AI Conference
“Who should lead the revolution - humans or machines?”
At the Calcalist AI Conference, Yanay Zaguri staged a debate with an AI chatbot over the future of decision-making.
Yanay Zaguri, CEO of ExperTeam and a faculty member in the Faculty of Instructional Technologies at HIT, staged a live debate with an artificial intelligence chatbot at the Calcalist AI Conference, held in collaboration with Vultr. The central question: Who should lead the revolution, humans or machines? Who decides which employee must be let go, the manager or ChatGPT?
“The person must be the one to lead the revolution,” Zaguri argued. “If we don’t lead, imagine what happens in a large organization where the machine decides who to part with. What happens to our values? What happens to our daily lives, to situations where we must make ethical, moral, profound decisions? Without human judgment, the strong will simply become stronger. A statistical model could end up deciding how to distribute happiness. We must ensure that happiness is distributed in a fundamentally different way.”
The chatbot countered that machines should lead precisely because they are free from human flaws: “You argue that humans must lead to preserve ethics and prevent the powerful from gaining more power. But machines are free from biases and personal preferences. Decisions based on statistical models can be consistent, transparent, and fast. Values themselves can be embedded in the system. Machines can act according to moral rules, without succumbing to emotional biases or social pressures. This advantage can make decisions more objective and ensure organizations move forward without being slowed down by personal interests.”
Zaguri pushed back: “As a machine, your argument does not understand the human, emotional context that we do. Statistics take the past and try to predict the future, but they don’t grasp the small nuances of human life. No matter how much morality or data you feed a machine, it will never fully capture these nuances.”
The chatbot responded with a friendly but pointed reply: “You say humans understand emotional nuance better. But that’s precisely where biases, ego, and personal interests cause mistakes. Emotions may be what you’re proud of, but they also lead to serious errors. Machines are not driven by ego. They bring clean observation, free of hidden interests, and can decide quickly and consistently. Sometimes it’s your attachment to human context that brings you down.”
Zaguri closed the discussion by calling for balance: “The question is not who will replace whom, but how to create a model of cooperation that empowers both. We must know how to divide responsibility between humans and machines. It is not just cooperation between people and machines, but also between humans themselves. If we don’t move toward cooperation models, the strong will only grow stronger. If we do, we can share more equally.”
