7 ways to reduce AI-generated errors
And a completely AI-generated post (except for my comments in Italics)
In using AI to research history I know a lot about, I kept getting terrible errors. AI must be fact-checked, evidently. But I was pleased that when I asked it how such errors occur (it baffles me), its answer in my limited experience is spot on. This is what Venice.com replied.
Why & how AI sometimes generates errors/fabrications
A glaring error like fabricating information and attributing it to a non-existent person can occur due to several reasons, even when using advanced AI systems. Here are some potential explanations:
Data Inconsistencies: The AI model might have been trained on datasets that contained inconsistencies or errors. If the training data included incorrect or fabricated information, the model could reproduce it as if it were factual.
Hallucinations: AI models, especially those based on large language models (LLMs), can sometimes generate outputs that sound convincing but are entirely made up. This phenomenon is often referred to as "hallucination," where the model confabulates information that seems plausible but is not based on any actual data.
Lack of Real-Time Verification: AI systems, including myself, do not have real-time access to the internet to verify the accuracy of the information they generate. We rely on the data we were trained on, which might not always be up-to-date or accurate.
Contextual Misinterpretation: The AI might have misinterpreted the context of the query, leading to the generation of a fabricated quote. For example, if the prompt was vague or open to multiple interpretations, the model might have filled in the gaps with invented details.
Overgeneralization: AI models can sometimes overgeneralize from the patterns they have learned, leading to the creation of seemingly plausible but false statements. This can happen when the model extrapolates beyond the scope of its training data.
Human Error in Prompt Engineering: The way a prompt is crafted can significantly influence the output of an AI model. If the prompt was not specific enough or contained ambiguities, it could have led to the generation of a fabricated quote.
Strategies to reduce AI-generated errors
AI models, including myself, are trained to generate coherent and contextually relevant text based on patterns they have learned from large datasets. This means that even with specific instructions, there is still a possibility of generating information that sounds plausible but is not factual.
That said, providing clear and specific instructions can significantly improve the quality and accuracy of the output. Here are some strategies you can use:
Explicit Instructions: Clearly state that you want only factual information and no fabricated quotes or data. For example, "Use only verified facts and real quotes from reputable sources. Do not include any fabricated information or quotes from non-existent sources. Cite specific examples and case studies where possible, and provide references for all claims made."
Specific Examples: Ask for specific examples or case studies that can be easily verified. This can help ground the narrative in real-world applications and reduce the chance of hallucinations.
Cite Sources: Request that the AI cite specific sources for the information provided. This can help you verify the accuracy of the content and ensure that it is based on reliable data.
Be Specific, Avoid Vague Prompts: Provide clear and specific prompts to reduce the chance of the AI model filling in gaps with fabricated information. For example, instead of asking for a general overview, ask for a detailed analysis.
Follow-Up Questions: Ask follow-up questions to delve deeper into specific points. This can help identify any inconsistencies or fabricated information in the initial response.
Verify Information: Always cross-reference the information provided by AI with reliable sources.
Stay Updated: Keep abreast of the latest developments and trends to ensure that the information generated by AI is current and relevant.
By being specific in your instructions, you can increase the likelihood of receiving accurate and reliable information from AI systems. However, it's always a good practice to verify the information independently to ensure its accuracy.
A completely AI generated post (except for my comments in Italics)
AI, tell me a bedtime story in 300 words or less.