Causal Conceptions of Fairness and their Consequences with Sharad Goel - #586

Causal Conceptions of Fairness and their Consequences with Sharad Goel - #586

Today we close out our ICML 2022 coverage joined by Sharad Goel, a professor of public policy at Harvard University. In our conversation with Sharad, we discuss his Outstanding Paper award winner Causal Conceptions of Fairness and their Consequences, which seeks to understand what it means to apply causality to the idea of fairness in ML. We explore the two broad classes of intent that have been conceptualized under the subfield of causal fairness and how they differ, the distinct ways causality is treated in economic and statistical contexts vs a computer science and algorithmic context, and why policies are created in the context of causal definitions are suboptimal broadly. The complete show notes for this episode can be found at twimlai.com/go/586

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Selling AI to the Enterprise with Kathryn Hume - TWiML Talk #20

Selling AI to the Enterprise with Kathryn Hume - TWiML Talk #20

This week's guest is Kathryn Hume. Kathryn is the President of Fast Forward Labs, which is an independent machine intelligence research company that helps organizations accelerate their data science and machine intelligence capabilities. If Fast Forward Labs sounds familiar, that's because we had their founder, Hilary Mason on a few months ago. We’ll link to that in the show notes. My discussion with Kathryn focused on AI adoption within the enterprise. She shared several really interesting examples of the kinds of things she’s seeing enterprises do with machine learning and AI, and we discussed a few of the various challenges enterprises face and some of the lessons her company has learned in helping them. I really enjoyed our conversation and I know you will too! You can find the notes for todays show here: https://twimlai.com/talk/20

21 Apr 201723min

From Particle Physics to Audio AI with Scott Stephenson - TWiML Talk #19

From Particle Physics to Audio AI with Scott Stephenson - TWiML Talk #19

This week my guest is Scott Stephenson. Scott is co-Founder & CEO of Deepgram, which has developed an AI-based platform for indexing and searching audio and video. Scott and I cover a ton of interesting topics including applying machine learning techniques to particle physics, his time in a lab 2 miles below the surface of the earth, applying neural networks to audio, and the Deep Learning Framework Kur that his company open-sourced. The show notes can be found at twimlai.com/talk/19.

14 Apr 201756min

(5/5) AlphaVertex - Creating a Worldwide Financial Knowledge Graph - TWiML Talk #18

(5/5) AlphaVertex - Creating a Worldwide Financial Knowledge Graph - TWiML Talk #18

This week I'm on location at NYU/ffVC AI NexusLab startup accelerator, speaking with founders from the 5 companies in the program's inaugural batch. This interview is with AlphaVertex, a FinTech startup creating a worldwide financial knowledge graph to help investors predict stock prices. The notes for this series can be found at twimlai.com/nexuslab. Thanks to Future Labs at NYU Tandon and ffVenture Capital for sponsoring the series!

7 Apr 201726min

(4/5) Behold.ai - Increasing Efficiency of Healthcare Insurance Billing with NLP - TWiML Talk #18

(4/5) Behold.ai - Increasing Efficiency of Healthcare Insurance Billing with NLP - TWiML Talk #18

This week I'm on location at NYU/ffVC AI NexusLab startup accelerator, speaking with founders from the 5 companies in the program's inaugural batch. This interview is with Behold.ai, which uses computer vision and natural language processing techniques to bring efficiencies to the world of healthcare insurance billing. The notes for this series can be found at twimlai.com/nexuslab. Thanks to Future Labs at NYU Tandon and ffVenture Capital for sponsoring the series!

7 Apr 201716min

(3/5) Cambrian Intelligence - Using AI to Simplify the Programming of Robots - TWiML Talk #18

(3/5) Cambrian Intelligence - Using AI to Simplify the Programming of Robots - TWiML Talk #18

This week I'm on location at NYU/ffVC AI NexusLab startup accelerator, speaking with founders from the 5 companies in the program's inaugural batch. This interview is with Cambrian Intelligence, a company using AI to simplify the programming of industrial robots for the automotive industry. The notes for this series can be found at twimlai.com/nexuslab. Thanks to Future Labs at NYU Tandon and ffVenture Capital for sponsoring the series!

7 Apr 201723min

(2/5) Klustera - Location-Based Intelligence for Smarter Marketing - TWiML Talk #18

(2/5) Klustera - Location-Based Intelligence for Smarter Marketing - TWiML Talk #18

This week I'm on location at NYU/ffVC AI NexusLab startup accelerator, speaking with founders from the 5 companies in the program's inaugural batch. This interview is with Klustera, a company applying location-based intelligence and machine learning to help brands execute smarter marketing campaigns. The notes for this series can be found at twimlai.com/nexuslab. Thanks to Future Labs at NYU Tandon and ffVenture Capital for sponsoring the series!

7 Apr 201722min

(1/5) HelloVera - AI-Powered Customer Support  - TWiML Talk #18

(1/5) HelloVera - AI-Powered Customer Support - TWiML Talk #18

This week I'm on location at NYU/ffVC AI NexusLab startup accelerator, speaking with founders from the 5 companies in the program's inaugural batch. This interview is with HelloVera, a company applying artificial intelligence to the challenge of automating customer support experiences. The notes for this series can be found at https://twimlai.com/nexuslab. Thanks to Future Labs at NYU Tandon and ffVenture Capital for sponsoring the series!

7 Apr 201725min

Interactive Machine Learning Systems with Alekh Agarwal - TWiML Talk #17

Interactive Machine Learning Systems with Alekh Agarwal - TWiML Talk #17

This week my guest is Alekh Agarwal. Alekh is a researcher with Microsoft Research whose research is focused on Interactive Machine Learning. In our discussion, Alekh and I discuss various aspects of this exciting area of research such as active learning, reinforcement learning, contextual bandits and more.

31 Mars 201730min

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