Ethical Considerations and Best Practices for Using Large Language Models in Decision - Making

Large language models (LLMs) like GPT -4 and BERT have revolutionized the way critical sectors make decisions.Independent of the ability to train such models with multiple data sources, state -of -the -art LLMs such as GPT -3 have exhibited remarkable capacity for producing realistic textual output, and conversing with users in a coherent manner.Over time, as LLMs become more sophisticated and are used by a broad range of organizations, they will have the capacity to shape decision -making and in some cases become decision makers in various fields such as the healthcare, financial, governmental and other sectors.However, there is an issue of ethical concerns when relying on the imperfect or biased LLM in making crucial decisions.In this white paper we look into how LLMs are already being used to suggest or even dictate decisions that affect people's lives; review the dangers posed by bias, accountability, and explainability of LLMs; explain why protecting standards is important but difficult due to present technological restraints; and give considerations on best practices for proper usage of LLMs in essential applications. The critical success factors explained are the acquisition of training datasets that are diverse and of high quality, integration checks with human involved in the process, audits of the system on a continuous basis, the provision of solutions which are explicable and transparent and clarity on the standards of the performance of the system or measures for risk control.