If AI is to meet basic business-use, legal and ethical needs, humans must be able to comprehend how it works. Unlike conventional AI systems, Causal AI is intrinsically explainable and human-compatible. causaLens leverages Causal AI for the enterprise, putting the “cause” in “because”.
Explainable AI (“XAI” for short) is AI humans can understand.
XAI sometimes encompasses important questions about algorithmic bias, fairness and discrimination. Find out how Causal AI addresses algorithmic bias here.
While AI can generate enormous benefits, black box models lead to project failures and place businesses at needless risk.
Businesses need explainable AI to harness the technology’s true potential. Explainability enables a wide range of business stakeholders to audit, trust, de-bias, improve, gain insight from and partner with AI systems.
To illustrate why explainability matters, take as a simple example an AI system used by a bank to vet mortgage applications. There are a wide range of stakeholders that have an interest in this model being explainable.
1. Sam applies for a mortgage
2. Sam’s application is inputted into an AI
3. AI estimates Sam's probability of defaulting
4. Sam’s mortgage application is rejected
Most powerful machine learning models are too complicated for anyone to comprehend or explain, and “overfit” to the past in complex, dynamic environments. Causal AI solves both problems, building models that are highly accurate and inherently explainable.
Post hoc (“after the fact”) approaches attempt to make black box models comprehensible, often by approximating them with a second model.
Intrinsically explainable models are already transparent and don’t require further explanation.
Intrinsically explainable machine learning models include linear models and decision trees.
Causal AI builds intrinsically explainable models that improve on standard models across several critical dimensions.
There’s a tradeoff between prediction accuracy and explainability in conventional machine learning that doesn’t apply to Causal AI. Our technology produces models that are more accurate and that everyone can understand. Mobilize explainable AI in your organization.
Learn more about how and why Causal AI generates a superior kind of explainability.Read the blog