On December 3-4, 2024, the Ukrainian Press Academy, with the support of the Friedrich Naumann Foundation for Freedom, hosted the ninth and final webinar on the topic “Artificial Intelligence and Media Literacy: Tools and Recommendations.”
Participants of the webinar had the opportunity not only to learn about the latest developments in the field of artificial intelligence but also to discuss issues of ethics, responsibility, and challenges associated with its application. A significant part of the program focused on practical cases of AI use in education, journalism, and other fields.
Valerii Ivanov, President of the Ukrainian Press Academy, Doctor of Philological Sciences, and Professor, noted:
“The unprecedented popularity of this topic (with over a thousand applications to participate) demonstrates the high relevance of using language models in both journalism practice and media literacy teaching. We will continue to analyze current issues related to AI.”
Maksym Zaporozhchenko, Media Education Program Manager at the Ukrainian Press Academy and Head of the Center for Digital Education and Media Culture at the Mykolaiv Regional Institute of Postgraduate Pedagogical Education, remarked:
“If we compare our first training on this topic to the latest one, the amount of material has increased by about a third. This vividly illustrates how rapidly this industry is developing—not in years or even months, but in weeks and days.”
Andrii Yurychko, media trainer, journalist, candidate of philological sciences, and lecturer at Taras Shevchenko National University of Kyiv, commented:
“The world of Large Language Models is currently at a kind of promising crossroads—companies will invest in what people need. But for this to happen, these tools must be tested and made accessible to the masses. For us, this is an opportunity to study, understand, and explore how LLM tools can be integrated into workflows to enhance, accelerate, and improve them.”
Next year promises many exciting topics, so stay tuned by subscribing to our Telegram channel.
Supported by the Federal Republic of Germany
Gefördert durch die Bundesrepublik Deutschland
