The main ethical considerations include: Bias in AI Outputs: AI systems may inadvertently reinforce biases present in the training data, leading to biased outcomes. Addressing this involves using diverse datasets and implementing bias detection tools. Security and Privacy: Protecting sensitive data from malicious attacks and unauthorized access is crucial. Strong security measures and regular audits are necessary. Regulation & Compliance: Staying updated with evolving AI regulations and ensuring compliance with global standards to mitigate legal risks.