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Traditional machine learning, explainability, drift detection, and bias. Explore the foundations of production ML.
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July 2, 2025
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Segio Ferragut, Karen He, Danny Brock

Proactive Drift and Data Quality Monitoring for Tecton Feature Views with Fiddler

May 8, 2025
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Segio Ferragut, Karen He, Danny Brock

Preventing Model Decay: Tecton + Fiddler for ML Drift Detection

August 9, 2024
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Amit Paka and Karen He

The EU AI Act: A Pathway to AI Governance with Fiddler

March 4, 2024
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Danny Brock and Karen He

AI Observability: The Build vs. Buy Dilemma

February 15, 2024
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Danny Brock and Karen He

Choosing Between Metrics and Inferences for Model Monitoring

February 12, 2024
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Amal Iyer and Barun Halder

The Advantage of Language Model-Based Embeddings

July 21, 2023
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Shohil Kothari

Machine Learning for High Risk Applications

June 6, 2023
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Karen He

91% of ML Models Degrade Over Time

May 9, 2023
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Mary Reagan

Legal Frontiers of AI with Patrick Hall

February 9, 2023
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Murtuza Shergadwala

Human-Centric Design For Fairness And Explainable AI

February 6, 2023
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Bashir Rastegarpanah

Monitoring Natural Language Processing and Computer Vision Models, Part 3

February 1, 2023
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Ankur Taly

Expect the Unexpected: Why Model Robustness Matters

January 5, 2023
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Krishnaram Kenthapadi

How the AI Bill of Rights Impacts You

December 15, 2022
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Amal Iyer

Monitoring Natural Language Processing and Computer Vision Models, Part 2

December 8, 2022
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Shohil Kothari

5 Things to Know About ML Model Performance

November 28, 2022
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Shohil Kothari

Responsible AI by Design

November 15, 2022
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Karen He

Which is More Important: Explainability or Monitoring?

November 3, 2022
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Shohil Kothari

The Real World Impact of Models without Explainable AI

November 1, 2022
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Karen He

3 Benefits of Model Monitoring and Explainable AI Before Deployment

October 3, 2022
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Bashir Rastegarpanah

Monitoring Natural Language Processing and Computer Vision Models, Part 1

September 30, 2022
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Shohil Kothari

ML Model Monitoring Best Practices

September 9, 2022
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Krishnaram Kenthapadi

Why You Need Explainable AI

August 29, 2022
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Shohil Kothari

Top 4 Model Drift Metrics

August 24, 2022
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Shohil Kothari

What is Class Imbalance?

August 8, 2022
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Krishnaram Kenthapadi

With Great ML Comes Great Responsibility

August 5, 2022
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Amit Paka

FairCanary: Rapid Continuous Explainable Fairness

August 1, 2022
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Murtuza Shergadwala

Detecting Intersectional Unfairness in AI: Part 2

June 28, 2022
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Krishnaram Kenthapadi

Steer Clear of These 7 MLOps Myths to Avoid Making an “ML-Oops”

May 25, 2022
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Krishna Gade

AI Regulations Are Here. Are You Ready?

May 2, 2022
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Krishna Gade

Thinking Beyond OSS Tools for Model Monitoring

April 19, 2022
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Shohil Kothari

Implementing Model Performance Management in Practice

April 4, 2022
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Murtuza Shergadwala

Detecting Intersectional Unfairness in AI: Part 1

March 21, 2022
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Shohil Kothari

Business Roundtable’s 10 Core Principles for Responsible AI

March 14, 2022
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Shohil Kothari

MLOps Lifecycle

March 2, 2022
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Shohil Kothari

Explainable AI

February 23, 2022
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Shohil Kothari

Model Performance Management

February 9, 2022
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Amy Holder

Q&A with Bigabid CTO: Monitoring Thousands of Models in Production

February 7, 2022
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Amy Holder

XAI Summit Highlights: Responsible AI in Banking

February 2, 2022
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Krishna Gade

The New 5-Step Approach to Model Governance for the Modern Enterprise

January 31, 2022
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Amy Holder

Drift in Machine Learning: How to Identify Issues Before You Have a Problem

January 18, 2022
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Amy Holder

A Maturity Model for AI Ethics - An XAI Summit Highlight

January 13, 2022
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Krishna Gade

Where Do We Go from Here? The Case for Explainable AI

December 2, 2021
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Krishna Gade

Zillow Offers: A Case for Model Risk Management

October 29, 2021
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Henry Lim

The Key Role of Explainable AI in the Next Decade

July 8, 2021
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Anusha Sethuraman

Responsible AI Podcast with Scott Zoldi — "It's time for AI to grow up"

July 2, 2021
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Amit Paka

EU Mandates Explainability and Monitoring in Proposed GDPR of AI

June 30, 2021
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Anusha Sethuraman

Fiddler X AWS Startup Showcase: Why Model Performance Management Is the Next Big Thing in AI

June 11, 2021
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Henry Lim

How Explainable AI Keeps Decision-Making Algorithms Understandable, Efficient, and Trustworthy - Krishna Gade x Intelligent Automation Radio

June 8, 2021
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Anusha Sethuraman

Responsible AI Podcast with Anjana Susarla – “The Industry Is Still in a Very Nascent Phase”

May 21, 2021
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Anusha Sethuraman

Responsible AI Podcast with Anand Rao – “It’s the Right Thing to Do”

May 11, 2021
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Henry Lim

Building Trust With AI in the Financial Services Industry

May 8, 2021
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Henry Lim

Achieving Responsible AI in Finance With Model Performance Management

April 29, 2021
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Anusha Sethuraman

Responsible AI Podcast Ep.3 – “We’re at an Interesting Inflection Point for Humanity”

April 16, 2021
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Henry Lim

What Should Research and Industry Prioritize to Build the Future of Explainable AI?

