As autonomous systems become more prevalent in society, it becomes increasingly important that they robustly behave as intended. The development of autonomous vehicles, autonomous trading systems, autonomous weapons, etc. has therefore stoked interest in high-assurance systems where strong robustness guarantees can be made; Weld and Etzioni have argued that “society will reject autonomous agents unless we have some credible means of making them safe”. Different ways in which an AI system may fail to perform as desired corresponding to different areas of robustness research. Discuss the following focus areas of AI research. Verification: how to prove that a system satisfies certain desired formal properties. (“Did I build the system right?”) Validity: how to ensure that a system that meets its formal requirements does not have unwanted behaviors and consequences. (“Did I build the right system?”) Security: how to prevent intentional manipulation by unauthorized parties. Control: how to enable meaningful human control over an AI system after it begins to operate. (“OK, I built the system wrong, can I fix it?”),

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Principles of Artificial Intelligence

As autonomous systems become more prevalent in society, it becomes increasingly important that they robustly behave as intended. The development of autonomous vehicles, autonomous trading systems, autonomous weapons, etc. has therefore stoked interest in high-assurance systems where strong robustness guarantees can be made; Weld and Etzioni have argued that “society will reject autonomous agents unless we have some credible means of making them safe”. Different ways in which an AI system may fail to perform as desired corresponding to different areas of robustness research. Discuss the following focus areas of AI research.
1. Verification: how to prove that a system satisfies certain desired formal properties. (“Did I build the system right?”)
2. Validity: how to ensure that a system that meets its formal requirements does not have unwanted behaviors and consequences. (“Did I build the right system?”)
3. Security: how to prevent intentional manipulation by unauthorized parties.
4. Control: how to enable meaningful human control over an AI system after it begins to operate. (“OK, I built the system wrong, can I fix it?”),

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