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Information
| Code | ILEM838 |
| Name | Artificial Intelligence and Media |
| Term | 2024-2025 Academic Year |
| Semester | . Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Belirsiz |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Dr.Öğr. Üyesi Kenan ATEŞGÖZ |
Course Goal / Objective
Students taking this course are expected to have knowledge about artificial intelligence and machine learning-mediated developments in the changing media environment with digitalization, to be aware of the effects of artificial intelligence-oriented developments on media and journalism practices, and to have a visionary perspective towards this. In general, this course aims to examine the theoretical and practical developments in the field of artificial intelligence and media.
Course Content
Information sharing and discussions will be held on the projections of technologies such as machine learning, artificial neural networks and deep learning as sub-branches of artificial intelligence, big data, algorithms, automation, robotization, or issues such as privacy and ethics in the field of media and communication. At the end of the course, it is aimed that students will be able to comprehend and interpret the artificial intelligence-mediated transformation of the media and communication field and have sectoral predictions for the future.
Course Precondition
There is no prerequisite for the course.
Resources
• Carroll, N. (2021). Augmented Intelligence: An Actor-Network Theory Perspective. İçinde F. Rowe, R. El Amrani, M. Limayem (Editör). European Conference on Information Systems (ECIS 2021) Conference Proceedings (s. 1-17). Marrakech: Morocco. • Caswell, D. (2023). AI and Journalism: What’s Next? Reuters Institute, https://reutersinstitute. politics.ox.ac.uk/news/ai-and-journalism-whats-next, (E.T.: Erişim 19.09.2023). • Chowdhary, K. R. (2020). Fundamentals of Artificial Intelligence. New Delhi: Springer. • Chowdhary, K. R. (2020). Fundamentals of Artificial Intelligence. New Delhi: Springer. Deuze, M. ve Witschge, T. (2018). Beyond Journalism: Theorizing the Transformation of Journalism. Journalism, 19(2), 165-181. • Çelik, İ. (2023). Exploring the Determinants of Artificial Intelligence (AI) Literacy: Digital Divide, Computational Thinking, Cognitive Absorption. Telematics and Informatics, 83, 1-11. • Çelik, İ., Dindar, M., Muukkonen, H. ve Järvelä, S. (2022). The Promises and Challenges of Artificial Intelligence for Teachers: A Systematic Review of Research. TechTrends, 66(4), 616-630. • Dörr, K. N. ve Hollnbuchner, K. (2017), Ethical Challenges of Algorithmic Journalism. Digital Journalism, 5(4), 404-419. • Druga, S., Vu, S. T., Likhith, E. ve Qiu, T. (2019). Inclusive AI Literacy for Kids Around The World. İçinde ACM Fablearn Conference (ss. 104-111). New York: 28-29 Mayıs, 2019 • Eguchi, A., Okada, H. ve Muto, Y. (2021). Contextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches. KIKünstliche Intelligenz, 35(2), 153-161. • Erdem, B. K. (2021). Yapay Zekânın Medya ve Yayıncılık Alanına Etkisi. TRT Akademi, 6(13), 896-903. • Faruqe, F., Watkins, R. ve Medsker, L. (2021). Competency model approach to AI literacy: Research-based path from initial framework to model, https://arxiv.org/ftp/arxiv/ papers/2108/2108.05809.pdf (E.T.: 15.09.2023). • Ghallab, M. (2019). Responsible AI: Requirements and Challenges. AI Perspectives, 1(1), 1-7. • Gillespie, T., Boczkowski, P. J. ve Foot, K. A. (2014). Introduction. İçinde T. Gillespie, P. J. Boczkowski ve K. A. Foot (Editörler), Media Technologies: Essays on Communication, Materiality, and Society (s. 1-17). London: MIT Press. • Gutiérrez, J. L. M. (2023). On Actor-Network Theory and Algorithms: ChatGPT and The New Power Relationships in the Age ff AI. AI and Ethics, 1-14. • Hermann, E. (2022). Artificial Intelligence and Mass Personalization of Communication Content—An Ethical and Literacy Perspective. New Media & Society, 24(5), 1258-1277. • İlhan, İ. ve Karaköse, M. (2021). Derin Sahte Videoların Tespiti ve Uygulamaları için Bir Karşılaştırma Çalışması. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, 8(14), 47-60. • Journo. (2023). Dünyanın İlk Yapay Zekâ Yasasını Avrupa Parlamentosu Onayladı. Journo, https://journo.com.tr/avrupa-birligi-yapay-zeka-yasasi-ap, (E.T.: 10.04.2024). • Kandlhofer, M., Steinbauer, G., Hirschmugl-Gaisch, S. ve Huber, P. (2016). Artificial Intelligence and Computer Science in Education: From Kindergarten to University. İçinde 2016 IEEE Frontiers in Education Conference (ss. 1-9). Erie: 12-15 Ekim, 2016. • Kırık, A. M. ve Özkoçak, V. (2023). Medya ve İletişim Bağlamında Yapay Zekâ Tarihi ve Teknolojisi: ChatGPT ve Deepfake ile Gelen Dijital Dönüşüm. Karadeniz Uluslararası Bilimsel Dergi, (58), 73-99. • Kim, J. H., Lee, K. H., Kim, Y. D., Kuppuswamy, N. S. ve Jo, J. (2007). Ubiquitous Robot: A