Summary  
This chapter covers programming techniques for ensuring ethical AI use, such as bias detection and mitigation, transparency interfaces, and human-in-the-loop controls.

General domain of usage  
Marketing

AI predicts user preferences, but too much tracking becomes intrusive.

**+** Stores suggesting relevant products.</br>
**-** Hyper-targeted messages based on private details.

Users must understand how personalization works and have control over it.

Users appreciate helpful experiences but dislike manipulation or secrecy.

**+** Companies that clearly explain how AI works and allow user control build loyalty.

Transparency creates trust; manipulation destroys it.

AI reflects the quality of its training data. Biased data creates unfair outcomes.

**-** Hiring AI rejecting women due to biased résumé data.
**-** Marketing tools excluding certain groups.

Requires fairness testing, reviewing data sources, and keeping humans in the loop.

Comprendere le regole fondamentali e i rischi nel marketing digitale. Focus sui principi base della privacy dei dati, sulle politiche delle piattaforme, sull'uso etico dei dati e sulla gestione della brand safety, inclusi i metodi per prevenire e rispondere a potenziali rischi e crisi.

Uso Etico dei Dati e IA nel Marketing

Principali sfide etiche