3 Review(s)

Here are some potential areas covered in such a book:Bias and Fairness: Generative AI models trained on biased data can perpetuate stereotypes and discriminatory outputs. The book would discuss methods to mitigate bias, like employing diverse datasets and fairness checks.Misinformation and Deepfakes: Generative AI can create highly realistic but fake content, potentially leading to the spread of misinformation. The book might explore solutions like embedding authenticity markers or improving media literacy.Privacy Concerns: Training data might contain sensitive information. The book could discuss data anonymization techniques and user consent protocols.Accountability and Transparency: When AI-generated content causes harm, it's crucial to pinpoint responsibility. The book might explore building explainable AI models and establishing clear ownership of outputs.