Artificial Intelligence Faces Bias, Hallucinations and New Coding Revolution

Artificial intelligence systems are increasingly exposing serious flaws. A Workday hiring algorithm has been sued for allegedly rejecting applicants based on race and age, favoring white-associated names 85 % of the time and rejecting Black male candidates in some cases outright. UnitedHealth’s predictive model halted care for a 91‑year‑old man with a fractured leg, shifting $12,000 of monthly costs to his family because the algorithm prioritized historical spending over medical need.

At the same time, large language models are transforming software development. Experts compare the emerging dynamic to the film Ratatouille, where a non‑technical human provides intent and a powerful model delivers code, enabling “anyone can code.” However, the rapid spread of AI also creates new attack surfaces, illustrated by a manipulated dealership chatbot that sold a car for $1. These developments highlight the need for robust AI governance across data, model, infrastructure, application and oversight layers.

The convergence of bias‑related lawsuits, algorithmic harm in healthcare, and the coding boom driven by LLMs underscores growing risks and opportunities in AI deployment.