This is a discussion forum for the activities in the Human Centricity module of the Free SAS e-learning course, Responsible Innovation and Trustworthy AI.
Scenario: Firing Decisions Taken by Bots
Consider This:
What can be done to make the system more human centric?
How could a rating system accommodate circumstances beyond a driver’s reasonable control?
Please share your ideas in this discussion.
We can add a human in the loop, prior to making any punitive actions.
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Analytical Methods:
1. Instead of a single low rating leading to deactivation, consider a weighted average over time.
2. Peer to Peer rating comparison, in case of a tornado, everybody must have received low rating
Human Intervention:
1. Right to appeal or a feature for providing contextual information by the user for low rating in case of uncontrollable factors.
Automated Decision Making Deactivation:
In the times of crises, humans should take over decisioning rather than an automated system which do not consider natural calamity or a weather disruption as a factor.
Automated Adjustments for Known Extreme Weather
Cross-Referencing Other Drivers’ Data
This is a reality many drivers face every day. It’s why we need systems that are not only efficient but fair, flexible, and human-centric.
A human-centric rating system should:
Recognize factors beyond a person’s control, like severe weather or traffic delays.
Include ways for individuals to provide context and appeal unfair ratings.
Prioritize safety and effort, not just raw numbers.
Be transparent about how scores are calculated.
Treat people as people—not just data points.
Technology should support us, not judge us unfairly. A human centric rating system recognizes that life is unpredictable. It builds in fairness, context, and the ability to respond to exceptions ensuring that drivers are treated with dignity and respect, even when the unexpected happens
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