As artificial intelligence continues to reshape industries, brands face the challenge of instilling trust in their AI products and services.
Consumers are seeking reassurance in the AI they engage with. They want transparency on why and how it’s used.
This trust-building process is crucial, and brands must seek to align their AI integration with their customer’s values and expectations.
1. Explainability = Trust
Transparency is key when it comes to AI.
Users should have a clear understanding of how the technology works, what data it used, and how decisions are made.
PathAI, a healthcare technology company that leverages AI to improve the accuracy and efficiency of diagnosing diseases, places a strong emphasis on explainability.
By providing detailed visualisations and insights that help clinicians understand how the AI arrived at its conclusions, it has become a trusted tool for clinicians to validate and refine diagnoses.
2. Design for ease of use
A positive user experience is crucial for establishing trust in AI functions.
Brands must prioritise designing AI interfaces that are user-friendly, intuitive, and provide clear feedback.
Google’s Smart Compose feature in Gmail is an excellent example of an AI-powered function that enhances the user experience. It uses AI to suggest complete sentences while composing emails.
It provides real-time suggestions that users can accept, enhancing productivity and creating a sense of reliability and trust in the AI function.
“AI can be a game-changer for the productivity and efficiency of your product and service, but only if your customers get fully behind it, so instilling trust is vital.”
— Chris Sherrick, Managing Partner, Athlon
3. Show how you are protecting user data.
Ensuring the security of AI functions is essential for building trust in your product or service.
Brands must prioritise data protection and embed robust security measures into the user experience.
Payment processing platform Stripe leverages AI to enhance fraud detection and prevention.
4. Demonstrate testing for bias
Trust in AI functions is strengthened when brands visibly test and validate their technology.
This process includes comprehensive testing for bias, accuracy, and other potential issues.
For example, Google has developed specific tools and frameworks, such as the Google Cloud Fairness Indicators, to measure and detect potential biases in their models.
Fitbit have also implemented robust testing to ensure accuracy and reliability of their AI-powered fitness tracking algorithms. They employ a combination of lab testing and field studies to assess the accuracy of their devices’ measurements.
5. Hybrid human approach
Brands can further instil trust in their AI functions by incorporating human oversight. Human experts play a critical role in reviewing and interpreting the AI functions and features to ensure accuracy, fairness, and ethical considerations. Facebook’s content moderation system demonstrates the importance of human oversight. Facebook combines AI algorithms with human moderators to review and moderate content on its platform. This hybrid approach ensures accurate and fair content decisions, instilling trust among users.