An ethical study of generative AI from the Actor-Network Theory perspective

TL;DR

This paper applies Actor-Network Theory to analyze ethical issues in generative AI, specifically ChatGPT, identifying key actors and processes to understand moral challenges and inform governance strategies.

Contribution

It introduces a novel Actor-Network Theory framework to analyze ethical concerns in generative AI, highlighting the roles of diverse actors and translation processes.

Findings

Identified nine key actors involved in ChatGPT's ethical landscape

Analyzed translation processes leading to moral issues

Provided insights for AI governance based on actor interactions

Abstract

The widespread use of Generative Artificial Intelligence in the innovation and generation of communication content is mainly due to its exceptional creative ability, operational efficiency, and compatibility with diverse industries. Nevertheless, this has also sparked ethical problems, such as unauthorized access to data, biased decision-making by algorithms, and criminal use of generated content. In order to tackle the security vulnerabilities linked to Generative Artificial Intelligence, we analyze ChatGPT as a case study within the framework of Actor-Network Theory. We have discovered a total of nine actors, including both human and non-human creatures. We examine the actors and processes of translation involved in the ethical issues related to ChatGPT and analyze the key players involved in the emergence of moral issues. The objective is to explore the origins of the ethical issues that arise with Generative Artificial Intelligence and provide a particular perspective on the governance of Generative Artificial Intelligence.