Center for Explanatory Research and Scientific Prediction – CERSP

To Explain the Future

The Challenge

To make decisions, we need to be able to make predictions.

We have no framework to accurately predict under uncertainty.
We need to reshape the theoretical basis of prediction to build models and systems that can predict and explain in a fast-changing world.

Foundational theoretical architecture

Based on causal explanatory models, predictive data science, counterfactual reasoning, and data source quality. It is transformative. It is revolutionary
It is how we design decision-making

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YAI: Artificial intelligence (AI) has become pervasive, and it is embedded in every aspect of our life.

Winds: Women have made significant contributions to the development of machine learning and AI.

Predict to explain: A fundamental divide persists between Social Science, which prioritizes explanation.

We are in poly-crisis. Elections, economic performance, public health, and geopolitical stability have all become.

EU-China: Europe-Asia relations are pivotal in shaping global politics, economics, and security amidst rising geopolitical.

EU-China: Europe-Asia relations are pivotal in shaping global politics, economics, and

cersp

This where you can find updates and news for the Why AI program of CERSP

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Hello World Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s

Hello World Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s

Uncertainty is the ‘New Normal’ “Uncertainty is the new normal” in global economy, IMF chief warns. IMF Managing Director Kristalina

What does P2E do? ‘Predict to Explain’ as a theoretical framework for a decision-making AI. At the theoretical level: YAI