Quest Global has partnered with code4thought to conduct an independent Bias Testing Audit of an Automated Employment Decision Tool (AEDT) under New York City’s Bias Law (Local Law 144) using code4thought’s NYC AI Bias Audit service.
Quest Global Partners with code4thought for NYC AI Bias Audit Read More »
Generative AI (GenAI) is revolutionizing industries ranging from content generation and software engineering to healthcare and finance. Unlike traditional AI systems, GenAI models generate dynamic outputs, introducing significant challenges in testing and validation.
Generative AI Quality Testing: A Standards-Based Approach for Reliability Read More »
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.
Advanced AI Quality Testing: Ensuring Robust and Trustworthy AI Systems Read More »
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.
The Ultimate Guide to AI Governance Standards Read More »
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
Ensuring Fairness in AI-Assisted Hiring: Lessons Learned from the NYC Bias Audit Law Read More »
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.
OECD AI Principles: Guardrails to Responsible AI Adoption Read More »
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.
OWASP Top 10 Vulnerabilities for Large Language Models (LLM): Impact and Mitigation Read More »
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.
The London AI Summit 2024 was an invaluable opportunity to engage with AI thought leaders, industry experts, and practitioners and discuss the ever evolving landscape of this field. If we had to give a one-liner about what we learned or sensed there, this is the need for pragmatic AI governance.
For Good AI Governance, We Need to Be Pragmatic Read More »
