As AI systems become integral across industries, ensuring reliability, fairness, and trustworthy performance is critical. From healthcare and finance to autonomous driving and customer service, AI systems present unique challenges requiring comprehensive quality testing to manage risks, foster trust, and achieve consistent performance in diverse, real-world applications.

As AI transforms industries and reshapes business landscapes, organizations face a dual challenge: harnessing its immense potential while ensuring responsible and ethical deployment. At code4thought, we understand that achieving this balance requires not only adherence to global standards but also the practical tools to implement them effectively.

As businesses increasingly leverage AI for streamlined recruitment due to its ability to quickly sift through vast applicant pools, a clear-eyed view of fairness is essential. The New York City’s Bias Audit Law is an unprecedented regulation that fosters fairness by mandating bias audits in AI-assisted hiring tools. Also known as Local Law 144, it marks a crucial step towards ensuring AI doesn’t

Amidst the transformative wave of artificial intelligence (AI) invoked in the digital ecosystem, the Organization for Economic Cooperation and Development (OECD) has introduced a comprehensive set of AI principles, a framework aimed at guiding responsible and effective AI adoption. These principles promise to revolutionize industries and redefine the way businesses operate.

Today, software permeates every aspect of life, and artificial intelligence (AI) is becoming increasingly integral to business operations. As AI systems grow in complexity and ubiquity, ensuring their reliability, safety, and effectiveness is paramount.

Large Language Models (LLMs) have garnered significant attention since the mass-market introduction of pre-trained chatbots in late 2022. Companies keen to take advantage of LLMs quickly incorporate them into their services and processes.

To address the risks and challenges of AI adoption and use, the National Institute of Standards and Technology (NIST) has developed the AI Risk Management Framework (AI RMF), a voluntary framework designed to help organizations manage the risks associated with AI technologies.