Mike HeapMike is an experienced Product Manager who focuses on all the “non-development” areas of My AskAI, from finance and customer success to product design, copywriting, testing and more.
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As advancements in artificial intelligence (AI) continue to accelerate, a recurring topic of discussion is AI hallucination – the generation of fictitious or inaccurate answers by AI tools like ChatGPT. Although AI technology is improving daily, reaching 100% accuracy remains an elusive goal. This blog post delves into the reasons behind this, such as the ever-changing nature of facts and the varying human interpretations of data.
Facts in Flux: How the Temporal Nature of Facts Affects AI Accuracy
AI hallucination proves to be a challenge due to the dynamic nature of facts. As our understanding of the world evolves, so do the "facts" we hold to be true. For instance, ‘facts’ regarding the fastest speed at which something could travel or the health benefits of certain substances have undergone significant changes in the last few hundred years. This fluid landscape of facts presents a challenge for AI to remain current and maintain a universally accepted truth.
A Matter of Perspective: Differing Human Interpretations and Their Impact on AI Responses
Another factor contributing to the difficulty of eliminating AI hallucination is the differing human interpretations of data. The way questions are framed and the perspective from which they are asked play a crucial role in the answers received. For example, two political parties may provide different answers to a question about immigration numbers, both justifiable based on their interpretation of data. AI may struggle to provide a definitive answer in such situations due to their inherent subjectivity.
The Limits of AI Accuracy: Balancing Expectations and Reality
AI may achieve impressive levels of accuracy, reaching up to 90% or even 95% or more. However, surpassing that threshold is unlikely due to the varying human perceptions of facts. AI might be able to stop hallucinating entirely fabricated information, but it cannot guarantee 100% accuracy when it comes to facts, as subjectivity and varying perspectives come into play.
A Possible Solution: Harnessing Predefined Truthful Data Sets for AI
One approach to mitigate the problem of AI hallucination is to provide AI with a reference data set that has already been determined to be factually correct. This could include encyclopedias, company information, or legislation. By instructing AI to use only this information to formulate answers, the chances of receiving inaccurate or fictitious answers are significantly reduced. However, this approach still relies on humans agreeing on what constitutes the "truth."
Conclusion
The topic of AI hallucination remains a captivating yet challenging aspect of artificial intelligence. Achieving 100% accuracy in AI-generated answers may remain an unattainable goal due to the ever-changing nature of facts and the differing ways humans interpret data. By understanding these limitations, and using tools like My AskAI to ensure you only use verifiable information from which you answer questions then you can get closer to your ‘truth’.
