Roman Yampolskiy on the Uncontrollability, Incomprehensibility, and Unexplainability of AI Future of Life Institute Podcast

    • Technology

Roman Yampolskiy, Professor of Computer Science at the University of Louisville, joins us to discuss whether we can control, comprehend, and explain AI systems, and how this constrains the project of AI safety.

 Topics discussed in this episode include:

-Roman’s results on the unexplainability, incomprehensibility, and uncontrollability of AI
-The relationship between AI safety, control, and alignment
-Virtual worlds as a proposal for solving multi-multi alignment
-AI security

You can find the page for this podcast here: https://futureoflife.org/2021/03/19/roman-yampolskiy-on-the-uncontrollability-incomprehensibility-and-unexplainability-of-ai/

You can find FLI's three new policy focused job postings here: https://futureoflife.org/job-postings/

Have any feedback about the podcast? You can share your thoughts here: www.surveymonkey.com/r/DRBFZCT

Timestamps: 

0:00 Intro 
2:35 Roman’s primary research interests 
4:09 How theoretical proofs help AI safety research 
6:23 How impossibility results constrain computer science systems
10:18 The inability to tell if arbitrary code is friendly or unfriendly 
12:06 Impossibility results clarify what we can do 
14:19 Roman’s results on unexplainability and incomprehensibility 
22:34 Focusing on comprehensibility 
26:17 Roman’s results on uncontrollability 
28:33 Alignment as a subset of safety and control 
30:48 The relationship between unexplainability, incomprehensibility, and uncontrollability with each other and with AI alignment 
33:40 What does it mean to solve AI safety? 
34:19 What do the impossibility results really mean? 
37:07 Virtual worlds and AI alignment 
49:55 AI security and malevolent agents 
53:00 Air gapping, boxing, and other security methods 
58:43 Some examples of historical failures of AI systems and what we can learn from them 
1:01:20 Clarifying impossibility results
1:06 55 Examples of systems failing and what these demonstrate about AI 
1:08:20 Are oracles a valid approach to AI safety? 
1:10:30 Roman’s final thoughts

This podcast is possible because of the support of listeners like you. If you found this conversation to be meaningful or valuable, consider supporting it directly by donating at futureoflife.org/donate. Contributions like yours make these conversations possible.

Roman Yampolskiy, Professor of Computer Science at the University of Louisville, joins us to discuss whether we can control, comprehend, and explain AI systems, and how this constrains the project of AI safety.

 Topics discussed in this episode include:

-Roman’s results on the unexplainability, incomprehensibility, and uncontrollability of AI
-The relationship between AI safety, control, and alignment
-Virtual worlds as a proposal for solving multi-multi alignment
-AI security

You can find the page for this podcast here: https://futureoflife.org/2021/03/19/roman-yampolskiy-on-the-uncontrollability-incomprehensibility-and-unexplainability-of-ai/

You can find FLI's three new policy focused job postings here: https://futureoflife.org/job-postings/

Have any feedback about the podcast? You can share your thoughts here: www.surveymonkey.com/r/DRBFZCT

Timestamps: 

0:00 Intro 
2:35 Roman’s primary research interests 
4:09 How theoretical proofs help AI safety research 
6:23 How impossibility results constrain computer science systems
10:18 The inability to tell if arbitrary code is friendly or unfriendly 
12:06 Impossibility results clarify what we can do 
14:19 Roman’s results on unexplainability and incomprehensibility 
22:34 Focusing on comprehensibility 
26:17 Roman’s results on uncontrollability 
28:33 Alignment as a subset of safety and control 
30:48 The relationship between unexplainability, incomprehensibility, and uncontrollability with each other and with AI alignment 
33:40 What does it mean to solve AI safety? 
34:19 What do the impossibility results really mean? 
37:07 Virtual worlds and AI alignment 
49:55 AI security and malevolent agents 
53:00 Air gapping, boxing, and other security methods 
58:43 Some examples of historical failures of AI systems and what we can learn from them 
1:01:20 Clarifying impossibility results
1:06 55 Examples of systems failing and what these demonstrate about AI 
1:08:20 Are oracles a valid approach to AI safety? 
1:10:30 Roman’s final thoughts

This podcast is possible because of the support of listeners like you. If you found this conversation to be meaningful or valuable, consider supporting it directly by donating at futureoflife.org/donate. Contributions like yours make these conversations possible.

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