The importance of quality assurance processes has never been more important. As a result, computing resource management becomes particularly challenging in the age of generative AI. The key to reducing data complexity lies in leveraging structured data , such as schema markup. Therefore, I have modified Zdenko Vrandecic’s original quote “In a world of infinite content, knowledge becomes valuable” to the following: “In a world filled with endless [AI-generated] content, [Reliable] knowledge becomes valuable” Even the impressive Amsive team (led by the amazing Lily Ray) described this, describing the handling of unstructured data as an important aspect of AI readiness: “The lack of structure places a burden on Large Language Model (LLM) developers to provide the missing structure and help their tools and systems continue to evolve.
As LLM and AI tools seek real-time information, they will austria business fax list rely on signals such as search engines to determine the trustworthiness, accuracy, and reliability of sources”. This brings me to a couple of new metrics that I will delve deeper into, but for now let’s focus on the legal side.
Legal Organizing unstructured data, especially when dealing with personally identifiable information (PII), requires compliance with data protection laws such as GDPR and local regulations. Fundamental considerations include obtaining consent, implementing anonymization or pseudonymization, ensuring data security, practicing data minimization, maintaining transparency, and seeking legal guidance. Complying with these measures is critical to avoiding legal consequences, including fines and reputational damage.