{"id":12288,"date":"2023-12-01T20:56:08","date_gmt":"2023-12-01T20:56:08","guid":{"rendered":"https:\/\/tokendices.com\/what-are-ai-hallucinations-and-how-to-prevent-them\/"},"modified":"2023-12-01T20:56:08","modified_gmt":"2023-12-01T20:56:08","slug":"what-are-ai-hallucinations-and-how-to-prevent-them","status":"publish","type":"post","link":"https:\/\/tokendices.com\/what-are-ai-hallucinations-and-how-to-prevent-them\/","title":{"rendered":"What Are AI Hallucinations and How to Prevent Them?"},"content":{"rendered":"

Coinspeaker<\/a>
\nWhat Are AI Hallucinations and How to Prevent Them?<\/a><\/p>\n

What comes to mind when you hear the term “hallucinations”? For most of us, this brings up images of insomnia-induced visions of things that aren\u2019t real, schizophrenia, or some other sort of mental illness. But have you ever heard that Artificial Intelligence (AI) could also experience hallucinations?<\/p>\n

The truth is that AIs can and do hallucinate from time to time and this is an issue for people and companies that use them to solve tasks. In this guide, we\u2019ll take you through AI hallucinations, what causes them, and what their implications are.<\/p>\n

AI Hallucinations Defined<\/h2>\n

An AI hallucination is a scenario where an AI model begins to detect language or object patterns that don\u2019t exist and this affects the outcome that they are given. Many generative AIs work by predicting patterns in language, content, etc. and giving responses based on them. When an AI begins to generate output based on patterns that don\u2019t exist or are completely off base from the prompt they were given, we refer to this as ‘AI hallucination.’<\/p>\n

Take, for example, your customer service chatbot on an e-commerce website. Imagine you ask it when your order will be delivered and it gives you a nonsensical answer unrelated to it. That is a common case of AI hallucination.<\/p>\n

Why Do AI Hallucinations Happen?<\/h2>\n

Essentially, AI hallucinations happen because generative AI is designed to make predictions based on language but doesn\u2019t actually \u2018understand\u2019 human language or what it is saying. For example, an AI chatbot for a clothing store is designed to know that when a user types the words \u2018order\u2019 and \u2018delayed\u2019, its response should be to check the status of the customer\u2019s order and tell them that it is on the way or has already been delivered. The AI doesn\u2019t actually \u2018know\u2019 what an order is or what a delay is.<\/p>\n

So if a user types in the chatbot that they would like to delay their order because they won\u2019t be home, such an AI might keep telling them the status of their order without actually answering their query. If you spoke to a human who understands language nuance, they would know that just because certain words are in a prompt doesn\u2019t mean the same thing every time. But AI, as we\u2019ve established, does not. Instead, it learns to predict patterns in language and works based on those. Hallucinations also tend to occur when a user gives a prompt that is poorly constructed or too vague and this can cause confusion. Typically, AIs will become better at language prediction over time but AI hallucinations are still bound to happen now and again.<\/p>\n

Types of AI Hallucinations<\/h2>\n

Typically, AI hallucinations occur in several different ways:<\/p>\n