In this article, we present an exploration of ten indispensable ethical AI indexes that are paramount for the responsible AI development and deployment of Large Language Models (LLMs) through the intricate processes of data training and modeling.
Within our compassionate AI Lab, we have diligently worked to create a series of AI indexes and measurement criteria with the objective of safeguarding the interests of future generations and empowering humanity. The names of the ten ethical AI indexes are as follows:
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- AI Cage Index
- AI Traps Detection Index
- Bias Detection and Mitigation Index
- AI Hostility Data Training Index
- Data Source Diversity Index
- Data Collection Practices Index
- Transparency in Data Usage Index
- Ethical Data Collection Practices Index
- Data Anonymization and De-identification Index
- Human Oversight and Review Index