# Ethics of Artificial Intelligence Demarcations

## TL;DR

This paper emphasizes the importance of clear distinctions between different AI types, methods, and applications to improve ethical discussions, interdisciplinary collaboration, and informed debate on AI's societal impacts.

## Contribution

It proposes a framework of key demarcations in AI to clarify ethical issues and support better interdisciplinary understanding and research.

## Key findings

- Defines essential AI demarcations for ethical discussions
- Highlights how clear distinctions improve interdisciplinary research
- Supports more informed debates on AI societal impacts

## Abstract

In this paper we present a set of key demarcations, particularly important when discussing ethical and societal issues of current AI research and applications. Properly distinguishing issues and concerns related to Artificial General Intelligence and weak AI, between symbolic and connectionist AI, AI methods, data and applications are prerequisites for an informed debate. Such demarcations would not only facilitate much-needed discussions on ethics on current AI technologies and research. In addition sufficiently establishing such demarcations would also enhance knowledge-sharing and support rigor in interdisciplinary research between technical and social sciences.