Ethical considerations and bias migration
The terms ethical considerations and bias mitigation are fundamental aspects of designing, developing, and deploying LLMs responsibly. Here’s what each of these terms broadly encompasses within the context of AI and ML:
- Ethical considerations: This encompasses a wide array of principles and practices aimed at ensuring that LLMs behave in ways that are considered morally acceptable and beneficial to society. It involves the following aspects:
- Respect for privacy: Ensuring that the LLM does not infringe on individuals’ privacy rights and complies with data protection regulations
- Transparency: Making the functioning of the LLM understandable to users, and clearly explaining the model’s capabilities and limitations
- Accountability: Establishing clear lines of responsibility for the outcomes produced by the LLM, including a framework for addressing any harm caused by the model’s actions
- Fairness: Ensuring that the...
