AI-Safety Respecting Architectures for Use in Small and Medium Size Businesses

There are several best practices that can be followed to ensure AI safety respecting architectures for use in small and medium size businesses. One approach is to use open-source foundation models for building custom domain-specific LLMs. The best open models use public training datasets. OpenAI has developed a set of best practices applicable to any organization developing or deploying large language models (LLMs). These include publishing usage guidelines and terms of use of LLMs that prohibit material harm to individuals, communities, and society. They also recommend building systems and infrastructure to enforce usage guidelines.

A “human first” approach to designing AI systems for business involves prioritizing the needs and well-being of people. This includes paying attention to privacy and ensuring that AI systems are designed to protect the personal information of employees and customers.

One way to ensure privacy in AI systems for business is to use encryption and secure data storage methods. This can help prevent unauthorized access to personal information. Additionally, businesses can implement policies and procedures to ensure that personal information is only accessed by authorized personnel on a need-to-know basis.

Large Language Models (LLMs) for business AIs can be fine-tuned to support fairness, diversity, specific knowledge of the business, and promote worker happiness and satisfaction. This involves training the LLMs on data that reflects these values and minimizing potential sources of bias in the training data. Techniques such as learning from human feedback can also be used to improve the model’s behavior and ensure that it aligns with these values.

By fine-tuning LLMs with appropriate data, the AI can provide recommendations and feedback that are fair, respectful, and promote worker happiness and satisfaction.