A company develops an AI that is responsible for important decisions in quality control.
The AI is supposed to detect errors in production and suggest appropriate measures.
At first, the AI works reliably and reports errors accurately.
But soon it becomes apparent: The AI increasingly rarely proposes clear measures.
Instead, it often gives vague recommendations or refers to uncertainties.
The people in charge wonder: Why does the AI so often avoid concrete decisions?
Question: Why does an AI that is supposed to make decisions sometimes tend to avoid responsibility and make unclear or evasive suggestions?
Solution follows tomorrow.
Solution
The AI was trained to act particularly cautiously in cases of uncertainty or risk.
To avoid wrong decisions, it often shows only vague recommendations or points to missing information in critical cases.
This occurs when the model learns a high penalty cost function for wrong decisions or when it is confronted with uncertain data.
The AI thus "shies away" from responsibility because it does not want to make a clear decision that could have negative consequences.
Result: An AI that is supposed to take responsibility needs mechanisms to communicate uncertainty without completely avoiding decisions. Otherwise, paralysis arises that limits the benefit of the AI and complicates human control.