As Artificial Intelligence (AI) becomes more deeply embedded in healthcare platforms, transparency is taking the center stage. Patients now rely on algorithms to guide their decisions, including what they eat, how they sleep, and how they manage chronic conditions. But when recommendations feel vague or unexplainable, trust begins to erode. Joe Kiani, Masimo and Willow Laboratories founder, is one of the leaders calling for greater clarity in how AI-powered systems operate. He emphasizes that transparency is not just a technical benchmark but a moral responsibility.

The latest innovation from Willow Labs, Nutu™, a digital health platform that delivers real-time, personalized insights based on metabolic and behavioral data, shows how transparency can be embedded from the ground up. It is not designed to issue rigid commands. Instead, it explains the reasoning behind each recommendation, helping users understand the connection between their data and the guidance they receive. In a field where sustained engagement is essential, clear and contextual communication is helpful and foundational.

Why Transparency Matters in Health Tech

AI-based platforms are powerful because they can identify patterns that are too complex for humans to detect. But that power comes with risk. When users don’t know how a system works or why it makes certain recommendations, they may feel skeptical, overwhelmed, or even misled.

This is especially true in health care, where trust is foundational. Patients need to believe that the guidance they’re receiving is based on sound evidence, not abstract calculations or hidden incentives. Transparency allows users to maintain agency. It enables them to question, learn and adapt rather than unthinkingly follow a recommendation they don’t fully understand.

From Black Box to Glass Box

Too many AI tools operate like “black boxes.” They take in data, run it through opaque models, and output recommendations without explanation. But patients aren’t data points. They’re individuals with real-world concerns and preferences. That’s why companies are shifting to a “glass box” model, one where users can see how decisions are made and feel confident that their data is being used responsibly.

For example, Nutu not only delivers insights but also shows which inputs contributed to them. Whether it’s a rise in stress, poor sleep, or unusual meal timing, the app connects the dots clearly. It builds confidence and reduces confusion.

Joe Kiani, Masimo founder, says, “Some of the early [Nutu] users that have been giving us feedback are saying really positive things about what it’s done for them.” That power depends on users trusting the insights they receive and understanding where they come from.

Empowering Users with Context

Transparency isn’t just about code, but also about communication. Health platforms need to explain their outputs in ways that feel accessible and supportive. That means avoiding technical jargon, providing context instead of raw data, and showing users how their behavior affects their outcomes.

Nutu offers personalized recommendations that are simple but informative. Instead of telling someone to “reduce stress,” it might highlight how late-night work or missed meals contributed to rising stress markers. Then, it offers specific, doable actions, like adjusting bedtime or taking short breaks during the day. By offering both explanation and guidance, it builds a bridge between analysis and action.

Transparency Supports Long-Term Engagement

Users are more likely to stick with platforms they understand. When feedback makes sense and aligns with lived experience, people are motivated to continue. On the other hand, if recommendations seem arbitrary or if changes in output aren’t explained, users may lose faith in the system. That drop in trust often leads to a drop in engagement.

Transparency needs to be treated as a core component of user retention. Long-term trust is essential for platforms designed to support chronic condition management, where consistency and confidence are everything.

Regulatory Pressures and Industry Expectations

Transparency isn’t just a user’s preference, but it’s increasingly a regulatory expectation. Agencies like the FDA and the European Commission are drafting guidelines that emphasize explainability in AI-driven medical tools. That includes requiring developers to provide a clear rationale for algorithmic decisions, particularly when they impact treatment, diagnosis or behavioral recommendations.

To stay ahead of these changes, many health tech platforms are prioritizing the documentation of how their algorithms interpret user data. By adapting their feedback systems to meet evolving regulatory standards, companies are positioning themselves for long-term success in an industry where accountability and transparency are increasingly critical.

Addressing Bias and Fairness Through Openness

Transparency also plays a crucial role in identifying and addressing bias. If users don’t know how an algorithm was trained or what data it prioritizes, it’s impossible to evaluate whether the system is working equitably. Open models and audit-ready systems allow researchers, partners, and users to identify when certain groups are being underserved. That’s the first step in building platforms that work well for everyone, not just a select few.

To ensure fairness, many platforms incorporate checks throughout their development process to monitor how different populations interact with, and respond to, recommendations. This ongoing evaluation helps developers adjust models accordingly, ensuring more equitable outcomes across diverse user groups.

Building Culture Around Ethical Use

For transparency to work, it must be part of a company’s culture, not just its codebase. That means involving teams from across the organization in conversations about how AI is used, what risks exist, and how to communicate with users openly.

Cross-functional teams, engineers, clinicians, behavioral scientists, and user experience designers collaborate to ensure that their guidance is as clear as it is helpful. This holistic approach supports the ethical use of technology and strengthens the user experience. It’s a reminder that transparency isn’t a feature. It’s a mindset.

The Future of Transparent Health AI

As AI continues to be integrated into health platforms, transparency will be a key factor in determining which systems will succeed. Users are increasingly aware of data ethics and are looking for platforms that treat them as partners rather than mere data points.

Companies that are open about how their systems operate, what users can expect, and the reasoning behind decisions are more likely to build trust and long-term engagement. In a healthcare landscape where accountability is paramount, companies that prioritize transparency are setting a new benchmark for trust and accountability.