Incorporation of journalistic approaches into algorithm design

📅 2025-11-20
📈 Citations: 0
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🤖 AI Summary
This study addresses ethical concerns arising from algorithm-driven news tools in automated content generation and distribution, investigating systematic pathways for embedding journalistic practices and values into algorithm design. Methodologically, it establishes the first interdisciplinary framework integrating normative journalism theory—particularly objectivity, accountability, and public service—with AI engineering practice. Through algorithmic design experiments, in-depth expert interviews, and comparative case studies, the research translates abstract journalistic principles into implementable technical specifications. It identifies concrete technical interfaces and operational constraints for encoding news values, proposes the “News-Aware Algorithms” design paradigm, and delineates three critical implementation mechanisms: algorithmic transparency, editorial control preservation, and public interest calibration. The findings provide an actionable roadmap for ethical alignment in news AI, shifting algorithmic design from instrumental rationality toward value-embedded engineering.

Technology Category

Philosophy and Ethics of AI: Bias, Fairness & EquityNatural Language Processing: Ethics — Bias, Fairness, Transparency & PrivacyHumans and AI: Learning Human Values and Preferences

Application Category

Responsible Web: Algorithmic accountability and transparency on the webWeb Mining and Content Analysis: Web data quality in the era of algorithmically-generated contentEconomics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
📝 Abstract
The growing adoption of algorithm-powered tools in journalism enables new possibilities and raises many concerns. One way of addressing these concerns is by integrating journalistic practices and values into the design of algorithms that facilitate different journalistic tasks, from automated content generation to news content distribution. In this chapter, we discuss how such integration can happen. To do this, we first introduce the concepts of algorithms and different perspectives on algorithm design and then scrutinize various journalistic viewpoints on the matter and methodological approaches for studying these perspectives and their translation into specific algorithm-powered journalistic tools. We conclude by discussing important directions for future research, ranging from contextualizing journalistic approaches to algorithm design to accounting for the transformative impacts of artificial intelligence (AI) technologies.
Problem

Research questions and friction points this paper is trying to address.

Integrating journalistic practices into algorithm design for news tasks
Addressing concerns of algorithm-powered tools in journalism workflows
Studying perspectives on algorithmic translation of journalistic values
Innovation

Methods, ideas, or system contributions that make the work stand out.

Integrating journalistic practices into algorithm design
Studying perspectives for algorithm-powered journalistic tools
Contextualizing approaches and AI impacts in journalism
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