Abstract
AI communication in the form of chatbots has brought about a new paradigm of communication and service delivery through the use of large language models (LLMs) like GPT. However, as these technologies are applied in daily life, questions about the bias of the answers given by chatbots also arise. In this paper, the focus will be on discussing the ethical considerations of AI chatbots, including the detection of bias, fairness, and transparency. Bias detection techniques described in the study include fairness metrics, sensitivity analysis, and bias correction algorithms. It also emphasizes the importance of diverse training data and the integration of ethical protocols to avoid radiating bias. The consequences of bias in AI chatbots are explored in a range of cases and actual-life scenarios in settings including healthcare, recruitment, and customer relations and service. The study draws attention to the fact that more work has to be done to make certain that AI chatbots are designed and utilized in a way that is ethical and not deceptive.
Keywords
AI Chatbots, Bias Detection, Fairness Metrics, Transparency, Ethical AI, Bias Mitigation, Generative Pretrained Transformers (GPT), Chatbot Development, Ethical Guidelines, Artificial Intelligence