Dr. Reinhard Ploss has worked in microelectronics for more than three decades. When he began his career in 1986 after a doctorate in process engineering, the internet was just taking off. During his time on the executive board, technology fundamentally changed business and society.
He was one of twenty-five leading thinkers interviewed by the research team of the Future of Leadership Initiative for its annual theme: leadership and the rise of intelligent machines.
What it is all for
Asked whether the rise of intelligent machines is an end in itself or serves a purpose, Ploss paused.
There is a fundamental contradiction today. Almost nine billion people live on this planet. Most of them should have the chance to enjoy a standard of living similar to ours. Only intelligent applications can help us achieve that without destroying our natural resources further.
Insight 1 — Machine intelligence can and should serve to raise the global standard of living without destroying the resource base.
The danger of a monochrome society
For ordinary users it is almost impossible to understand the decision process of an intelligent algorithm. Combined with the convenience of intelligent systems, this creates great potential for unconscious manipulation. Many people do not know to what extent their decisions online are driven by AI. And the convenience is too tempting.
“Why do people use Google? Because it delivers the best results,” Ploss said. “You have to ask yourself: where am I paying for this convenience?”
Over time, the pull of the easiest option could lead to increasingly uniform behavior. “The world works today because it is colorful. We must avoid monochrome, over-optimized systems.”
Insight 2 — The human tendency toward convenience can lead to an imbalance of power that favors those with the best data and algorithms.
The need for moral leadership
Artificial intelligence is only as good as its training. It is biased by the data it is given and by the way of thinking of those who wrote the algorithms.
Introducing machine intelligence demands a high degree of awareness and moral judgment about the possible consequences. Individuals and organizations must decide consciously how much data they generate and make available to others. That is a leadership task, and leadership must set clear rules about what is permitted and what is not done.
Insight 3 — The purpose of leadership is to ensure moral judgment about how intelligent machines are developed, trained and used.
Fusion thinking instead of silo thinking
How can leaders prepare everyone to work with intelligent machines? Ploss calls for a “fusion of thinking between technology and business.” Anyone who needs a digital solution should be able to understand the logic behind it — as well as its possible ethical consequences and use cases.
Insight 4 — Everyone should have a basic understanding of how intelligent machines think and process data.
For this fusion thinking to emerge, leadership should spark curiosity, hold open debates and ensure that good practice is shared. For Ploss, exploratory thinking begins with openness: people should enter a process with curiosity and feel encouraged to say what they do not know. Answers to the unknown can then be sought together.
The value of not knowing
As technical systems grow more complex and exceed human understanding, the ability to deal with the unknown becomes more important. Many people, especially in leadership positions, experience the unknown as a threat. Yet it holds the potential for improvement. Deliberately valuing the unknown releases curiosity and creative power.
There is a fundamental insight in valuing not knowing.
Insight 5 — Curiosity and an exploratory approach are becoming key individual capabilities.
Why this conversation is here
In insight 5, Ploss describes something that in our work goes by the name of tolerance for ambiguity, and he names it as a leadership problem, not a character trait.
That is the difference that matters. When not knowing counts as weakness, no one in a meeting says they do not understand something. Exactly the information a group would need to be smarter than its members individually then goes missing. We see this regularly at board retreats on AI: the question everyone has, no one asks.
Leadership decides whether it gets asked. Not through an invitation, but by the highest-ranking person in the room being the first to admit not knowing something. That takes thirty seconds and changes the rest of the day.