Factoring ethics in management algorithms for municipal information-analytical systems

Area of Science:

• Computer Science
• Ethics
• Social Science

Background:

• Existing artificial intelligence (AI) ethical frameworks lack specificity for practical applications.
• General AI ethics principles are insufficient for addressing nuanced use cases in digital governance.
• There is a need to bridge the gap between theoretical AI ethics and applied management techniques.

Purpose of the Study:

• To examine the ethical implications of information analytical systems in social media.
• To propose a management approach for filtering social media content and mitigating negative information impacts.
• To connect digital governance challenges with applied management techniques for AI ethics.

Main Methods:

• Analysis of existing AI ethics conventions, principles, and guidelines.
• Deductive reasoning to link general digital governance challenges to specific management techniques.
• Examination of information analytical systems for social media content filtering.

Main Results:

• Identified vagueness in current AI ethical frameworks when applied to specific use cases.
• Demonstrated the utility of a management approach for filtering social media content.
• Highlighted the ethical dimensions of AI through applied management techniques.

Conclusions:

• A management approach can effectively address ethical challenges in AI applications like social media content filtering.
• Bridging general AI ethics with applied management techniques is crucial for responsible AI deployment.
• This research provides a framework for managing the ethical implications of AI in public administration and society.