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

We recently chatted with Merve Hickok, Founder of AIEthicist.org and Lighthouse Career Consulting. Take a listen to the podcast below or read the transcript. (Transcript lightly edited for clarity.) Listen to all the Explainable AI Podcasts here Fiddler: Welcome to the Fiddler Explainable AI podcast. My name is Anusha Sethuraman. Today I have with me Merve Hickok, … Continue reading “Explainable AI Podcast: Founder of AIEthicist.org, Merve Hickok, explains the importance of ethical AI and its future”

Responsible AI With Model Risk Management

The desire among financial institutions to better mitigate risk gained renewed prominence as a result of the financial crisis of 2008. Subsequent regulatory and governance requirements fostered interest in risk modeling and sophisticated forecasting based on artificial intelligence (AI) to improve outcomes. It now seems common to have AI-driven models supporting decision making related to … Continue reading “Responsible AI With Model Risk Management”

CIO outlook 2020: Building an explainable AI strategy for your company

Building an AI strategy needs to include explainability for complete visibility into machine-generated decisions. Explainable AI ensures there’s a human present in the loop of the AI process, where the machine provides transparent and reliable explanations, and the human can correct the machine in cases where its decisions are wrong. The sooner such an AI … Continue reading “CIO outlook 2020: Building an explainable AI strategy for your company”

How to Design to make AI Explainable

Explainable AI, a topic of research until recently, is now mainstream. Recent research has enabled insights into the behavior of inherently black box AI models that can address its otherwise significant business risks related to bias, compliance and opaque outcomes. However, many platforms and solutions provide these explanations either with flat numbers via API or … Continue reading “How to Design to make AI Explainable”

Explainable AI goes mainstream. But who should be explaining?

Bias in AI is an issue that has really come to the forefront in recent months — our recent blog post discussed the Apple Card/Goldman Sachs alleged bias issue. And this isn’t an isolated instance: Racial bias in healthcare algorithms and bias in AI for judicial decisions are just a few more examples of rampant … Continue reading “Explainable AI goes mainstream. But who should be explaining?”