AI leader voices
What would you say are common misconceptions about AI?
It is somehow interesting to observe that AI was initiated only 70 years ago in the research labs of mathematical scientists, a discipline where by default definitions are used to give a precise meaning to a new term. Today, AI left those labs and influenced our complete society at a very fast speed with no agreement on terms and definitions. In my opinion, this current Babylonian speech confusion between all actors involved (business, research, government, society) is the origin of many misconceptions.
What is the future of AI?
Today, there is an increased need for more humain AI translators, T-shaped profiles or generalists who can demystify some important definitions and who can clarify in understandable words the current confusion between AI as a science, technology or tool, and AI as a common goal, journey or quest for general intelligent machines. For this, we need to leave our silos and create more inter-disciplinary teams at all levels: research, business, society and government.
What are the challenges for AI today? Tomorrow?
AI needs more regenerative AI leaders who keep the long-term impact in mind, while still recognising that they are here today to do what's best for the company, our society and for the world. Regenerative leaders look beyond AI regulation and AI4Good projects, and master the challenging balancing act of nature's co-operating principles. In order to reach sustainable AI solutions, regenerative leaders dare to add one additional stakeholder around the table during their design phase: Planet Earth.