Grade Level at Time of Presentation

Senior

Major

Computer Information Technology - Cybersecurity

Minor

Computer Science and Information Security

2nd Grade Level at Time of Presentation

Senior

2nd Student Major

Computer Information Technology

Institution

Northern Kentucky University

KY House District #

4th

KY Senate District #

11th

Department

Department of Computer Science

Abstract

The last couple of years have seen a strong movement supporting the need of having intelligent consumer products align with specific design guidelines for trustworthy artificial intelligence (AI). This global movement has led to multiple institutional recommendations for ethically aligned trustworthy design of the AI driven technologies, like consumer robots and autonomous vehicles. There has been prior research towards finding security and privacy related vulnerabilities within various types of social robots. However, none of these previous works has studied the implications of these vulnerabilities in terms of the robot design aligning with trustworthy AI. In an attempt to address this gap in existing literature, we have performed a unique research study with two social robots - Zümi and Cozmo. In this study, we have explored flaws within the robot’s system, and have analyzed these flaws to assess the overall alignment of the robot system design with the IEEE global standards on the design of ethically aligned trustworthy autonomous intelligent systems (IEEE A/IS Standards). Our initial research shows that the vulnerabilities and design weaknesses, which we found in these robots, can lead to hacking, injection attacks, and other malfunctions that might affect the technology users negatively. We test the intelligent functionalities in these robots to find faults and conduct a preliminary examination of how these flaws can potentially result in non-adherence with the IEEE A/IS principles. Through this novel study, we demonstrate our approach towards determining the alignment of social robots with benchmarks for trustworthy AI, thereby creating a case for prospective design improvements to address unique risks leading to issues with robot ethics and trust.

COinS
 

Assessing the Alignment of Social Robots with Trustworthy AI Design Guidelines: A Preliminary Research Study

The last couple of years have seen a strong movement supporting the need of having intelligent consumer products align with specific design guidelines for trustworthy artificial intelligence (AI). This global movement has led to multiple institutional recommendations for ethically aligned trustworthy design of the AI driven technologies, like consumer robots and autonomous vehicles. There has been prior research towards finding security and privacy related vulnerabilities within various types of social robots. However, none of these previous works has studied the implications of these vulnerabilities in terms of the robot design aligning with trustworthy AI. In an attempt to address this gap in existing literature, we have performed a unique research study with two social robots - Zümi and Cozmo. In this study, we have explored flaws within the robot’s system, and have analyzed these flaws to assess the overall alignment of the robot system design with the IEEE global standards on the design of ethically aligned trustworthy autonomous intelligent systems (IEEE A/IS Standards). Our initial research shows that the vulnerabilities and design weaknesses, which we found in these robots, can lead to hacking, injection attacks, and other malfunctions that might affect the technology users negatively. We test the intelligent functionalities in these robots to find faults and conduct a preliminary examination of how these flaws can potentially result in non-adherence with the IEEE A/IS principles. Through this novel study, we demonstrate our approach towards determining the alignment of social robots with benchmarks for trustworthy AI, thereby creating a case for prospective design improvements to address unique risks leading to issues with robot ethics and trust.

 

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