Episode Description

Given how Artificial Intelligence (AI) is eating our civilization, it's essential to sketch out its first principles and ethical dimensions. We are joined by one of the world's leading AI/ML experts in former founder and co-lead at Google's AI ethical division, and the founder of Ethical AI LLC Margaret Mitchell (@mmitchell_ai) joins our host Waheed Rahman (@iwaheedo) for this insightful episode on the fundamentals of artificial intelligence ethics and global value structures. Margaret has published more than 50 blockbuster papers on vision-language and grounded language generation concentrating on the evolution of AI towards achieving positive goals. She is vastly famous for her work on the instinctive elimination of undesired biases concerning demographic groups from machine learning models. And her work is utilized by some of the biggest companies in the world. Margaret was also the founding member of Microsoft's ethical AI group.

In this episode, we talk about:

- what is exactly AI? 

- what's machine learning vs deep learning?

-the first principles of Ethical AI

-various types of bias and the existence of a 'good' and 'bad' bias as key components to building an AI model 

-how governments and policymakers can evaluate ethical AI models

-development of AI in the western world vs the Emerging markets

-the possible utopian, dystopian and realistic predictions of a society fully adopting AI

Follow our host Waheed Rahman (@iwaheedo) for more updates on tech, civilizational growth, progress studies, and emerging markets.

Here are the timestamps for the episode. On some podcast players, you should be able to click the timestamp for the episode.

(00:00) - Intro

(06:03) - Margaret's background on Artificial Intelligence (AI)

(07:55) - Definition of Artificial Intelligence 

(09:36) - Difference between Machine Learning & Deep Learning

(11:56) - Ethics in AI (Definition & Practices)

(13:43) - The role of the human layer in Ethical AI 

(15:11) - Categories & Examples of biases that occur in AI

(22:29) - Normative vs Descriptive approach for selecting biases in machine learning models

(25:22) - Recent developments in the field of AI

(26:50) - Effective practices of ethical AI in big tech companies

(29:33) - Steps Governments & Policymakers can take to build and regulate AI models

(32:08) - How should tech startups in Emerging Markets develop models in the field of AI ethics?

(35:07) - Future of AI: Utopian vs Dystopian vision

(37:41) - Margaret's recent venture on open source AI 

(40:36) - Outro