Implementing Accuracy for Responsible AI in Newsrooms
Implementing Accuracy for Responsible AI in Newsrooms
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Date
2024-8-9
Authors
Quintanilla Portugal, Roxana
Delle Ville, Juliana
Antonelli, Ruben Leandro
Journal Title
Journal ISSN
Volume Title
Publisher
Even3, Brazil
Abstract
This paper explores the intersection between software development
and journalism, highlighting the fundamental importance of implementing nonfunctional requirements to achieve a balance between immediacy and accuracy.
In software development, requirements encompass user needs and demand
precise and continuous updates to meet time-to-market demands. In journalism,
audience engagement drives the need for precise news coverage, especially with
the growth of artificial intelligence (AI). Non-functional requirements (NFRs)
have gained relevance, emphasizing the need for effective balance. This work
investigates the integration of technologies such as Named Entity Recognition
(NER) and topic modeling into news updating processes as means to enhance
both efficiency and precision. Additionally, this strategy, beneficial in
requirements management and applicable across domains, is explored. The
article is structured to delve into the imperatives of news writing, the proposed
strategy, potential applications, and directions for future research.
Description
Keywords
Non-functional Requirements,
NFRs,
artificial intelligence,
AI,
Natural Language Processing,
NLP,
journalism,
requirements engineering
Citation
Portugal, R. L. Q., Delle Ville, J., & Antonelli, L. (2024). Implementing accuracy quality for responsible AI in newsrooms. Proceedings of the 27th Workshop on Requirements Engineering (WER2024).