Help, My AI Is Hallucinating!

Imagine you are a lawyer and your court case is dropped because you argued with quotes from non-existent court documents thanks to time-saving AI support. What sounds like a bad joke to us is a real problem in practice: large generative AI models such as ChatGPT, Copilot or Gemini sometimes come up with answers that sound convincing but have little to do with reality. In the case of legal questions, this can even be the case in 69 to 88 percent of cases. Sounds absurd? Welcome to the world of AI hallucinations!

Why Does AI Hallucinate at All?

You could say “AI is made to please you”. Large generative AI models are designed in such a way that they always provide an answer if possible and thus satisfy the user. Have you ever found yourself in an (unsuccessful) discussion with ChatGPT or another model because you were sure that the answer provided was wrong?

The cause is quickly explained: Generative AI models are true masters at recognizing patterns and formulating plausible sentences. However, they do not really “understand” what they are writing.

This problem is exacerbated by the sheer volume of data with which modern LLMs are trained. The models process petabytes of information, which makes LLMs digital all-rounders. Like a consultant proudly proclaiming “we’ve done this before”, they draw seemingly appropriate answers from their vast store of knowledge. But quantity is no substitute for quality: a lot of knowledge does not automatically mean the right knowledge for the respective context.

If the model does not find any suitable information for a very specific question – for example, because the training data is incomplete or too general or the context is missing – then it concocts an answer with a high probability of being correct (based on the data). The result: seemingly well-founded statements that are simply made up. In technical jargon, this is known as “confabulation” or AI hallucination.

Why Is This So Problematic?

The danger is obvious: users rely on the seemingly correct answers – and in the worst case, make the wrong decisions. This can quickly become expensive, especially in companies where compliance, documentation or customer communication are involved. Trust in AI dwindles and the benefits fall by the wayside.

How Does MORESOPHY Deal With the Hallucination Problem?

We have substance instead of show. We know that AI can’t do everything, and we communicate this clearly. We have created a basis for the implementation of AI-supported projects in order to prevent hallucinations and keep them to a minimum. We use hybrid AI for this. Our patent-pending DAPHY® technology combines the creative power of generative AI with the analytical precision of classic data models. What does that mean in concrete terms?

• Focus on data: We process company data intelligently using algorithms from the field of machine learning in order to make it usable for specific tasks.
• Transparency and traceability: Every answer can be backed up with sources on request. This means it is always clear where the information comes from and, in case of doubt, it is easy to check whether it is correct.
• Automated, controlled prompting: DAPHY® generates prompts automatically and context-sensitively and transfers them to the generative AI together with the relevant data for generating answers. This ensures that it operates within a predefined framework and reduces hallucinations.

MORESOPHY keeps AI down to earth

Of course, even the best AI can be wrong – but with our technology, we significantly minimize the risk of hallucinations. You receive comprehensible, verifiable results that help you move forward. This is how generative AI becomes a reliable partner and leaves the storytellers behind.

Curious to find out more? Contact us – we will be happy to show you how AI can make a difference in your company.