How to Determine Agency in the World of AI and Machine Learning

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Eddan Katz has previously served as international affairs director at The Electronic Frontier Foundation, where he worked in advocacy initiatives at an international multi-stakeholder decision-making bodies in cyber crime, data privacy, intellectual property and freedom of expression. He was also the first executive director of the information society project at Yale law school, where he taught cyber law and he founded the Access to Knowledge initiative. Eddan has a JD from UC Berkeley, has a BA in philosophy from Yale and today he's working at the World Economic Forum on artificial intelligence and machine learning.  

Episode Links:  

Eddan Katz’s LinkedIn: https://www.linkedin.com/in/eddankatz/ 

Eddan Katz’s Twitter:  https://twitter.com/eddankatz 

Eddan Katz’s Website: https://www.weforum.org/centre-for-the-fourth-industrial-revolution/ 

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Outline: 

Here’s the timestamps for the episode: 

(00:00) – Introduction

(02:52) –The decentralized nature of our communications makes things connected together in a way that they haven't been before. And that complexity between the physical environment and the digital environment means that more and more of our daily lives are impacted by the structure and rules around how digital context and the digital network environment is governed

(03:56) – The international aspects reflect the fact that our communications and our trade and our products and services don't obey the same physical borders as we're used to in other contexts

(05:01) – There is a possibility of establishing some privacy norms in the US. US law is oriented towards strong privacy protection in different arenas, data privacy as a whole

(07:30) – The Generation AI project is run by the World Economic Forum and the center for the Fourth Industrial Revolution, in partnership with UNICEF in regards to policy development, with developmental education and science and researchers who are working on the latest research in regards to how children can actually benefit from algorithmic and precision education

(10:44) – Facial recognition project as a center for the fourth investment solution. Authentication and after the fact crime-fighting. Transparency as to how the processes are being designed and where the data goes

(14:34) – People need to understand what AI is and what is different about aggregated data and artificial intelligence, machine learning and deep learning

(16:28) – Understand the implications of false positives and other ways in which there are errors in information application before it gets deployed publicly 

(18:58) – New legislations can create havens where certain types of activity can take place. It’s important to think globally and think about harmonizing norms on a greater level

(20:32) – We're developing guidelines for government procurement officials for the ethical and efficient purchasing of AI systems and algorithms

(23:55) – Diversity is a key principle that makes up ethical design of AI systems an important point to carry.

(25:16) – It's crucial for us to maintain the space where responsibility can still be assigned when it is divorced from human judgment and interaction becomes a unique problem

(27:53) – AI in military weaponry, when divorced from the actual intent and the context of conflict, is particularly dangerous. 

(32:42) – There is an opportunity to move towards new and innovative uses of our emerging technology without having to consume the structures of what's already in place

(33:59) – Teaching AI ethics and the responsible use of AI and social and economic considerations, and integrate that into engineering and computer science graduate programs

(37:11) – We had the different stages of technology development and the one that we're currently in integrates the physical, the biological, the computational in this way, where the convergence is creating all sorts of exciting opportunities, but also social and economic challenges