AI and Ethics

This lecture explores the potential of AI in creating smart environments that adapt to human emotions and behaviors, while also delving into the ethical implications of AI technologies. It discusses algorithmic fairness, dataset biases, and the societal impact of AI applications, highlighting issues such as facial analysis disparities and object recognition challenges. The lecture emphasizes the importance of responsible AI research, transparency, and accountability in addressing representational harms, biases in generative models, and the need for diverse and inclusive datasets. It also examines the ethical considerations in model testing, dataset maintenance, and the value of interdisciplinary collaboration in AI development.