Explainability of AI starts with design, not communication
Explainability of AI and digital systems starts with design, not afterwards. Transparency requires that decisions are traceable, contextual, and auditable from the start. This is the only way that citizens, clients and supervisors can have real confidence in the results.

Why transparency is not possible afterwards
Explainability starts with design, not communication
Transparency has become an integral part of conversations about AI and algorithms. Especially when systems are used in decision-making, the need for explanation grows. In practice, this question often only arises when a decision is contested.
Many AI systems function technically correctly, but are barely able to explain their decisions. They provide an outcome, without insight into the steps that preceded them. This is not a shortage of communication, but a result of how these systems were designed.
With many digital AI applications the focus is on efficiency. Data is linked, processes are accelerated and models are applied. The question of how an individual decision can be explained later often comes only afterwards. At that time, essential information is missing. What data was used. How these were weighted. And where human assessment has taken place.
Explainability requires systems that can reconstruct decisions. On a case-by-case basis. With context and traceability. This is only possible if logging and decision structure are included in the design from the start.
When transparency is only added afterwards, it is limited to general explanation. This is insufficient for citizens, clients and supervisors. In regulated environments, explanation is not an extra provision, but a basic requirement.
At Xuntos, we therefore see transparency as a property of the system itself. Architecture determines whether an explanation is possible. Not the interface or the text that will be written around it later.
If you take transparency seriously, you start with design choices.
Getting started with responsible AI
We first start with an analysis for a thorough plan of action. In doing so, we analyse data, processes and risks and translate them into a concrete architectural sketch.
Learn more about our approach at

Heb je vragen? Of wil je samen sparren?
We denken graag met je mee hoe jouw organisatie digitaal kan versnellen. Of het nu gaat om een UX, technische uitdaging of AI oplossingen. Stuur een berichtje en we nemen zsm contact met je op.
Verder lezen
Nieuwsgierig? Lees onze andere inzichten over webontwikkeling, AI, toegankelijkheid en digitale strategie


.jpg)





















