Implementing Accuracy Quality for Responsible AI in Newsrooms

• Autores: Portugal, Roxana L.Q.; Delle Ville, Juliana; Antonelli, Leandro
• Año de publicación: 2024
• Idioma: inglés
• Tipo de recurso: documento de conferencia
• Materia: Ciencias de la Computación e Información; Requirements engineering; Artificial Intelligence (AI); Natural Language Processing (NLP); Journalism; Non-Functional Requirements (NFRs)
• Institución: Comisión de Investigaciones Científicas de la Provincia de Buenos Aires

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.