Part 10/12:
Addressing challenges, Soin admits that biases can inadvertently creep into AI systems—such as rejection biases based on geography or ethnicity—and must be actively managed. Transparency is vital, so users should be aware when they are interacting with AI rather than humans. Misuse, deepfakes, and data security pose additional threats.
He stresses that AI developers must implement safeguards, regularly audit systems for biases, and ensure proper deployment protocols to prevent data poisoning and prompt injections that could manipulate AI responses or compromise security.