When using AI models in environments where compliance standards are important, Mosaic Factor can help your company be on top of data governance by applying trustworthy AI solutions.
This means ensuring that the AI models we use are explainable and ethical so that we can make sure they are robust and reliable, but also safe, secure, transparent, fair, inclusive, and produce accountable results.
MOSAIC XAI DASHBOARDS: NON-TECHNICAL VISUALISATIONS FOR DECISION MAKERS
We believe that AI models need to be explainable (or XAI -explainable AI-) to any company decision makers, not only to data scientist or technical teams.
Mosaic Factor’s XAI dashboards are visualisations we produce to help different stakeholders understand and comprehend how the AI models work so that appropriate decisions can be taken, especially for decision makers who are not necessarily data or tech profiles.
TRANSLATE AI VISUALISATIONS TO DASHBOARDS
THAT FACILITATE BUSINESS DECISIONS
TRUSTWORTHY AI MODELS WORKFLOW
At Mosaic Factor, we do that by focusing on “explainable-by-design” and “fairness-by-design” models, instead of creating AI models that become black boxes and hence cannot be fully trusted or accountable:
- First, we create an Explainable AI pipeline (XAI Pipeline) for AI models. This includes:
- Pre-model, in-model and post-model phases.
- Or just post-model in case we need to explain a pre-existing model.
- The we run a Data Bias & Fairness Tracker for the XAI Pipeline.
- We work with synthetic data for collected data that fails the spectrum test and for privacy-related concerns (sensitive data) when needed
- We run a model performance evaluation (mainly on reliability, trustworthiness, fairness, and robustness) via XAI-driven monitoring and auditing techniques.
- This way, we unlock the reasoning behind the model’s decision and outputs considering the whole modelling process.
- Finally, we generate a Mosaic XAI dashboard (a XAI-driven visualisation) adapted to specific stakeholders so that we can facilitate decision-making and define the necessary tools for homologation processes, where needed.
