From black box to glass box: hidden mechanisms in automated journalism

Increasingly journalists are using automated tools in their research process. Digital, self-learning or AI tools are entering the journalistic market. We study how journalists use these tools and what the effect is on the gathering, selection and use of the found information and sources. 

Objective

The project aims to investigate what is involved in the implementation of explainable AI. In addition, this project aims to apply for follow-up research to ultimately arrive at an approach and tools for explainable AI.

Results

A practical checklist with checkpoints that must be considered in the implementation of explainable AI linked to the AI lifecycle and a scientific paper with the results of this project.

Duration

01 July 2020 - 01 July 2022

Approach

The research follows design science research. An artefact is developed from literature research and research into use cases in practice. The artefact in this case is a checklist that supports organizations in implementing explainable AI.

HU researchers involved in the research

  • Yael de Haan | Professor | Quality Journalism in Digital Transition
    Yael de Haan
    • Professor
    • Research groups: Quality Journalism in Digital Transition
  • Camila Valgas
    • Researcher
    • Research groups: Quality Journalism in Digital Transition
  • Sophie Duvekot
    • Researcher
    • Research groups: Quality Journalism in Digital Transition

Collaboration with knowledge partners

Any questions or do you want to collaborate?

Yael de Haan | Professor | Quality Journalism in Digital Transition

Yael de Haan

  • Professor
  • Research group: Quality Journalism in Digital Transition