AI Ethics

[Technical Overview] The emergence of sophisticated AI technologies, particularly in generative models, has enabled the creation of highly realistic fake images and videos, commonly known as deepfakes. These deepfakes utilize machine learning techniques, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), to learn the complex patterns in image and video data and then generate new content that is often indistinguishable from real footage. The process typically involves training the model on a large dataset of target individuals, enabling the system to manipulate their appearance and actions in new, synthesized scenarios....

[Technical Overview] The increasing use of artificial intelligence (AI) and machine learning (ML) in tenant screening raises significant concerns about algorithmic bias, transparency, and fairness. Traditionally, tenant screening involved manual review of credit reports and rental history. However, with the advent of AI, automated systems are now used to generate risk scores based on complex algorithms. These algorithms often rely on historical data, which can inadvertently perpetuate existing societal biases. This can lead to discriminatory outcomes, where applicants from certain demographics are disproportionately denied housing opportunities without a clear understanding of the reasons behind the decisions....