Explainable AI in retail with Play Vectors

Blog post

As AI becomes more prevalent in retail, the need for explainable AI (XAI) is growing. XAI aims to make AI systems more transparent and understandable, fostering trust in the decisions and recommendations among both retailers and shoppers.

The challenge of XAI in retail

AI is inherently biased, which is why explainability and control are crucial to mitigating these biases. Retailers need highly transparent solutions that support their product search and discovery experiences.

With the rise of generative AI, people have become more aware of how developers' biases can impact AI judgments. This heightened awareness makes it even more critical for retailers to prioritize XAI to support their search data and insights to make informed business decisions.

The benefits of XAI

For retailers, explainable AI leads to better decision-making and understanding. It enables them to audit their AI-based search systems, identify biases, and make necessary improvements, resulting in more trustworthy and effective AI-powered experiences.

For shoppers, XAI enhances trust and improves the shopping experience. When shoppers understand why they see certain recommendations or search results, they're more likely to engage with them, driving increased conversions and loyalty.

Empathy Platform's approach to XAI

At Empathy.co, we believe in making AI transparent and understandable. Empathy Platform AI search and discovery solution is designed with these principles in mind, offering:

  • Headless architecture with API-first backend microservices that are fully decoupled from the composable frontend.
  • Intuitive controls and clear relevance insights through the Empathy Platform Playboard.
  • Scalable, reliable, and cloud-agnostic infrastructure

Empathy Platform’s AI semantic search uses approximate nearest neighbor (AAN) algorithms to create associations between search terms and product data as this approach helps understand shopper intent and semantic similarities, enhancing traditional keyword search.

Built on a cloud-native stack, the semantic models used to calculate these similarities are trained within each customer’s specific domain, ensuring privacy and customization.

Visualizing semantic models with Play Vectors

At Empathy.co, we envision XAI as an integral part of the future of retail. Our Play Vectors demo showcases this perception by providing a visual explanation of the similarities between queries and product-related information through vector models. These models represent vector points in a high-dimensional space, allowing you to locate specific queries and explore related terms visually.

Vector search & explainability

Play Vector demonstrates how the explainability gap can be bridged by offering visual insights into how semantic models work. It illustrates the potential for retailers to clearly understand shoppers' intent, enabling them to make informed decisions and tailor the search and discovery experience to their brand and business needs.

So, by prioritizing XAI, Empathy.co helps retailers create AI-powered search and discovery experiences that are trustworthy, transparent, and personalized. This approach not only enhances the shopping experience for shoppers but also empowers retailers to make data-driven decisions, fostering trust and loyalty in an increasingly AI-driven market.