Artificial Intelligence and Infodemic: Video Dataset for Fact-Checked Health Communication and Synthetic Media

Videos created using prototypes and APIs for participatory research. The videos were used as technological probes presented to various stakeholders.
This dataset was created in the context of Fact-Checking Chatbot Initiative. The proliferation of disinformation poses a significant challenge to societies. Within the field of journalism, fact-checking emerges as a critical tool to combat this issue. Technology has become a key enabler for the production and dissemination of dis- information. In this work, we question the use of technology as a solution to fight back disinformation, specifically examining the ethical implications of this choice. To address this, we organized a workshop using the Value Sensitive Design (VSD) methodology to explore questions in this context. The workshop introduced participants to the VSD framework, enabling them to critically assess whether specific scenarios align with human values, norms, and requirements. Real-world scenarios were discussed, including approaches implemented by legitimate news outlets and the use of 3D virtual characters by a Brazilian television employing deep learning. As artificial intelligence becomes more integrated into journalism, values such as truth, credibility, transparency, privacy, and consent become increasingly important considerations. Participants analyzed how technology impacts journalism values, norms, and practices, with a particular focus on aligning synthetic media technologies with automated fact-checking dissemination. In conclusion, the authors prepare a list of recommendations from valuable insights into the complex ethical considerations surrounding synthetic media technologies for automatic fact-checking dissemination. It also facilitated cross-border discussions, with 11 participants from seven countries engaging in fruitful dialogue on this vital topic. The study proposes evaluation criteria for AI-generated content in this diversity, including privacy protection, inclusiveness, transparency, beauty standards conformity, engagement, meaningfulness, and effortlessness.

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필드 값
소스 Data from fact-checking initiatives
저자 Haline Maia
최종 업데이트 10월 7, 2024, 10:51 (UTC)
생성됨 9월 27, 2024, 14:41 (UTC)
Citation Maia, H. (2024). Artificial Intelligence and Infodemic: Video Dataset for Fact-Checked Health Communication and Synthetic Media [Data set]. INESC TEC. https://doi.org/10.25747/TKJR-EV33
Contributor Priscila Ariel
DOI https://doi.org/10.25747/TKJR-EV33
Data Collection Method Data generated using API and prototypes
Date of Creation February 2024
포맷 mp4
언어 PT and EN
Temporal Coverage From 2022 to 2024
타입 Outputs of fact-checking videos using various LLM applications
Type of Instrument LLM applications. Globo prototype, Akool, D-ID, GPT, Claud