Home Page

Media and Technology Management (MTM) Selected Issues I (Master)
Algorithmic News and Sensor Journalism - Reflections on AI in Management

SS '22

C. Loebbecke

2 SWS, 6 CP

START: Apr. 08, '22

Fridays, 12:30 - 5:30 pm, in most cases we will end much earlier!
Selected dates see below
Location: ZOOM - live (no recording!)

Pre-Assignment due Apr. 01, '22, 11:00 am via eMail (see details below!)

Held in English

Overview

This is a master level, interactive discussion (!) course, we will understand and reflect upon a portfolio of presentations on 'Artificial Intelligence (AI) and Management' held during the Academy of Management Conference (Aug. '20) and apply our thoughts and insights to the specifics of managing journalism (keywords: algorithmic news or sensor journalism). The course offers a broad range of considerations concerning AI and management and their application to journalistic production. This allows students to shape the discussion - upon having read and heard some of the material.

During the course sessions, we will have a grounded discussion among students on the cutting-edge topics covered in the material and transfer the arguments to journalistic production. The aim is to develop and fine-tune one's arguments and line of thinking about AI, algorithmic news, and sensor journalism while being aware of rather contrasting perspectives. The aim is NOT to know who said what and repeat anybody's text or words.

Hence, the main learning goals are (1) using academic research to understand contrasting views on AI in journalism, (2) develop and ground one's own thoughts / opinions, and (3) back those up with academic arguments.

We already list the Pre-Assignment, Intermediate Assignments and Final Assignment (and the related materials) below. This way, students should have a good idea of the total workload and can work between now and the respective due dates. The Final Assignment will be a guided integration of previously covered course material along one of three topics (see below) – the more you got out of the course sessions, the easier and faster it will be.

Dates

Apr. 08, Apr. 22, May 06, May 27, and June 03 or June 24 – all '22; likely 4 and max. 5 sessions

Course Grading

Prerequisite for the acquisition of 6 CP are:

- 20%: Pre-Assignment

- 25%: Intermediate Assignments
- 30%: Active participation throughout the sessions - building on assignments / having digested the material

- 25%: 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 Apr. 01, '22, 11:00 am via eMail (see above); minimum passing that grading element, AND

(2) Upon receiving an eMail from Prof. Loebbecke on Apr. 01, '22, register for the exam on KLIPS by Apr. 07, '22!

Plus, to make things easier for all involved: If you are interested in taking the course, please send an eMail from your sMail account to three persons: claudia.loebbecke<at>uni-koeln.de, astrid.obeng-antwi<at>uni-koeln.de, and irina.boboschko<at>uni-koeln.de. The eMail must list the course, your first name, your last name, your 'matr.-number', and your study program. We suggest that you also add a phone number so that we can help on short notice.

Important: The registration only becomes binding for you, once you have handed in the Pre-Assignment latest on Apr. 01, '22, 11:00 am via eMail (see above). Hence, on Apr. 01, '22, we will list you as course participant in KLIPS and by Apr. 07, '22 you will then have to register for the exam of the course ('Prüfungsanmeldung') via KLIPS. We will help and double check, if / after you have handed in the Pre-Assignment.
For any course related questions, please contact claudia.loebbecke<at>uni-koeln.de from your sMail account.

Pre-Assignment - due Apr. 01, '22, 11:00 am via eMail

Tasks:

Watch three video clips*, each <15 minutes and each entailing a short presentation on an 'AI and Management' topic and thoughts provided by a pre-assigned discussant, whose job as a discussant is to challenge / question the given presentation. Note that these are NOT research presentations, but summaries of thoughts for entering a discussion. I.e., there is no research method, etc. This gives you in total six persons providing their views.

* Henfridsson, O., AI Capability for Data Network Effects (discussant: Olumba, U.), duration: 13:30 min., size: 75 MB (Download)

* Keil, M., AI - Are We Asking the Right Questions? (discussant: Beck, R.), duration: 13:30 min., size: 16 MB (Download)

* Rai, A., How Will the AI Genie Behave? (discussant: Tuunainen, V.), duration: 15:00 min., size: 104 MB (Download)

For each of the three video clips with two presentations each,

1) Google the speakers and for each state where they are based since when, where and when they did their PhD (perhaps even their master), at which other universities they held positions (between PhD and current), which academic editorial positions they held. Search for a CV or one or several bio abstract(s) published anywhere but their own website. Re. Mrs. Olumba: just tell us briefly what she does. [6x about 50 words, <300 words in total]

2) Present each presenter's main topic / message / viewpoint and explain the differences in statements – between presenter and discussant, and among the three clips with two presenters each. Do not transcribe the videos, but rephrase the crucial message to kick off the course discussion. We are NOT interested in any particular study a presenter may offer. [6x 50-70 words, about 400 words in total]

3) Relate one of the video clips to one feature covered in Loebbecke / Picot (2015) (link requires VPN connection; vpngate.uni-koeln.de). [about 50 words]

4) Be prepared to present your short pieces in the ZOOM discussion and to comment on your fellow students' contributions – graded as class participation, not as Pre-Assignment. Know your six persons and their main punch lines so that you do not have to scroll and search. We never like you READING your assignments loud in class.

