Anastassia Kornilova is the Director of Machine Learning at Trustible. Anastassia translates research into actionable insights and uses AI to accelerate compliance with regulations. Her notable projects have involved creating the Trustible Model Ratings and AI Policy Analyzer. Previously, she has worked at Snorkel AI developing large-scale machine learning systems, and at FiscalNote developing NLP […]
Despite the explosive growth of AI, most enterprises remain unprepared to manage the very real risks that come with its adoption. While the opportunities are vast—from smarter products to more efficient operations—the path to realizing AI’s full potential is fraught with challenges around performance, cybersecurity, privacy, ethics, and legal compliance. Without a strong AI governance […]
In the early hours of July 1, 2025, the Senate overwhelmingly voted to strip the proposed federal moratorium on state and local AI laws from the Republican’s reconciliation bill. The moratorium went through several re-writes in an attempt to salvage it, though ultimately 99 Senators supported removing it from the final legislative package. While the political […]
At Trustible, we understand the challenges insurers face in navigating the evolving AI regulatory landscape, particularly at the state-level in the U.S. That’s why we’re excited to introduce the Trustible US Insurance AI Framework, designed to streamline compliance by synthesizing the latest insurance AI regulations into one comprehensive, easy-to-comply with framework embedded in our platform.
On July 11, 2024, the New York Department of Financial Services (NY DFS) released its final circular letter on the use of external consumer data and information sources (ECDIS), AI systems, and other predictive models in underwriting and pricing insurance policies and annuity contracts. A circular letter is not a regulation per se, but rather a formalized interpretation of existing laws and regulations by the NY DFS. The finalized guidance comes after the NY DFS sought input on its proposed circular letter, which was published in January 2024.
In our final blog post of this AI Policy series (see Comprehensive AI Policy and AI Use Policy guidance posts here), we want to explore what organizations should make available to the public about their use of AI. According to recent research by Pew, 52 percent of Americans feel more concerned than excited by AI. This data demonstrates that, while organizations may understand or realize the value of AI, their users and customers may harbor some skepticism. Policymakers and large AI companies have sought to address public concerns, albeit in their own ways.
In this series’ first blog post, we broke down AI policies into 3 categories: 1) a comprehensive organizational AI policy that includes organizational principles, roles and processes, 2) an AI use policy that outlines what kinds of tools and use cases are allowed, as well as what precautions employees must take when using them, and 3) a public facing AI policy that outlines core ethical principles the organization adopts, as well as their stance on key AI policy stances. In this second blog post on AI policies, we want to explore critical decisions and factors that organizations should consider as they draft their AI use policy.
As organizations increase their adoption of AI, governance leaders are looking to put in place policies that ensure their AI deployment aligns with their organization’s principles, complies with regulatory standards, and mitigates potential risks. But where to start in developing your policies can oftentimes be overwhelming. Let’s start with some important context. AI Policies break […]
As organizations increase their adoption of AI, governance leaders are looking to put in place policies that ensure their AI deployment aligns with their organization’s principles, complies with regulatory standards, and mitigates potential risks. But where to start in developing your policies can oftentimes be overwhelming.
For enterprise AI leaders and governance experts, developing Policies to guide the appropriate use and risk mitigation of AI can be a daunting task. Moreover, understanding whether that policy is compliant with AI regulations and standards can be costly, time-consuming, and overwhelming. Trustible’s AI Policy Analyzer is an expert AI system designed to simplify this process, providing an automated analysis of your existing AI policies in just minutes.
