March 4, 2025
Ethical Considerations and Best Practices in LLM Development
Bias is inherent to building a ML model. Bias exists on a spectrum. Our job is to tell the difference between the desirable bias and the one that needs correction. We can identify biases using benchmarks like StereoSet and BBQ, and minimize them with ongoing monitoring across versions and iterations. Adhering to data protection laws is not as complex if we focus less on the internal structure of the algorithms and more on the practical contexts of use. To keep data secure throughout the model’s lifecycle, implement these practices: data anonymization, secure model serving and privacy penetration tests. Transparency can