Examining media coverage of ethical dimensions of advanced algorithmic technology

Area of Science:

• Ethics of Artificial Intelligence
• Machine Learning Ethics
• Data Science Ethics

Background:

• Growing integration of AI, ML, and data science into daily life necessitates ethical considerations.
• Media plays a crucial role in shaping public perception and acceptance of emerging technologies.

Purpose of the Study:

• To systematically analyze media discourse on ethics in AI, ML, and data science from 2015 to 2020.
• To understand how media frames ethical concerns and future scenarios related to these technologies.

Main Methods:

• Systematic analysis of media discourse.
• Content analysis of media coverage focusing on ethical dimensions.

Main Results:

• Media coverage predominantly focused on the industry sector.
• Key ethical challenges discussed include algorithmic bias, social justice, data privacy, and socioeconomic effects.
• Media portrayal maintained a balanced perspective, presenting both positive and negative outcomes with realistic future scenarios.

Conclusions:

• The study provides a holistic analysis of media framing of AI, data science, and ML ethics.
• Highlights overlooked dimensions such as accountability strategies and the link between applications and consequences.