Global AI and Data Science

Join us for The Model Explainability Forum on Tuesday, August 11th at 11 AM PT!

In this panel discussion, we're bringing together experts and researchers to explore the current state of explainability and some of the key emerging ideas shaping the field. The use of machine learning in business, government, and other settings that require users to understand the model's predictions has exploded in recent years. This growth, combined with the increased popularity of opaque ML models like deep learning, has led to the development of a thriving field of model explainability research and practice. 

Each guest will share their unique perspective and contributions to thinking about model explainability in a practical way. 

Visit twimlai.com/explainabilityforum to register!

Panelists include: 

• Kush R. Varshney, IBM

• Solon Barokas, Cornell; Microsoft

• Rayid Ghani, Carnegie Mellon University

• Alessya Labzhinova, Stealth

• Hima Lakkaraju, Harvard

Join us as we explore concepts like stakeholder-driven explainability, adversarial attacks on explainability methods, counterfactual explanations, legal and policy implications, and more.

Join us for The Model Explainability Forum on Tuesday, August 11th at 11 AM PT!

In this panel discussion, we're bringing together experts and researchers to explore the current state of explainability and some of the key emerging ideas shaping the field. The use of machine learning in business, government, and other settings that require users to understand the model's predictions has exploded in recent years. This growth, combined with the increased popularity of opaque ML models like deep learning, has led to the development of a thriving field of model explainability research and practice. 

Each guest will share their unique perspective and contributions to thinking about model explainability in a practical way. 

Visit twimlai.com/explainabilityforum to register!

Panelists include: 

• Kush R. Varshney, IBM

• Solon Barokas, Cornell; Microsoft

• Rayid Ghani, Carnegie Mellon University

• Alessya Labzhinova, Stealth

• Hima Lakkaraju, Harvard

Join us as we explore concepts like stakeholder-driven explainability, adversarial attacks on explainability methods, counterfactual explanations, legal and policy implications, and more.

Join us for The Model Explainability Forum on Tuesday, August 11th at 11 AM PT!

In this panel discussion, we're bringing together experts and researchers to explore the current state of explainability and some of the key emerging ideas shaping the field. The use of machine learning in business, government, and other settings that require users to understand the model's predictions has exploded in recent years. This growth, combined with the increased popularity of opaque ML models like deep learning, has led to the development of a thriving field of model explainability research and practice. 

Each guest will share their unique perspective and contributions to thinking about model explainability in a practical way. 

Visit twimlai.com/explainabilityforum to register!

Panelists include: 

• Kush R. Varshney, IBM

• Solon Barokas, Cornell; Microsoft

• Rayid Ghani, Carnegie Mellon University

• Alessya Labzhinova, Stealth

• Hima Lakkaraju, Harvard

Join us as we explore concepts like stakeholder-driven explainability, adversarial attacks on explainability methods, counterfactual explanations, legal and policy implications, and more.

Join us for The Model Explainability Forum on Tuesday, August 11th at 11 AM PT!

In this panel discussion, we're bringing together experts and researchers to explore the current state of explainability and some of the key emerging ideas shaping the field. The use of machine learning in business, government, and other settings that require users to understand the model's predictions has exploded in recent years. This growth, combined with the increased popularity of opaque ML models like deep learning, has led to the development of a thriving field of model explainability research and practice. 

Each guest will share their unique perspective and contributions to thinking about model explainability in a practical way. 

Visit twimlai.com/explainabilityforum to register!

Panelists include: 

• Kush R. Varshney, IBM

• Solon Barokas, Cornell; Microsoft

• Rayid Ghani, Carnegie Mellon University

• Alessya Labzhinova, Stealth

• Hima Lakkaraju, Harvard

Join us as we explore concepts like stakeholder-driven explainability, adversarial attacks on explainability methods, counterfactual explanations, legal and policy implications, and more.

Join us for The Model Explainability Forum on Tuesday, August 11th at 11 AM PT!

In this panel discussion, we're bringing together experts and researchers to explore the current state of explainability and some of the key emerging ideas shaping the field. The use of machine learning in business, government, and other settings that require users to understand the model's predictions has exploded in recent years. This growth, combined with the increased popularity of opaque ML models like deep learning, has led to the development of a thriving field of model explainability research and practice. 

Each guest will share their unique perspective and contributions to thinking about model explainability in a practical way. 

Visit twimlai.com/explainabilityforum to register!

Panelists include: 

• Kush R. Varshney, IBM

• Solon Barokas, Cornell; Microsoft

• Rayid Ghani, Carnegie Mellon University

• Alessya Labzhinova, Stealth

• Hima Lakkaraju, Harvard

Join us as we explore concepts like stakeholder-driven explainability, adversarial attacks on explainability methods, counterfactual explanations, legal and policy implications, and more.