1st Intermediate Assignment - due Apr. 20, '22, 11:00 am via eMail

Tasks:

Read Chapters 1-3 of Diakopoulos, N. (2019) Automating the News: How Algorithms Are Rewriting the Media, Harvard University Press, Cambridge, MA, US,* and

For each chapter, briefly summarize the relevant points (not the examples, etc.) and relate them to one or two topics of the Pre-Assignment videos, i.e., please dig deeper into a few points you care about, use additional references, presentations, etc. to anchor your discussion. [3x about 300-400 words]

*Diakopoulos (2019), Ch1

*Diakopoulos (2019), Ch2

*Diakopoulos (2019), Ch3 (mandatory ONLY up to 'The Business Case', s. yellow highlighting)

Notes to the chapter above

For the complete book, we refer to www.hup.harvard.edu/catalog.php?isbn=9780674976986.
Formal requirements: see above

Delivery:
Please send an eMail from your sMail account to claudia.loebbecke<at>uni-koeln.de and astrid.obeng-antwi<at>uni-koeln.de; attach a non-protected word file (.doc or .docx)
- Subject line: MTM-Issues-Inter1-Lastname (your last name only, no accent, etc.)
- File name: MTM-Issues-Inter1-Lastname.doc(x) (your last name only, no accent, etc.)

2nd Intermediate Assignment - due May 04, '22, 11:00 am via eMail

Tasks:

1) Repeat the Pre-Assignment on two more videos*.
* Ramaprasad, J., AI & Decision-Making: Programming, Biases, and Moral Decision-Making (discussant: Mooney, J.), duration: 14:30 min., size: 96 MB (Download)
* Butler, B., Assessing AI Value & Impact – Accounting for the Hidden Work of Reliability (discussant: Joyce, E.), duration: 13:30 min., size: 18 MB (Download)

AND

2) Watch the video presentation by N. Schick offered at the International Telecommunication Society (ITS) '21 webinar, duration: 37:30 min., size: 389 MB (Download) and
- Offer her definition of 'Deep Fake',
- Briefly present three of her 'Deep Fake' examples [one sentence p. example], and
- Relate the 'Deep Fake' concern to two of the issues raised in the five AoM'20 video clips covered before. [ca. 50 words]

Formal requirements: see above

Delivery:
Please send an eMail from your sMail account to claudia.loebbecke<at>uni-koeln.de and astrid.obeng-antwi<at>uni-koeln.de; attach a non-protected word file (.doc or .docx)
- Subject line: MTM-Issues-Inter2-Lastname (your last name only, no accent, etc.)
- File name: MTM-Issues-Inter2-Lastname.doc(x) (your last name only, no accent, etc.)

Final '1' (1st version) - due May 24, 11:am via eMail.

Tasks:

Choose one of the following three statements (we will talk about them during the earlier course sessions)

(A) If news production is automated, input data are the most determinant of the 'journalistic' output,

(B) Automated journalism is an oxymoron – machines cannot be part of the journalistic profession,

(C) The problem of 'automated news' and 'AI supported journalism' is that the audience cannot distinguish between human-made and automatically produced news,

and complete the following five steps:

(1) Explain and elaborate on the one chosen statement. [400-600 words]
Do not judge; but offer thoughts for and against the statement - integrate at least Diakopoulos (2019), one video from the Pre-Assignment, and one video from the 2nd Intermediate (you may have to change some terms from those sources, so that in your assignment you use consistent wording).

(2) Present your own position to the chosen statement. Here it is time for your opinion, keep in mind that we do not think or feel, but we argue and derive from arguments. [100-200 words]

(3) Suggest a research design for investigating one still open aspect of the first two tasks of the Final Assignment. Suggest precisely HOW you would investigate exactly WHAT. [100-200 words]

(4) Provide a rough outline / table of contents with meaningful headings and sub-headings for a paper to be written on the chosen statement.

(5) Offer a reference list (can be short, but must be complete!) The videos and Diakopoulos (2019) are sufficient. You may want to look up some of the sources that text and videos refer to and check other readings by the authors, which you can find on their respective websites.

Important: For the text, there is no 'right' or 'wrong', but there are consistent, convincing logical, and well-presented arguments versus blunt, poorly reflected statements.

Formal requirements:
- State your name, matr.-number, sMail address, and study program and its start date on top of the first page; then continue typing, no cover sheet!
- Max. 1 empty line before starting with the assignment text. Offer the task and then your answer.
- Times New Roman (TNR) 12, single-spaced.
- 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 repetition of reference titles in the assignment text.
- For formatting the reference list, see our website.
- Consistent format (including spacing, indentations, etc.).
- Page numbers of references only for word-by-word citations.
- Complete reference list formatted appropriately with all required information per file (see mtm.uni-koeln.de) – even if it is only one source.

Delivery:
Please send an eMail from your sMail account to claudia.loebbecke<at>uni-koeln.de and astrid.obeng-antwi<at>uni-koeln.de; attach a non-protected word file (.doc or .docx)
- Subject line: MTM-Issues-Final1-Lastname (your last name only, no accent, etc.)
- File name: MTM-Issues-Final1-Lastname.doc(x) and MTM-Issues-Final1-Lastname.ppt(x) (your last name only, no accent, etc.)

IMPORTANT: Make sure to include a MANUALLY SIGNED 'Eidesstattliche Erklärung' copied into the word file.

IDEALLY NOT NECESSARY Final '2' (reworked / extended version) - tbd.

Tasks: See Final '1' and the discussion in the previous session

Formal requirements: see above

Delivery:
Please send an eMail from your sMail account to claudia.loebbecke<at>uni-koeln.de and astrid.obeng-antwi<at>uni-koeln.de; attach a non-protected word file (.doc or .docx)
- Subject line: MTM-Issues-Final2-Lastname (your last name only, no accent, etc.)
- File name: MTM-Issues-Final2-Lastname.doc(x) and MTM-Issues-Final2-Lastname.ppt(x) (your last name only, no accent, etc.)

IMPORTANT: Make sure to include a MANUALLY SIGNED 'Eidesstattliche Erklärung' copied into the word file.