Privacy Violations
AI can expose personal data.
Safeguards involve:
- avoiding sensitive data,
- using anonymized datasets,
- reviewing privacy policies,
- and adhering to data protection laws.
Exploitation and Intellectual Property Concerns
AI use of creative works without compensation or permission.
It’s crucial to ensure:
- outputs comply with copyrights,
- provide proper attribution,
- and maintain transparency about the use of pre-existing content.
Misinformation and Hallucinations
AI may generate incorrect or fabricated information, often based on outdated or biased training data.
To mitigate this:
- fact-check outputs,
- use models with updated data,
- and implement safeguards to detect and correct errors.
Bias and Discrimination
Bias can emerge at various stages of the AI lifecycle, reinforcing stereotypes or marginalizing groups.
To reduce bias:
- craft inclusive prompts,
- use diverse training data,
- review outputs for fairness,
- and consider bias mitigation tools.