Explainable Data Science | Denis Rothman


May 14th, 2021

1 hr 20 mins 23 secs

Season 12

Your Host
Special Guest

About this Episode

Denis is an expert in explainable AI (XAI) and today he’s here to talk to us about how to explore machine learning model results, review key influencing variables and variable relationships, detect and handle bias, and ethics issues - among many, many other things.


LinkedIn: https://www.linkedin.com/in/denis-rothman-0b034043/

Website: http://www.eco-ai-horizons.com/


[00:01:32] Guest introduction

[00:02:49] Tell us a little bit about where you grew up and what was it like there?
your map behind you. When I was 15, I was thinking, I want to discover the world.

[00:07:08] How important do you think it is for data scientists and machine learning practitioners focus solely entirely on just math and data science, but to expose themselves to a number of different topics?

[00:09:27] Where are your ideas? Where's the blueprints? What are you creating?

[00:10:30] Why Denis got into artificial intelligence

[00:14:06] Denis talks about his fascination with world religions and how it led to his pursuit of the truth

[00:17:01] Denis has been in the game since 1978, he’s what he’s seen change and remain the same since then

[00:19:28] Where Denis thinks the field is headed in the near future – but not before he tells us why he’s always scribbling math formulas all over his books

[00:23:09] Denis’ problem solving triangle

[00:26:08] What’s the scariest application of AI going to be?

[00:33:40] What the pre-Google era was like, for all you youngins

[00:35:04] The individual must be shaped, he must be made to react, in the way that our culture wants him to

[00:38:57] We start going off on some interesting tangents

[00:40:46] How do we ensure that we are building systems that are ethical?

[00:55:31] How do you view data science machine learning? An art or purely a hard science?

[00:59:12] It is s one hundred years in the future - what do you want to be remembered for?

[01:02:03] The Random Round

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