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MTM Selected Issues 1:
Artificial Intelligence in the Media

Master - WS '24/'25

C. Loebbecke

2 SWS

Fridays, 12:00 - 5:30 pm, max. 5 sessions!
Pre-Assignment Deadline: Oct. 09, '24, 11:00 am, via eMail from your sMail account

First Session: Oct. 11, '24, 12:00 - 1:30 pm

All students will receive a complimentary 3-months free 'Dyn' subscription and on Oct. 18, we will visit Dyn Media (Universitätsstr. 71, short walking distance) during the 2nd half of the course,
making the Inter-Assignments EASY and preparing for the Final Assignment (see below).

Likely location for sessions in presence: Lecture Hall XVIII, main building

Held in English

If you are interested in the course, please send an eMail from your sMail account to claudia.loebbecke<at>uni-koeln.de.

Overview

This is a master level discussion course with a mostly practical examination of the potential and risks of 'Artificial Intelligence' (AI) in the media, this semester focusing on sport journalism. We will investigate AI in sports media and in non-sport journalism. Assignments will build on the Pre-Assignment, the company visit to Dyn, and our course discussions. The better prepared you are for a session, the easier (and faster) you can do a perfect final assignment!

We will understand and reflect upon 'AI and Management' in the media context based on practitioner input and academic sources. Students will not need any technological experience, but should be open and enjoy to think through the opportunities and risks of deploying AI in the media. As we will offer a broad range of considerations, students can shape the focus of our discussion. The idea is to develop and fine-tune one's arguments and line of thinking regarding AI deployment in the media while being aware of rather contrasting insights and thoughts.

The main learning goals are (1) transfer cutting edge technological developments to academic lines of arguments (here: around media content), (2) considering academic research to understand contrasting views on AI in different media settings, (3) develop one's own thoughts / opinions (not technical solutions!) and back those up with academic arguments.

During the course, students will get practical experience and delve into practical insights – likely from dyn.sport and / or other media providers making use of AI in journalism. Presumably, I will also upload some Intermediate Assignments before the course starts.

Dates

Oct. 11, 12:00 - 1:30 pm (90 minutes online), Oct. 18 (on site session plus visit to Dyn), Oct. 25 (90 minutes, online if wanted), Nov. 15 (onsite), Nov. 22, Nov. 29 - all '24 and, only unlikely, Jan. 10, Jan. 17 - all '25!

Pre-Assignment due Oct. 09, '24, 11:00 am, via eMail from your sMail account.

(1) Go to dyn.sport and explain (in your words, so that you can present and explain in the course!) what the company offers [ca. 50 words], what you see as the biggest challenges to their business model [ca. 50 words] and try to assess how and for which task they use Artificial intelligence (AI) [ca. 100 words].

(2) Find a top academic journal paper (VHB-A or VHB-B) on some kind of use or impact of AI in political / social journalism approval and elaborate which aspect the paper investigates, how the researchers go about to get to their findings [ca. 150 words]. Feel free to send the chosen paper to claudia.loebbecke<at>uni-koeln.de for (yes / no) approval; it MUST BE a research contribution in a VHB-A or VHB-B journal.

Formal requirements
- State your name, matr.-number, sMail address, and study program with start date (max. two lines) in the header of each page; no cover sheet

- Have an empty line before the task, copy the task, and in the next line start the answer. For each regulatory initiative / article / paragraph have a subheading

- No empty lines after any heading / sub-heading, after a paragraph, or after a reference

- After a task, have one empty line before typing the next task and the answer

- NEVER two empty lines!

- Do not start a new page for every new task

- Times New Roman (TNR) 12, single-spaced

- Have 2 points (2 pts.) before and after each (1) paragraph

- Scientific writing style – no jokes, no slang, hardly any passive voice
- References IN THE TEXT (no footnotes), no 'ibid.' – s. some Anglo-American academic management journals
- NO author first names, NO usage of reference titles in the assignment text

- For formatting the reference list, see our website

- Consistent format (including spacing, etc.)

- Page numbers of references only for word-by-word citations

- Complete reference list formatted appropriately with all required information per file - – even if it is only one source
- See also MTM website on scientific work

Delivery

Please send an eMail from your sMail account to claudia.loebbecke<at>uni-koeln.de and irina.boboschko<at>uni-koeln.de; attach a non-protected word file (.doc or .docx)

- Subject line: MTM-Issues1-Pre-Lastname (your last name only, no accent, etc.)

- File name: MTM-Issues1-Pre-Lastname.doc(x) (your last name only, no accent, etc.)

Intermediate Assignment 1 due Oct. 23, '24, 11:00 am (AFTER the visit to Dyn, building on thr Pre-Assignment and, of course, the visit), via eMail from your sMail account.

