Resource Hub
Gain insights into Causal AI from blogs, white papers, case studies, webinars, and more.
Enterprise decision making needs more than chatbots
Following the hype around large language models (LLMs), tools and applications, the question remains, how many enterprise problems today can actually be solved by ChatGPT?
Read moreConfounders: machine learning’s blindspot
9 out of 10 machine learning projects never make it beyond an experimental phase and into production. One key factor is that machine learning algorithms can’t identify “confounders”.
Read moreExplainable AI (XAI) doesn’t explain enough
Current XAI approaches only provide post-hoc explainability. Causal AI generates superior ante-hoc (before the event) explainability.
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Causal AI papers
Go in-depth into applied use-cases and Causal AI applications for enterprise decision-making.
View allFeatured research
Our Causal AI research papers, AI news and events. causaLens covers the latest insights into Causal AI machine learning and causal inference. Our diverse team of researchers have published papers at NeurIPS, ICML, UAI, Nature Neuroscience, and other top outlets. Find a sample of our publicly accessible academic work below.
A Causal Analysis of Harm
Defining harm is essential for dealing with the many legal and regulatory issues around the growing integration of autonomous systems in society. Consider, for example, the question of harm in accidents involving self-driving cars.
Read moreDomain Knowledge in A*-Based Causal Discovery
Causal discovery has become a vital tool for scientists and practitioners wanting to discover causal relationships from observational data. While most previous approaches to causal discovery have implicitly assumed
Read moreEquality of Effort via Algorithmic Recourse
AI systems are increasingly used in many socially significant applications, such as loan approval, hiring decisions, legal processes, and healthcare, sometimes encoding existing human
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Featured Papers
Explore Causal AI applications
Next Generation A/B Testing powered by Causal AI
Learn about the next generation of A/B testing that is powered by Causal AI. Delivering virtual experiments.
Read moreAI Fairness and Causality
Chances are your organization doesn’t trust AI systems to support business-critical decisions. Why not? In a nutshell, today’s stock of machine learning systems are not trustworthy.
Read moreExplainable AI (XAI) doesn’t explain enough
Current XAI approaches only provide post-hoc explainability. Causal AI generates superior ante-hoc (before the event) explainability.
Read more