So why is GAI still stymied by poor data quality, and what should we be doing about it?
“Garbage in – Garbage out!” manifests in three primary ways for Gen AI. We see it first in the form of bias and hallucination in our response output when we allow the GAI to wander untamed data sources to provide us with answers. Uncontrolled access yields unpredictable and likely undesirable outcomes. We see it again prominently in the quality of answers we get when the questions or prompts we ask lack the direction or sophistication to get us true value. Your answers are only as good as the questions you ask. Finally, we see it in the form of incomplete or inaccurate responses if we point GAI toward our in-house data sources when they remain full of duplicates, poor-quality images, and incomplete and improperly associated files.