## 2 Related Research
### Large Language Models and Chatbots  
A chatbot such as ChatGPT (Chat Generative Pre-Trained Transformer) is a software application (generally on-line) that typically utilises GenAI and an LLM. When considering chatbots in e-commerce, there are two approaches to interactions: (a) using _formal_ language and (b) using _informal_ (possibly colloquial language which is generally nationality and ethnically specific [36]) language used in ordinary or familiar conversation [37]. Figure 1: A model of _micro, meso_, and _macro_ level dangers for GenAI (source: [24]). As discussed in [37], the results derived \"through the mediating role of 'parasocial interaction\" [37] show that when chatbots adopt an informal language style customers' reactions are positive with increased use and a positive brand awareness. Parasocial interaction (PSI) refers to a psychological relationship experienced by an audience in their mediated encounters with performers in the mass media and on-line platforms [37; 38; 39; 40; 41]. The goal of a chatbot is to maintain a conversation with a user in natural language and simulate how a human would behave as a conversational partner [34]. ChatGPT is a transformer-based deep neural network-enabled model capable of accepting natural language prompts as input based on LLMs [42]. There is an interesting parallel between the concept of a chatbot using GenAI and LLMs and the Turing test (devised in 1950) [34]. However, notwithstanding that the Turing test is not representative of AI, in the opinion of many in human-chatbot interactions \"ChatGPT not only passed but obliterated the Turing test\" [34]. While the core function of a chatbot is to mimic a human conversationalist, GenAI-driven chatbots have demonstrated the capability to: (a) write and debug computer programs, (b) compose music, stories, and drama scripts, (c) draft student essays and assignments, (d) answer test questions (on occasion above the level of a human), (e) generate business ideas, (f) write poetry and song lyrics, (g) translate and summarise text, (h) emulate a Linux system, (i) simulate entire chat rooms, (j) play games (like tic-tac-toe), or (k) simulate an ATM. The scope, and the related potential threats, for GenAI and chatbots is clear [20; 22; 23; 34; 43; 44; 45]. Turning to the limitations and issues in GenAI models and ChatGPT:  
1. There is a recognition by OpenAI (OpenAI: [[https://openai.com/](https://openai.com/)]([https://openai.com/](https://openai.com/)) (accessed on 10 December 2023)) that ChatGPT \"sometimes writes plausible sounding but incorrect or nonsensical answers\"; a feature common to LLMs often termed \"hallucination\". To address (or at least mitigate) hallucination, ChatGPT operates a reward model which is predicated on \"human oversight\". However, the reward model can be over-optimised and thus hinder performance, which is an example of an optimisation pathology known as Goodhart's law [46]. 2. ChatGPT has limited knowledge of events that occurred after September 2021 resulting in significant errors. Moreover, as discussed in Section 5.4, errors (e.g., inaccurate translation) can be the result of semantic misunderstanding or the language corpus. 3. In training ChatGPT, human reviewers preferred longer answers, regardless of actual comprehension or factual content. Additionally, training data also suffers from algorithmic bias, which may be revealed when ChatGPT responds to prompts including descriptors of people. In one instance, ChatGPT generated a rap indicating that women and scientists of colour were inferior to white male scientists. 4. There is an issue with plagiarism by GenAI and therefore by ChatGPT. It is necessary to address this problem which is a recognised problem in the education field [20; 30]. 5. In an attempt to mitigate plagiarism, it has been reported that OpenAI (for ChatGPT) has investigated using a digital watermark for text generation systems to combat \"bad actors using their services for academic plagiarism or spam\".