MTM Selected Issues:
Algorithmic News and Sensor Journalism - Reflections on AI in Management

(Master - WS '20/'21)

C. Loebbecke

 2 SWS, 6 CP

Fridays, 12:30 - 5:30 pm, selected dates see below
Location: ZOOM

Held in English

Overview

This is a master's level discussion course! We will understand and reflect upon a portfolio of presentations on 'Artificial Intelligence (AI) and Management' from the Academy of Management Conference, which took place in August 2020, and apply those to journalistic production (keywords here are sensor journalism or algorithmic news) as one specific management field. The challenge will be the transfer of the AI topics (presented by management scholars and discussed in class) to the specifics of journalistic production. As we will offer a broad range of considerations, both for AI and management and for journalistic production, the focus of our discussion will partially depend on students' preferences after having read and heard the material.

The idea of the course sessions will be to have a grounded discussion among students on the cutting edge topics covered in the material and to transfer their arguments to a specific context, here journalism. The idea is to develop and fine-tune one's arguments and line of thinking when being aware of rather contrasting insights and thoughts. The idea is NOT to know who said what and repeat anybody's text or words.

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

We already list the Pre-Assignment and two Intermediate Assignments (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 to have a guided integration of previously covered course material -- the more you got out of the course sessions, the easier and faster it will be.

Dates (max. 5)

Nov. 6, Nov. 20, Nov. 27, Dec. 18 - all '20, Jan. 15, '21; max. 5 dates

Pre-Assignment - due Oct. 21, '20, 11:00 am via eMail

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 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.

For each video clip,

1) Google the speakers and their recent / most prominent works so that you know where they come from. For each write about 30-50 words on where they are based, since when, and one or two other points that may help you remember who is who [6 x 30-50 words, <300 words in total].

2) Present his / her main topic / message / view point and try to write your text in a way that you give us explanations for the differences in the statements. What aspect of a presentation does a discussant use as viewpoint to provide a contrasting or complimentary perspective [6x 50-70 words, about 400 words in total]. Note that we are NOT interested in any particular study a presenter may offer!

Note: We also provide you with diverse additional material such as slides, papers, and more videos, but never use those spoken or printed words for ANY ASSIGNMENT.

3) Relate one of the video clips to one feature covered in Loebbecke / Picot (2015) (link requires VPN connection; https://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.]

*

Henfridsson, O., AI Capability for Data Network Effects, duration: 13:41, size: 75 MB (Download)

Keil, M., AI – Are we asking the right questions?, duration: 13:26, size: 16 MB (Download)

Rai, A., How Will the AI Genie Behave?, duration: 14:53, size: 104 MB (Download)

1st Intermediate Assignment - due Nov. 18, '20, 11:00 am via eMail

Read the Introduction and Chapters 1-4 of Diakopoulos, N. (2019) Automating the News: How Algorithms Are Rewriting the Media, Harvard University Press, Cambridge, MA, US,* and

1) Briefly summarize the relevant points (not the examples etc.) [about 200 words],

2) Relate selected thoughts to the topics in the three Pre-Assignment videos. Note that it says 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 [about 800 words].

*

Diakopoulos (2019), Introduction

Diakopoulos (2019), Ch1

Diakopoulos (2019), Ch2

Diakopoulos (2019), Ch3

Diakopoulos (2019), Ch4

Notes to the selected chapter above

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

2nd Intermediate Assignment - due Nov. 25, '20, 11:00 am via eMail

Repeat the Pre-Assignment on another four videos*. Different from the Pre-Assignment, on those four videos, it is your choice to include the discussant's perspective or not.
Again, and very important here: Note that we are NOT interested in any particular study, which a presenter may offer! Your job is to "skip" those parts.