April 2, 2021
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Anusha Sethuraman

Responsible AI Podcast Ep.2 - “Only Responsible AI Companies Will Survive”

April 1, 2021
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Amit Paka

Why Data Integrity is Key to ML Monitoring

March 22, 2021
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Krishna Gade

Introducing ML Model Performance Management

March 19, 2021
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Anusha Sethuraman

Responsible AI Podcast Ep.1 - “AI Ethics is a Team Sport”

March 2, 2021
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Mary Reagan

Understanding Bias and Fairness in AI Systems

February 26, 2021
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Anusha Sethuraman

AI in Finance Panel: Accelerating AI Risk Mitigation with XAI and Continuous Monitoring

February 11, 2021
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Anusha Sethuraman

The Past, Present, and Future States of Explainable AI

January 29, 2021
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Amit Paka

Supporting Responsible AI in Financial Services

January 20, 2021
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Anusha Sethuraman

Explainable Monitoring for Successful Impact with AI Deployments

January 9, 2021
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Anusha Sethuraman

How Do We Build Responsible, Ethical AI?

December 15, 2020
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Anusha Sethuraman

Achieving Responsible AI in Finance

November 17, 2020
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Amit Paka

AI in Banking: Rise of the AI Validator

October 29, 2020
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Amit Paka

How to Build a Fair AI System

September 14, 2020
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Amit Paka

The Rise of ML Monitoring

September 10, 2020
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Krishna Gade

TikTok and the Risks of Black Box Algorithms

September 3, 2020
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Erika Renson

AI Explained Video Series: The AI Concepts You Need to Understand

August 20, 2020
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Amit Paka

How to Detect Model Drift in ML Monitoring

June 1, 2020
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Amit Paka

Enterprise Monitoring Landscape - Overview and New Entrants

May 14, 2020
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Marissa Gerchick

Identifying Bias When Sensitive Attribute Data is Unavailable: Geolocation in Mortgage Data

May 1, 2020
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Marissa Gerchick

Identifying Bias When Sensitive Attribute Data is Unavailable: Exploring Data From the Hmda

April 24, 2020
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Ankur Taly

[Video] AI Explained: What are Integrated Gradients?

April 20, 2020
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Anusha Sethuraman

Webinar: Why Monitoring is Critical to Successful AI Deployments

April 13, 2020
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Krishna Gade

Explainable Monitoring: Stop Flying Blind and Monitor Your AI

March 20, 2020
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Ankur Taly

AI Explained Video Series: What are Shapley Values?

March 4, 2020
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Marissa Gerchick

Identifying Bias When Sensitive Attribute Data is Unavailable: Techniques for Inferring Protected Characteristics

February 27, 2020
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Marissa Gerchick

Identifying Bias When Sensitive Attribute Data is Unavailable

February 26, 2020
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Anusha Sethuraman

Explainable AI Podcast: Founder of AIEthicist.org, Merve Hickok, explains the importance of ethical AI and its future

February 24, 2020
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Anusha Sethuraman

The Next Generation of AI: Explainable AI

February 17, 2020
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Anusha Sethuraman

Responsible AI With Model Risk Management

February 10, 2020
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Anusha Sethuraman

CIO Outlook 2020: Building an Explainable AI Strategy for Your Company

January 10, 2020
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Anusha Sethuraman

Explainable AI Podcast: Founder & CTO of Elixr AI, Farhan Shah, discusses AI and the need for transparency

January 7, 2020
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Amit Paka

How to Design to make AI Explainable

December 20, 2019
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Anusha Sethuraman

Where is AI Headed in 2020?

December 6, 2019
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Amit Paka

Fed Opens Up Alternative Data - More Credit, More Algorithms, More Regulation

November 25, 2019
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Krishna Gade

Explainable AI Goes Mainstream But Who Should Be Explaining?

November 14, 2019
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Krishna Gade

The Never-ending Issues Around AI and Bias – Who’s to Blame When AI Goes Wrong?

October 10, 2019
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Anusha Sethuraman

Explainable AI Podcast: Global & Fiddler discuss AI, explainability, and machine learning

September 2, 2019
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Amit Paka

Regulations to Trust AI Are Here. And it's a Good Thing

July 18, 2019
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Kent Twardock

Can Congress Help Keep AI Fair for Consumers?

June 13, 2019
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Krishna Gade

AI Needs a New Developer Stack

April 23, 2019
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Dan Frankowski

A Gentle Introduction to Algorithmic Fairness

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