Before you get into how you could technically solve governance with software, you first need to build some policies and establish some visibility.
- Anthony Habayeb, Monitaur CEO from the recent CIO Chat.
January 2025 | What's new this month
Webinar: Advancing AI in Insurance: Navigating Regulatory Trends
AI is reshaping the insurance industry, offering new opportunities to enhance operations and manage risk. However, its rapid adoption poses significant compliance challenges, particularly with evolving regulatory expectations and generative AI’s implications. Insurers must navigate these complexities to ensure transparency, trust, and ethical use of AI.
Join AAIS on January 23rd at 12:00 pm CT for an engaging webinar to learn about the intersection of AI innovation and insurance regulation. Moderated by Chris Aufenthie, Director of Regulatory Filings at AAIS, the webinar will feature Anthony Habayeb, CEO and Co-Founder of Monitaur, and Mary Block, Director of Insurance Regulation at the Vermont Department of Financial Regulation. The discussion will highlight trends in AI adoption, practical steps to align with the NAIC AI Bulletin, and strategies to ensure transparency and explainability for regulators and consumers.
This link takes you to the AAIS webinar registration page.
The AI Fundamentalists
Contextual integrity and differential privacy: Theory vs. application with Sebastian Benthall
What if privacy could be as dynamic and socially aware as the communities it aims to protect? Sebastian Benthall, a senior research fellow from NYU’s Information Law Institute, shows us how privacy is complex. He uses Helen Nissenbaum’s work with contextual integrity and concepts in differential privacy to explain the complexity of privacy. Our talk explains how privacy is not just about protecting data but also about following social rules in different situations, from healthcare to education. These rules can change privacy regulations in big ways.
Data is the lifeblood of modern decision-making, and AI systems rely heavily on it. However, the quality and ethical implications of this data are paramount. Ethical data preparation is fundamental to the success of AI systems. It’s like ensuring the bricks and mortar used in building a house are sound. If the data is flawed, biased, or incomplete, the resulting AI system will be similarly flawed. This could lead to biased, unfair, and untrustworthy outcomes.
As artificial intelligence (AI) gains prominence in pathology and medicine, the ethical implications and potential biases within such integrated AI models will require careful scrutiny. Ethics and bias are important considerations in our practice settings, especially as increased numbers of machine learning (ML) systems are being integrated within our various medical domains. Such machine learning based systems, have demonstrated remarkable capabilities in specified tasks such as but not limited to image recognition, natural language processing, and predictive analytics. However, the potential bias that may exist within such AI-ML models can also inadvertently lead to unfair and potentially detrimental outcomes.
The global AI regulation landscape is fragmented and rapidly evolving. Earlier optimism that global policymakers would enhance cooperation and interoperability within the regulatory landscape now seems distant. Instead, we continue to see the policy process to regulate AI progress throughout the world at different stages and adopting different models, from policy statements to soft law, to tabled or adopted legislation. However, through our support of global businesses, we see the beginnings of a common global direction emerging on how to minimize the risks of AI use and create the structures to address the core principles of safe and ethical AI development and use that are becoming the cornerstones of global AI regulations. In order to develop these AI governance structures, businesses need to anticipate evolving legal requirements and regulatory approaches.
Tech law in 2025: A look ahead at AI, privacy and social media regulation under the new Trump administration Artificial intelligence harms, problematic social media content, data privacy violations – the issues are the same, but the policymakers and regulators who deal with them are about to change. As the federal government transitions to a new term under the renewed leadership of Donald Trump, the regulatory landscape for technology in the United States faces a significant shift. The Trump administration’s stated approach to these issues signals changes. It is likely to move away from the civil rights aspect of Biden administration policy toward an emphasis on innovation and economic competitiveness. While some potential policies would pull back on stringent federal regulations, others suggest new approaches to content moderation and ways of supporting AI-related business practices. They also suggest avenues for state legislation.
Artificial Intelligence (AI) is poised to shape society in profound ways, both beneficial and disruptive. Two emerging predictions for 2025 underscore the transformative potential of AI while highlighting the challenges society must address to harness its full benefits responsibly.
Artificial Intelligence (AI) is no longer a distant concept belonging to the realm of science fiction. In recent years, AI has grown from a collection of specialized tools into an all-encompassing force capable of transforming nearly every aspect of our lives. It is already making its mark in industries like healthcare, finance, and manufacturing, but its potential to shape the future goes far beyond automation and efficiency. From reshaping educational systems to transforming how we interact with our environments, AI promises to fundamentally alter the structure of society. In this article, we will explore the future of AI and its profound impact on various industries, education, and daily life. We will also address the ethical considerations that come with integrating AI into the fabric of society and discuss how we can ensure that its development benefits humanity.
As artificial intelligence (AI) continues to reshape industries, its integration into the insurance sector has emerged as a transformative force. By 2025, AI is not merely a tool but a strategic enabler redefining risk management, customer engagement, and operational efficiency. This article explores key trends in AI's application to insurance, highlighting the benefits, challenges, and future directions of this evolving landscape.