*
Ramaprasad, J., AI & Decision-Making: Programming, Biases, and Moral Decision-Making, duration: 14:41, size: 96 MB (Download)
Butler, B., Assessing AI Value & Impact – Accounting for the Hidden Work of Reliability, duration: 13:27, size: 18 MB (Download)

Contractor, N., Using AI to Turbocharge Organizational Network Analysis, duration: 8:29, size: 33 MB (Download)

Kallinikos, J., Broadening Our Sight to "AI in Management", duration: 16:11, size: 49 MB (Download)

Final Assignment - due Dec. 16, '20, 11:00 am via eMail

Choose one of the following three statements

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

or

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

or

(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 tasks:

(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 Diakopolous (2019), one video from the 1st Intermediate, and one video from the 2nd Intermediate (you may have to change the some terms from those sources, so that in your assignment you use consistent wording.]

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

(3) Suggest a research project in the sense of Future Research, which could help to scientifically support or not support the statement (100-200 words)

[Suggest precisely WHAT you would investigate exactly HOW]

(4) Offer a reference list (can be short, but must be complete!)
[The videos and Diakopolous (2019) are sufficient. You may want to (1) look up some of the sources that the main text and the videos refer to, (2) check other readings by the authors, which you can find on their respective websites, and / or (3) relate to Loebbecke / Picot (2015) which you already read for the Pre-Assignment.]

(5) Prepare up to (max) 5 ppt(x) slides for a presentation of up to 12 minutes.
[12 minutes are maximum; important to focus precisely on the topic.

For text and slides: please note that 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 necessary
- Times New Roman, 12 pt., single-spaced
- Scientific writing style - no jokes, no slang, hardly any passive voice
- References IN THE TEXT (no footnotes), no "ibid." We talked about it ... Look up some Anglo-American academic management journals to see the placing of references.
- Consistent format (including spacing)
- 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 denis.niederle <at> uni-koeln.de; attach a non-protected word file (.doc or .docx)
- Subject line: MTM-Issues-Final-Lastname (your lastname only, no accent etc.)
- File names: MTM-Issues-Final-Lastname.doc(x) and MTM-Issues-Final-Lastname.ppt(x) (your lastname only, no accent etc.)

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

Course Grading

- Pre-Assignment: 20%

- Intermediate assignments (30%, individual)
- Active participation throughout the sessions - building on assignments / having digested the material  (30%, individual)

- Final Assignment and presentation (20%, individual)
All grading elements have to be passed in order to pass the course.
"Alle Prüfungselemente müssen mindestens bestanden sein, um den Kurs zu bestehen."

Required Course Registration until Oct. 21, '20, 11:00 am

A successful registration for the examination requires

(1) an MTM-Master-Account [Additional Privacy Policy],

(2) online registration HERE [Additional Privacy Policy] for THIS course.

On Oct. 21, '20, we will forward the participant list to KLIPS / WiSo-PA, which will allow you (only those registered for the course) to register for the examination. After that you can and must register for the examination by Oct. 29, '20. We will send those of you registered a reminding eMail to your sMail account.

Notwendige Veranstaltungsanmeldung bis 21. Okt. '20, 11:00 Uhr

Eine erfolgreiche Anmeldung erfordert

(1) einen MTM-Master-Account [Zusätzliche Datenschutzbestimmungen],

(2) Online-Anmeldung [Zusätzliche Datenschutzbestimmungen] für die Veranstaltung.

Am 21. Okt. '20 leiten wir die Teilnehmerliste an KLIPS / WiSo-PA. Daraufhin können und müssen Sie sich selbst bis zum 29. Okt. '20 für die Prüfung anmelden. Wir werden den für die Veranstaltung Angemeldeten eine Erinnerungsmail an ihr sMail Account senden.

Required Handing in of the Pre-Assignement by Oct. 21, '20, 11:00 am (see above) and subsequent exam registration until Oct. 29, '20 on KLIPS / Notwendige Abgabe des Pre-Assignments bis 21. Okt (11:00 Uhr) UND folgende Prüfungsanmeldung bis 29. Okt. '20 auf KLIPS (only for those who registered in time for participating in the course).

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

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