Year: 2024
Type: article
Abstract: The study examines the transformative potential impact of Generative AI (GAI) on society, media, and media education, focusing on the challenges and opportunities these advancements bring. GAI technologies, particularly large language models (LLMs) like GPT-4, are revolutionizing content creation, platforms, and interaction within the media landscape. This radical shift is generating both innovative educational methodologies and challenges in maintaining academic integrity and the quality of learning. The study aims to provide a comprehensive understanding of how GAI impacts media education by reshaping the content and traditional practices of media-related higher education. The research delves into three main questions: the nature of GAI as an innovation, its effect on media research and knowledge acquisition, and its implications for media education. It introduces critical concepts such as radical uncertainty, which refers to the unpredictable outcomes and impacts of GAI, making traditional forecasting and planning challenging. The paper utilizes McLuhan’s tetrad to analyze GAI’s role in media, questioning what it enhances or obsoletes, retrieves, or reverses when pushed to extremes. This theoretical approach helps in understanding the multifaceted influence of GAI on media practices and education. Overall, the research underscores the dual-edged nature of GAI in media education, where it presents significant enhancements in learning and content creation while simultaneously posing risks related to misinformation, academic integrity, and the dilution of human-centered educational practices. The study calls for a balanced approach to integrating GAI in media education, advocating for preparedness against its potential drawbacks while leveraging its capabilities to revolutionize educational paradigms.
Source: Media Education
DOI: 10.36253/me-16303
Authors: Petri Honkanen, Mats Nylund
Institution: Arcada University of Applied Sciences
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4406794374