13 Dec Case Study: Uber’s AI-Driven Pay Systems & Legal Action
In November 2025, the non-profit Worker Info Exchange sent a legal demand to Uber to stop using its AI-driven “dynamic pricing” pay system, alleging it significantly reduced driver incomes and violated European data protection law. This case directly connects to the Fairness and Transparency principles in our course.
This case highlights the tangible harm algorithmic systems can cause when deployed without adequate safeguards for fairness and human welfare.
How to Connect This to Your Final Project
This case provides concrete, current justifications for your proposals:
- Enforce Fairness Audits: Use the Uber case to mandate independent, third-party audits of any algorithmic system that manages pay, promotions, or resource allocation.
- Mandate Transparency: Referring the case to require that AI decision processes are documented and explainable to affected individuals, not just the technical team.
These examples show that AI ethics is not a solved problem but an urgent, ongoing challenge.
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Read More:
- What is Deep Learning
- Feedforward Neural Networks (FNN)
- Convolutional Neural Network (CNN)
- Recurrent Neural Networks (RNN)
- Long short-term memory (LSTM)
- Generative Adversarial Networks (GANs)
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