- AI Introduction
- Narrow AI
- Strong AI
- Nueral Network
- Deep Learning
- AI Perceptrons
- AI Historical Context
- AI Types
- Problem Solving Using AI
- AI Use Cases In Real Life
- AI Advantages Disadvantages
- AI Tools
- Cognitive AI
- Symbolic AI
- AI Ethics
- Responsible AI
- AI Multi Model Networks
- AI Genetic Algorithms
- AI Multi Agent Systems
- AI Prompt Programming
- AI Training Your Embeddings
- AI CCN Architecture
- AI Pre Trained Networks
AI Ethics.
AI ethics is a multidisciplinary field that guides the development and use of artificial intelligence (AI) to ensure it aligns with human values.
AI ethics principles include:
Fairness:
Avoiding bias that could marginalize vulnerable groups or exacerbate prejudice
Transparency:
Ensuring AI systems are transparent and explainable
Accountability:
Establishing mechanisms to ensure responsibility for AI systems and their outcomes
Privacy:
Protecting privacy and establishing adequate data protection frameworks
Security:
Avoiding unwanted harms and vulnerabilities to attack
Societal impact:
Ensuring AI systems benefit all human beings, including future generations
Respect for persons:
Protecting individuals with diminished autonomy
Some other principles of AI ethics include: Respecting the law and acting with integrity, Being objective and equitable, and Fostering diversity.
Organizations are developing AI codes of ethics, also called AI value platforms, to provide guidance on ethical decisions. Intergovernmental entities like the United Nations and the World Bank are also raising awareness and drafting agreements for AI ethics globally