Accuracy, compliance, and ethics in AI (PT. 1)
A benefits leader once told me, "I have no idea how many of my employees have cancer." It wasn't for lack of trying—the data was fragmented, reports were delayed, and insights remained unclear. Unfortunately, this is the reality for many benefits teams: they want to make data-driven decisions, but their available tools only hinder that goal.
These challenges extend beyond the benefits team. When benefits managers struggle to get clear answers, employees naturally face even greater hurdles. Over half of U.S. adults express confusion about their health benefits—a concerning statistic given how benefits impact physical, mental, and financial well-being. While technology can help, it requires thoughtful implementation.
At Avante, we apply technology where it's needed most and where it can significantly impact real-world scenarios—ones we discuss directly with affected individuals. This curious and careful approach ensures we deploy AI selectively and thoughtfully, always respecting those it serves. We build AI tools to enhance human decision-making, focusing on solving genuine problems rather than creating technology for its own sake. To simplify access to the right information at the right time, we follow clear principles that ensure technology serves benefits leaders and their plan members effectively.
How do we ensure our technologies are truly helping? We take a comprehensive approach to evaluating product performance.
Why Accuracy Alone Isn't Enough
AI performance extends beyond providing correct answers—it's about trust, reliability, and real-world impact. Generative AI models, like Large Language Models (LLMs), differ from traditional AI in their unpredictability. This requires a structured evaluation approach that considers not just accuracy, but also fairness, safety, consistency, and other crucial qualities.
That's why we've developed a comprehensive evaluation framework. Our products must do more than provide technically "correct" responses—they must avoid being misleading, biased, or incomplete. These multiple dimensions are crucial when evaluating new features and capabilities. It's truly a team effort: all our team members consider these aspects while building products, and we ask our customers to do the same. Our goal is to create products that serve all customers while providing an accurate, safe, and useful experience that simplifies their work and lives.
In this blog series, we'll explore the core principles guiding our AI development, starting with the foundation: Safety & Security.
Safety & Security: The Foundation
Safety and Security form the foundation of every product we build. These principles ensure users can interact confidently with our systems, knowing their well-being and information remain protected.
Safety means ensuring our products provide appropriate and ethical responses within its intended scope. We maintain clear boundaries around what our products will and won't address, keeping responses relevant and avoiding off-topic or potentially harmful queries. We also recognize when questions are too complex or sensitive for AI alone, redirecting to human support when needed. Safety includes strict content guidelines that prevent engagement with harmful content, such as hate speech, violence, or discussions of self-harm.
Security focuses on protecting user data and maintaining privacy throughout AI interactions. We implement robust data privacy measures to prevent unauthorized access and breaches. This creates a secure environment where users can safely share necessary information, knowing their conversations remain confidential. Our platform maintains SOC 2 and HIPAA compliance, and we build on trusted leaders like Open AI to meet industry-leading security standards.
Next Time:
In the next post, we'll share how we've prioritized groundedness, transparency, and conversation quality in our products to ensure AI isn't just producing answers, but producing the right answers, in a way people can trust.
