Building trust in AI: A principled approach to ethical agent development

AI agents are no longer confined to labs and prototypes. They’re shaping how we live, work and make decisions. From customer service bots and self-driving cars to robotic surgical assistants and virtual companions, these systems now influence real outcomes in society. But with this growing influence comes an urgent question: How do we build AI agents that people can actually trust?

Trust isn’t something we can code in at the last minute. It has to be designed into the system from the start – woven into how agents learn, act and interact. This means thinking beyond performance or accuracy and embracing principles that prioritize human values, ethical decision-making and inclusive design.

These characteristics create tremendous opportunities but also introduce novel ethical challenges. As AI agents become more sophisticated and embedded in critical systems, establishing robust ethical frameworks becomes essential. Here are four key considerations that can guide a trustworthy approach to AI agent development.

1. Human-centered by design
AI agents should empower people – not replace or override them. That starts with clear roles and responsibilities.
Support, don’t supplant: Health care diagnostic tools can analyze data and suggest options, but doctors must make final decisions. The same goes for content recommendation engines or email writing assistants. They should enhance human productivity, not remove control.
Design for clarity: Interfaces that use natural language (like voice assistants) help users interact with agents in familiar ways.
Enable feedback: Learning agents that adapt over time – like personalized news feeds or spam filters – must let users correct them. Feedback loops are important to build trust and reliability over time.

Consider this: Robotic agents like the da Vinci Surgical System assist surgeons when they perform precise and minimally invasive procedures. These AI agents don’t perform surgeries autonomously, but they extend the surgeon's capabilities.

2. Building for everyone: Inclusivity as a priority
Building inclusive AI agents requires intentional design choices that address diverse user needs across various contexts. In short, trustworthy AI serves everyone – not just a privileged few.
Language and speech diversity: Virtual assistants must understand varied accents and dialects to serve global users equitably.
Cultural awareness: Chatbots for customer service need to incorporate cultural sensitivity training to handle inquiries appropriately across different regions and respond with the correct honorifics.
Health care equity: Medical AI agents should be trained on diverse patient data to provide accurate symptom assessment regardless of gender or ethnicity.

Designing for inclusivity means diversifying development teams, training datasets and user testing pools. Responsible innovation starts with responsible innovators.
If your AI agent only works well for some people, it’s not trustworthy for anyone.

3. Setting boundaries with AI agent governance
Autonomy without oversight can quickly become dangerous. Governance separates helpful AI agents from harmful ones. It’s not a blocker to innovation but rather the guardrails that keep it on the road. What I mean is we should:
Set operational limits: Self-driving cars must know when to hand off control to a human and communicate it clearly.
Create ethical guardrails: Emergency circuit breakers that can halt agent actions in potentially harmful scenarios.
Be transparent: Effective governance also demands thoughtful interaction guidelines, where AI Agents can communicate actively their limitations and confidence levels to users instead of pretending to know everything. This helps people trust AI because they understand its real abilities and limits.

Governance is about ensuring agents stay in their lane and that users know where those lanes begin and end.

4. Purpose-driven and value-aligned
Different AI agents serve different goals but all of them should be built with clear intent and aligned values. Building trustworthy AI agents isn't just about technical excellence but it is about aligning technological capabilities with human values and needs. By prioritizing human-centric design, inclusivity and transparency, we can create AI agents that enhance human potential while respecting fundamental rights and dignities.

The future of AI agents depends not just on what these systems can do, but on how thoughtfully we integrate them into our world. By embedding ethical considerations into every stage of development, we can ensure AI serves as a force for positive transformation.

Vrushali Sawant is data scientist with SAS Data Ethics Practice.