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We Replaced Leaders with Artificial Intelligence. Here’s What We Learned.

by Mengqiao Liu, Ph.D.

Even with the inevitable rise of AI, leaders are here to stayFive million jobs are projected to be replaced by technology by 2020, and, according to the 2016 World Economic Forum, 50 percent of today’s workforce activities will be automated by 2055. Artificial Intelligence (AI), the study of machines that can imitate human intelligence, is undeniably revolutionizing our world, transforming the way we learn, shop, entertain, and more.

Immersed in this AI era, you’ve probably wondered if you should start automating your organization, as well. And, if you do, you may be wondering if there will still be a place for leaders in the workplace in 20 years.

We wondered the same. To find evidence-based answers, we started experimenting with AI and applying it to leadership selection and development. Our conclusion? Leaders are not only here to stay but are becoming more important in the era of AI.

Here’s how we arrived at this conclusion. We started our AI venture in partnership with MedRespond, a company that combines AI, search, and media to provide training solutions. Leveraging natural language processing and machine learning, we developed an interviewing simulation where leaders can practice interviewing skills. This powerful tool can train leaders to ask behavioral questions to elicit job-relevant information, as well as deter them from asking biased or illegal questions (e.g., “How old are you?”). Given that interviewing requires specific, focused, procedural skills that can be captured using data, AI was quite effective in this case, achieving over 90 percent accuracy.

Where AI falls short

In another AI experiment, we explored whether AI can be used to interpret and evaluate leadership behaviors. But after analyzing data on thousands of leaders’ interactions with employees and coworkers, we found that AI falls short in understanding important leadership behaviors, such as coaching and delegation, as it fails to differentiate effective leadership behaviors from ineffective ones.

Let’s take coaching as an example. Our machine learning algorithms were given the task to dissect all the key behavioral actions that take place in a coaching conversation (engages the employee, defines challenges, offers support, gains commitment, etc.) and evaluate whether each action is effective—which, by the way, even a human leadership specialist may find challenging to do from time to time. It’s expected that computers would struggle at these tasks where complex and multidimensional knowledge, skills, and interpersonal understanding are required. So, score one for humans. After all, if AI can’t tell the good from the bad, how can we expect it to successfully lead people?

Taken together, our findings reflect the strengths as well as the limitations of today’s AI, which focuses on solving for narrow tasks that can be done with less than a second of thought by a human. While AI can take on specific, narrow-focused tasks that can make a leader’s job more efficient (e.g., using data trend visualization to aid decision making), leadership requires more than AI can offer.

Leadership is complex and multidimensional. It has to do with communication, empathy, and trust, all of which, in addition to complex knowledge and skills, cannot be mastered by AI now or in the foreseeable future. Therefore, AI should be seen and leveraged as a supplement to a leader’s job and not a substitute for it.

How to best use AI

Here are our recommendations for leaders deploying AI within their organizations:

  • Identify value-adding business cases for AI deployments. AI can be used to automate existing tasks or be leveraged by leaders to create new business opportunities. Find opportunities for AI to do what it does best, so that you can do your job better.
  • Data, data, data. There is no data science without data. Building a strong data foundation and making data-driven decisions are keys to success in your AI adventure.
  • Use AI responsibly. AI is subject to human biases. The responsibilities fall on the shoulders of leaders to ensure AI implementations follow ethical and legal standards.
  • Ensure a healthy culture for people and AI. While promoting an open, collaborative culture is important for successful AI implementations, leaders need to consider the impact of AI on people and make sure every member of the organization has an opportunity to thrive.

Interested in learning more? Read about how DDI can help you develop and transform leaders at all levels.

Mengqiao (MQ) Liu, Ph.D. is a consultant in DDI’s Product Development group. MQ is responsible for developing testing and assessment solutions for DDI's worldwide deployment, and strives to identify and advance projects and research that combine content solutions with cutting-edge technology. Outside of work, MQ is a foodie, tango dancer, and classical music lover.

Posted: 12 Mar, 2018,
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