machine learning

How Artificial Intelligence Means More Efficient Leadership

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These days, there’s a lot of talk about artificial intelligence (AI). Is this revolutionary technology here to help us or to take us over? Some people are really excited about an increasingly technology-driven future; others imagine there is no future with humans in it. After watching the latest sci-fi flick imagining our apocalyptic fate, it’s very easy to believe that AI threatens our intelligence, our jobs, and even our very survival.

 

Artificial Intelligence and Efficient Leadership

 

AI provides us with ways to do our jobs better and smarter. This transformational technology is still in its infancy, but already it is making radical changes in the workplace, all the way up to leadership. If you are a leader, AI shouldn’t be relied on to do your job for you. However, it can certainly help you do a better job. 

 

One thing is sure: adaptation to this increasingly digitized world is no longer a question of choice; it’s a necessity. So, let’s take a look at how you can use AI to complement your strategic vision. 

 

Data-Driven Intelligent Leadership

 

Great leaders understand that leadership is a lifetime role informed by continuous learning and transformation. Outdated leadership models are no longer effective in today’s modern world. As technology evolves, the day-to-day responsibilities of leaders must evolve along with it. AI is powered by machine learning that provides leaders with more access to data than ever before. 

 

If you are a leader in a data-driven industry, you may think there’s not as much for you to do. However, AI isn’t meant to do away with your oversight. Think of it as leveraging your intuition with accurate information. Data allows you to make better and smarter business decisions. In other words, it enables intelligent leadership.

 

How Artificial Intelligence Can Turn You Into a Smarter Leader

 

Here are just a few of the ways AI can benefit your leadership:

 

  • Increase collaboration across departments.

  • Reveal inefficiencies in product design.

  • Pinpoint holdups in a workflow.

  • Assess cost-effectiveness.

  • Reduce customer churn.

  • Predict probable outcomes based on several different starting points.

  • Sort through hundreds of résumés to find top job candidates.

 

Artificial Intelligence Gives You More Time to Lead

 

Do you have a seemingly endless to-do list? AI can liberate you from routine tasks that can easily be automated. This cuts down on stress, leaves you time to focus on the big picture, and increases your productivity.

 

Artificial Intelligence Reduces Decision Fatigue

 

Have you experienced depleted energy levels, unexplained bouts of anger and frustration, and impulsive decisions? Do you recognize these signs as the high price of being a leader? You might just pass these symptoms off as the consequence of a demanding, high-stress job, but what you are actually suffering from is decision fatigue

 

When people have to continuously make one decision after another, there’s a biological price to be paid. The more decisive you have to be during the day, the harder it is on your mental capacities. Eventually, your overloaded brain will look for a way out – you will either make a reckless decision or do nothing when you should be doing something. 

 

Algorithms Don’t Get Tired

 

There is one significant way that algorithms are different from humans: they don’t get decision fatigue. They can keep on making infinite numbers of decisions more accurately and faster than people are biologically capable of. So look upon AI as a partner and a competitive advantage that can make you a trailblazer in your industry. 

 

AI should not be regarded as a one-size-fits-all solution to every leadership problem you may face. You need to understand your limitations and AI’s advantages and sensibly amalgamate the two. If you do, you will be traveling down the high road of intelligent leadership.

 

If you are interested in learning more about how Artificial Intelligence can help you in your business and you aspire to more intelligent leadership, Shaping Development can help you. Book a consultation call with us today to learn more.

How Can Behavior Analysis Assist in the Study of Machine Learning?

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Recently, we have been contemplating the relation between machine learning and behavior analysis.  Interestingly enough, this topic of the collaboration of machine learning and behavior analysis is not new.  William Huchison, in 1998, discussed "Computer Simulations of Verbal Behavior," and compared the learning of verbal behavior in computer simulations to that of a human learning verbal behavior, proving that "operant learning is sufficient to produce verbal behavior."  Fast forward to 2012, and in Huchison's work, "The Central Role for Behavior Analysis in Modern Robotics, and Vice Versa," it is observed that most computer "systems assume basic foundations of operant conditioning (Huchison, 2012)."

Howard Rachlin (2012) also discusses the similarities between the IBM computer, Watson, and a human being, in his work, "Making IBM's Computer, Watson, Human," outlining that the basic needs of humans and computers are the same:  we need an energy supply, protection from the elements, maintenance, and our bodies to be maintained at a reasonable temperature.  He theorizes that by creating a "Watson II" with more characteristics of human beings (i.e. being able to "override its own logical mechanism" after establishing "rules"), ultimately:

"those who would see Watson II as nonhuman because he was manufactured, not born, might go on to say that it would be worse for humanity were we all to be made as Watson II may be made. To me, this would be a step too far. We are all a conglomeration of built-in and environmentally modified mechanisms anyway. And no one can deny that there are flaws in our current construction." 

In both of these articles, Huchison and Rachlin, create a call to action, discussing the need for collaboration in computer science and behavior analysis, as computer science evolves to machine learning and artificial intelligence.

So how do we do this?  Ultimately, computer science majors interested in programming, should receive training in behavior analysis.  Currently, this is not happening, as most computer science programs have adopted more of a "pop psychology" background in their current research and practice (see Ink's article:  "MIT Researchers Use Reddit to Create World's First Psychopath AI).  What this further demonstrates, is not only a need for the dissemination and training of our science to the computer world, but also a need for a similar ethics code in the shaping of behavior when programming, as we do as behavior analysts working with human beings.

So what do you think? Comment below!

 

References:

Hutchison W.R. (1998). Computer simulations of verbal behavior for research and persuasion. The Analysis of Verbal Behavior. 15:117–120. 

Hutchison, W. R. (2012). The Central Role for Behavior Analysis in Modern Robotics, and Vice Versa. The Behavior Analyst35(1), 29–35.

Rachlin H (2012).  Making IBM's computer, Watson, human. The Behavior Analyst. 35:1–16