New Paradigm for Integrated Services. İçinde 2007 IEEE International Conference on Robotics and Automation (ss. 2853-2858). Rome: 10-14 Nisan, 2007. • Kong, S. C., Cheung, W. M. Y. ve Zhang, G. (2021). Evaluation of An Artificial Intelligence Literacy Course for University Students with Diverse Study Backgrounds. Computers and Education: Artificial Intelligence, 2, 1-12. • Lee, I., Ali, S., Zhang, H., DiPaola, D. ve Breazeal, C. (2021). Developing Middle School Students’ AI Literacy. İçinde 52. Technical Symposium on Computer Science Education (ss. 191-197). USA: 13-20 Mart, 2021. • Long, D. ve Magerko, B. (2020). What Is AI Literacy? Competencies and Design Considerations. İçinde 2020 CHI Conference on Human Factors in Computing Systems (ss. 1-16). Honolulu: 25-30 Nisan, 2020. • Napoli, P. M. (2014). Automated Media: An Institutional Theory Perspective on Algorithmic Media Production and Consumption. Communication Theory, 24(3), 340-360. • Ng, D. T. K., Leung, J. K. L., Chu, S. K. W. ve Qiao, M. S. (2021). Conceptualizing AI Literacy: An Exploratory Review. Computers and Education: Artificial Intelligence, 2, 1-11. • Russell, S. ve Norvig, P. (2010). Artificial Intelligence: A Modern Approach. New Jersey: Pearson Education, Inc. • Turing, A. M. (1950). Computing Machinery and Intelligence-AM Turing. Mind, 59(236), 433- 460
Notes
Online resources.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Have knowledge about the current dimensions of digitalization in media. |
| LO02 | It reveals artificial intelligence mediated media practices. |
| LO03 | Develop critical thinking skills. |
| LO04 | Have knowledge about artificial intelligence platforms. |
| LO05 | Can effectively use methods related to artificial intelligence and media. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Belirsiz | Develops critical thinking skills. | 3 |
| PLO02 | Belirsiz | Have the conceptual and theoretical competence to explain the phenomena in Communication Studies disciplines. | |
| PLO03 | Belirsiz | She/he has knowledge of basic methodological approaches, methods, research techniques and their application and evaluation in communication and media studies.(dişil) | |
| PLO04 | Belirsiz | Identify local, national and international problems in the field of Communication Studies. | |
| PLO05 | Belirsiz | Gains the ability to analyze and synthesize the phenomena in the field of social sciences in an interdisciplinary context. | |
| PLO06 | Belirsiz | She/He reports a social research she designed in the field of communication studies and turns it into original works in accordance with academic rules. | 3 |
| PLO07 | Belirsiz | He/she transfers his/her knowledge of the field in an effective and systematic way, both verbally and in writing. Gains the ability to give lectures, conferences and seminars. | |
| PLO08 | Belirsiz | Have sufficient knowledge about the basic conceptual approaches used in the field of social sciences. | 4 |
| PLO09 | Belirsiz | Takes responsibility, leads and works effectively individually and/or in a team. | |
| PLO10 | Belirsiz | Selects data collection and analysis techniques within the appropriate methodologies and applies empirical studies in order to solve these problems, | 5 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Information about the course flow, teaching style, evaluation method and resources. | Sharing relevant resources, sharing examples. | Öğretim Yöntemleri: Anlatım |
| 2 | Evolution of Media: Digitalization | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 3 | Development of Artificial Intelligence | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 4 | Big Data | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 5 | Algorithms | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 6 | Automation and Robotization | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 7 | Machine Learning | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 8 | Mid-Term Exam | Reading and Discussion | Ölçme Yöntemleri: Ödev |
| 9 | Deep learning | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 10 | Artificial neural networks | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 11 | Artificial Intelligence and Ethics | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 12 | The effects of Artificial Intelligence on journalism practices | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 13 | Artificial Intelligence Journalism | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 14 | Artificial Intelligence and Disinformation | Reading and Discussion | Öğretim Yöntemleri: Anlatım, Tartışma |
| 15 | Sample Application | Application | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 16 | Term Exams | Reading and Discussion | Ölçme Yöntemleri: Ödev |
| 17 | Term Exams | Reading and Discussion | Ölçme Yöntemleri: Ödev |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||