In an era where artificial intelligence (AI) and data are reshaping industries, the relationship between data governance and generative AI has become increasingly significant. Generative AI is revolutionizing how businesses operate. However, this rapid advancement also brings challenges that must be addressed through robust data governance. Tech Target brought this interesting topic to our attention in their article, “Generative AI shines spotlight on data governance and trust.”
Generative AI models rely on high-quality data to function effectively. Data governance plays a crucial role in ensuring that the data used to train these models is accurate, complete and free from biases. Poor data quality can lead to flawed AI outputs, which can have serious implications, especially in critical areas like healthcare, finance and law.
As generative AI continues to evolve, the need for strong data governance will only grow. Organizations that invest in robust data governance frameworks will be better positioned to leverage the benefits of generative AI while mitigating its risks. This includes ongoing monitoring and updating of governance policies to keep pace with technological advancements and regulatory changes.
The biggest challenge is that most organizations have little knowledge on how AI systems make decisions and how to interpret AI and machine learning results. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms.
Melody K. Smith
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