Innovative Sport Journalism - Basketball on German TV

1) Dig deeper into basketball on Dyn. Be precise, do NOT repeat Dyn's website / slides. Total 600-800 words, see suggestions per bullet point.

- Outline the current market for basketball via OTT platforms [ca. 100 words]

- Identify key economic factors influencing basketball's popularity and viewership [ca. 100 words]

- Sketch out revenue streams (advertising, subscription models, and merchandising) and rough calculations for basketball on OTT. Refer to examples from other sports platforms and basketball leagues [ca. 150 words]

- Compare Dyn's operational setup regarding cost structure and efficiency (AI, cloud computing, and digital innovations) with industry standards [ca. 200 words]

- Propose two strategies to attract and retain basketball fans on OTT platforms (such as Dyn) [ca. 100 words]

- Suggest one market expansion strategy for basketball on Dyn based on examples / arguments from global OTT and sports media [ca. 100 words]

2) Abstract from Dyn and discuss the overall potential and risks of exploiting AI, cloud computing, and digital innovations in sports journalism (production, distribution) - based on all of the above … [500-700 words]

Formal requirements - as for the Pre-Assignment

Delivery

Please send an eMail from your sMail account to claudia.loebbecke<at>uni-koeln.de and irina.boboschko<at>uni-koeln.de; attach a non-protected word file (.doc or .docx)

- Subject line: MTM-Issues1-Inter1-Lastname (your last name only, no accent, etc.)

- File name: MTM-Issues1-Inter1-Lastname.doc(x) (your last name only, no accent, etc.)

Intermediate Assignment 2 due Nov. 06, '24, 11:00 am (presenting the Intermediate1 Assignment in slide format), via eMail from your sMail account.

Redo Intermediate 1 and prepare a cover slide plus 6 slides for Task 1 and up to 6 slides for Task 2.

Delivery

Please send an eMail from your sMail account to claudia.loebbecke<at>uni-koeln.de and irina.boboschko<at>uni-koeln.de; attach a non-protected word file (.doc or docx) and the PowerPoint slides (.ppt or .pptx / NOT pdf)

- Subject line: MTM-Issues1-Inter2-Lastname (your last name only, no accent, etc.)

- File name: MTM-Issues1-Inter2-Lastname.ppt(x) (your last name only, no accent, etc.)

Final due Dec. 12, '24, 11:00 am

Proposing a research study leading to practical implications relevant to Dyn.

(0) Do not repeat all you know about Dyn, you know it, we know it -- no point in writing anything again. [0 words]

(1) Derive ONE precise scientifically researchable question, where neither you nor Dyn know the answer. You could think about the pros and (!) cons why or why not the use of a certain technological innovation could help Dyn without knowing whether pros or cons will outweigh the other. And / or you could dig into the academic literature to reflect upon academic empirical studies (minimum one paper) which typically investigate one precise research question per empirical research paper.

What should Dyn learn that academic research (not market research) could answer/explain in a rigorous manner within 6 months or so. [about 300 words, RQ < 25 words ending with a question mark]

(2) Suggest a way / research design and ideally research method for you to conduct the research. State precisely how you would go about investigating YOUR research question.

IMPORTANT: Do NOT do the research and hence do NOT suggest a likely answer. Just convince Dyn (and me) HOW (!) academia could offer a contribution to their business. Here, looking at some academic papers which typically solve a very narrow / focused question may help! Do not copy, but learn from / transfer other / older research to outline a new study. [ca. 500 - 1000 words].

(3) Provide 4 or 5 slides: 1 slide with your name and title of the potential research paper, 1 slide presenting and deriving the RQ, 2 slides detailing the research design / method, 1 slide with academic references (if used).

Format rules see earlier course assignments.

- Subject line: MTM-Issues1-Final1-Lastname (your last name only, no accent, etc.)

- File names: MTM-Issues1-Final-Lastname.doc(x) and MTM-Issues1-Final-Lastname.ppt(x) (your last name only, no accent, etc.)

Course Grading

- 25%: Pre-Assignment (a very good Pre-Assignment will prepare extremely well for the rest of the course)

- 35%: Intermediate Assignments / Exercises and Discussions throughout the sessions – building on assignments / having digested the material

- 40%: Final Assignment and Presentation
It is required to at least 'pass' (grade 4.0 or better) each grading element for passing the course.
'Alle Prüfungselemente müssen mindestens bestanden sein.'

Required Course Registration:

(1) Hand in Pre-Assignment by Oct. 09, '24, 11:00 am (passing the Pre-Assignment is required for passing the course).
On Oct. 04, '24, we will list all those who will hand in the Pre-Assignment in time as course participant in KLIPS and THEREUPON you must
(2) Register for the exam on KLIPS by Oct. 17, '24.

For any course related questions, please contact claudia.loebbecke<at>uni-koeln.de from your sMail account.