AI Chatbots Make Mistakes, Too

GenAI chatbots, despite their advancements, are prone to making mistakes in various ways, stemming from their inherent limitations. Many find chatting with LLMs like ChatGPT offers significant potential in enhancing the speed of delivery and empowering ease-of-use experiences. 

Many use these tools without understanding that misinformation and disinformation can arise due to flawed training data or inadequate grounding. While extremely useful, these LLMs or foundation models used to create these chat interfaces lack emotional intelligence and morality. Recognizing these limitations is essential for designing effective and responsible AI and GenAI chatbot interactions.

Let’s explore how these limitations manifest in three key areas:

Misinformation and Disinformation:

Chatting with your LLM interface—some call it an AI chatbot—can inadvertently propagate misinformation or disinformation due to its reliance on the data it’s trained on. If the training data contains biased or incorrect information, the chatbot may unknowingly provide inaccurate responses to users. Additionally, without proper grounding, where prompts are based on high-quality data sets, AI chatbots may struggle to discern between reliable and unreliable sources, leading to further dissemination of false information.

For instance, if a chatbot is asked about a controversial topic and lacks access to accurate data to form its response, it might inadvertently spread misinformation.

Lack of Emotional Intelligence and Morality:

AI chatbots lack emotional intelligence and morality, which can result in insensitive or inappropriate responses. Even with extensive training, they may struggle to understand the nuances of human emotions or ethical considerations. Similarly, in scenarios involving moral dilemmas, AI chatbots may provide responses that overlook ethical considerations, as they lack the ability or simply cannot perceive right from wrong in a human sense.

Limited Understanding and Creativity:

Despite advancements in natural language processing, AI chatbots still have a limited understanding of context and may struggle with abstract or complex concepts. This limitation hampers their ability to engage in creative problem-solving or generate innovative responses. Without grounding in diverse and high-quality data sets, AI chatbots may lack the breadth of knowledge necessary to provide nuanced or contextually relevant answers.

Consequently, they may provide generic or irrelevant responses, especially in situations that require creativity or critical thinking. When systems like this are pushed to go beyond or asked to be creative.

𝗡𝗼𝘁𝗶𝗰𝗲: The views expressed in this post are my own. The views within any of my posts or articles are not those of my employer or the employers of any contributing experts.