papers in adversarial machine learning — algorithmic fairness

The potential for harm from AI is growing with its increased usage in products and services. It's not possible for even well-intentioned companies to mitigate all the harm these systems might cause, but individuals can also use technology to shift these systems' behaviors toward their own preferences. Examples of this include adversarial patches to avoid surveillance, and data poisoning for fair loan acceptance.