"Ethically contentious aspects of artificial intelligence surveillance: a social science perspective"

Area of Science:

• Computer Science
• Ethics
• Sociology

Background:

• Artificial intelligence (AI) presents complex societal and ethical challenges.
• Surveillance is a particularly contentious area within AI ethics.
• Existing research on AI surveillance is vast and multifaceted.

Purpose of the Study:

• To conduct a topic modeling analysis of scientific research on AI surveillance.
• To identify and categorize the major scholarly themes in AI surveillance research.
• To provide a framework for understanding the ethical implications of various AI surveillance forms.

Main Methods:

• Topic modeling analysis of a corpus of scientific research on AI surveillance.
• Identification of significant scholarly topics and their interrelationships.
• Categorization of surveillance dichotomies within AI research.

Main Results:

• Seven significant scholarly topics in AI surveillance research were identified.
• The research highlights the ambiguity between dichotomous forms of surveillance, including public health vs. state, transportation vs. national security, peace vs. military, disease vs. surveillance capitalism, urban vs. citizen ubiquitous, computational vs. fakeness, and data vs. invasive surveillance.
• These findings underscore the complex ethical landscape of AI surveillance.

Conclusions:

• AI surveillance research reveals significant ethical complexities and blurred distinctions between surveillance types.
• The study provides a foundational understanding for navigating the ethical challenges of AI surveillance.
• This research serves as a guideline for policymakers and technology companies to consider the consequences of AI surveillance.