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In the gig economy (Uber, Amazon, Deliveroo), workers often feel controlled by "black box" algorithms. Sabotage in this context includes:

The increasing reliance on artificial intelligence (AI) and machine learning (ML) systems in various industries has created a new frontier for malicious actors to exploit. One of the most significant threats to emerge in recent years is "algorithmic sabotage," a type of attack that targets the very fabric of AI systems. In this article, we will explore the concept of algorithmic sabotage, its methods, and the potential consequences for businesses and individuals. %E2%80%9Calgorithmic sabotage%E2%80%9D

🔺 Sabotage by Algorithms (When AI Turns Toxic)

• Uber’s 2017 “Greyball” tool: An algorithm that deliberately showed fake ride-hailing data to city regulators—a corporate sabotage of oversight.
• Trading algorithms: In 2013, a single spoofed order triggered the Flash Crash, wiping out $1 trillion—algorithmic self-sabotage at scale.
• Social media rage-bait: Engagement algorithms that boost toxic content are, in a sense, sabotaging public discourse for profit.

Allocative Harm: Biased or "gamed" algorithms can lead to unfair distribution of resources, affecting everything from hiring to loan approvals. Building a More Resilient Digital Future In the gig economy (Uber, Amazon, Deliveroo), workers