, according to tests by researchers at the Okinawa Institute of Technology in Japan.

Studies and empirical evidence confirm human intelligence follows a bell curve distribution pattern. This means, on average—and on an IQ score scale from 55 to 145—96 percent of people fall within the 70 to 130 score bracket, and 68 percent of the population would have an IQ between 85 and 115. And here comes the interesting part: 0.1 percent of outliers will stand out as extremely high IQers, above 145. This is 1 out of every 1,000 individuals.

Now think about it: If interactions between IQ outliers (+150) and normal people (85–115 IQ) prove to be extremely difficult (geniuses bother very little about everyday things), what would happen with a sufficiently developed A.I.? Would this be like humans trying to speak with ants? Or would an A.I. even bother communicating?

High-frequency trading, enabled by A.I. algorithms, was a culprit in the U.S. stock market flash crash of 2010, in which the Dow Jones plunged 9 percent within minutes. It was the biggest one-day point decline in the history of the Dow Jones. In 2010 an estimated 70 percent of all equity trading volume was done by machines. Ray Dalio, famed hedge fund manager at Bridgewater Associates, poached the former head of IBM's Watson division to oversee his hedge fund's expanding A.I. effort.

Companies in general can utilize analytics to predict customer sentiment and choose when to intervene and interact directly with customers—all to improve consumer engagement and brand perceptions. Moreover, machine learning is now in a rapid democratization process. Google Prediction API, for instance, lets you build your own smart applications for sentiment analysis and purchase prediction, all from the cloud.

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The most advanced A.I. developments today are coming from what is called deep reinforcement learning. Demis Hassabis' DeepMind, last year acquired by Google, is at the forefront of this research, and the results are impressive. Remember the classic Atari games from the '80s? We were dragged into endless hours of fun and play to master Pong, Breakout or Space Invaders, right? Now an A.I. machine with no other input than raw pixels and a reinforcement learning algorithm is capable of beating the most expert of human players.

An A.I. survival guide for CEOs

So what's a CEO to do?

1. Expect that Software as a Service (SaaS) will become more and more like "Everything as a Service."

That goes for everything from sourcing talent to getting probabilistic predictions of the sales of your products. Your company needs to keep up with the times, embrace new services and A.I.-based technologies or fall behind. Similarly to what happened a decade ago, when enterprise mobility entered the strategic road map of major corporations, A.I.-enabled technologies will become an integral part of the strategy planning process in the near future.

2. If you think A.I. is not here—at least not in a conspicuous way when it comes to your businessthink twice.

Do your marketing people hire research or customer insights reports? Most likely your contractors are using big data analytics to deliver their conclusions to you. Is your competitor doing so in-house? That may indicate they can react and move faster in decision-making and eventually interact rapidly and more decisively with (your) customers.

3. Conduct an A.I. inventory.

Map out existing internal and external resources of your company and match them to available big data, analytics and A.I.-related technologies and tools.

4. Delegate it.

To make it simple and to monitor A.I. readiness of your company, you should earmark a tech champion in your management team (if there isn't one already). The chief information officer promoted to chief digital officer or chief marketing officer will do for the time being. Task the tech champion to screen for any of these referred tools or technologies currently in use either internally or externally. If the answer is a hard no internally, run a supplier and partner appraisal to understand how far A.I. is from the core of your business. Give yourself a score on a scale of 1 to 10 and start pushing the company to embark on the A.I. journey. You probably already did this when you told your management team to start using mobiles, tablets or smartphones.

5. Think ahead and don't wait; there's no reason you can't, or shouldn't, be the one to A.I.-innovate.

If you don't have internal resources to do it, partner with corporate innovation advisors, launch your own company sponsored start-up incubator, or even a venture fund with a focus on the specific A.I.-enabling technologies that you have identified as relevant and disruptive to your business. Many of these innovation mechanisms are already one click away, in the cloud.

Stephen Hawking said, "Intelligence is the ability to adapt to change." While we wait for a General Purpose Artificial Entity (aka, A.G.I.) to do that for us, as my daughter promptly inferred, let's take the driver's seat.

By Ed Fernandez, an early-stage venture capitalist and board advisor to Daedalus S.A, a data analytics and predictive technology company. He is also a member of the CNBC-YPO Chief Executive Network.

Follow him @efernandez

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