A city administration uses an AI-based platform to efficiently process citizen concerns.
Citizens can submit their concerns digitally and receive automated feedback.
The AI filters and prioritizes the concerns to relieve the administration and respond faster.
At first, the system seems to work well.
But soon many citizens complain that their concerns are hardly answered anymore.
Especially critical or dissatisfied voices seem to get lost in the automated processing.
The administration wonders: Why do the critical concerns disappear and are hardly processed?
Question: Why can an AI that automatically prioritizes citizen concerns cause critical voices to be systematically ignored or not processed?
Solution follows tomorrow.
Solution
The AI was trained to evaluate concerns based on urgency and tone.
In doing so, it often learns that neutral or positive requests are easier and faster to process.
Critical or emotionally negative concerns are classified as more complex and therefore prioritized lower.
Furthermore, due to insufficient training data or biases in the data, the AI can classify critical voices as less relevant or even as spam.
This leads to important complaints or problems being processed less frequently and citizens feeling ignored.
Result: An AI that automatically prioritizes citizen concerns must carefully ensure that no critical voices are excluded. Otherwise, a bias arises that suppresses important feedback and weakens trust in the administration.