The AI Hallucination Problem

AI has made significant strides in the recent years but it has a troubling weakness – it cannot truly replicate human language. Wondering why? The dirty little secret is that the AI system has the tendency to hallucinate. They cannot correctly interpret the data it has received. Keep reading to learn what AI hallucinations are and how dangerous they can be.

What is an AI hallucination?

Amid the exponential growth of AI experts believe that AI systems can create an output that is seemingly unrelated to its input. This faulty output is called “hallucination” where AI models create information that isn’t true or accurate. Thus with the rise of AI models the danger of disastrous outcomes also rises. Say for example if an AI medical scribe records your blood type as AB when it’s actually A+ it could prove fatal.

Why do AI models hallucinate?

AI systems make decisions based on training data. If the quality of the training data is biased or incomplete then it can definitely have a significant impact on the accuracy and performance of the AI system. The design of the AI system can also make it prone to hallucination. For instance, an AI model that is built to be extremely sensitive to even the slightest variations in the input data is likely to experience hallucinations than an AI model that is built to be more robust. Moreover, bugs in the AI model can also cause it to hallucinate. Lastly, the environment in which the AI system is trained or used can also impact its susceptibility to hallucination.

The dangers that AI hallucination pose

Legal implications: One of the most significant dangers that AI models pose is the risk of legal liability. We are aware that when AI models hallucinate they are prone to saying things that are not true. And when these false statements cause harm they are likely to sue. Not just developers, but also the organizations deploying these AI models are accountable for it.

Compliance issues: AI hallucinations also pose a risk when it comes to satisfying regulatory requirements. Organizations have strict compliance requirements that need to be adhered to. Although it is tempting to use AI models to automatically perform certain tasks the AI system could violate the compliance requirements that must be followed by an organization. This could pave the way for some disastrous effects on the organization.

Erode trust: AI has vast potential. But to attain this it must be trust worthy. Hallucination can inadvertently lead to the spread of false or misleading information. AI models that generate incorrect or misleading information can simply erode the trust humans have on machines. When users lose trust in this technology it will definitely hinder its adoption across a variety of other sectors also.

Impacts decision making: AI hallucinations can negatively impact crucial decision making. AI systems are being increasingly used in various fields like healthcare, finance and law for crucial decision making. AI hallucination can lead to poor decision making with unpleasant results and disastrous consequences.

Well, AI systems can sometimes go off the rails just to please the user and this is what we call “hallucination”. This hallucination problem is not something that is easy to fix. Yes, AI hallucination is the biggest challenge that everyone in the industry is trying to address. Experts are of the opinion that these hallucinations are one of the hardest problems to solve - simply that the deep neural network is very different from a human brain.