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2020/2021  KAN-CKOMV1707U  Challenges and Opportunities of Datafication: Interdisciplinary Perspectives

English Title
Challenges and Opportunities of Datafication: Interdisciplinary Perspectives

Course information

Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Quarter
Start time of the course Second Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for BSc/MSc in Business Administration and Organizational Communication, MSc
Course coordinator
  • Nanna Bonde Thylstrup - Department of Management, Society and Communication (MSC)
Main academic disciplines
  • CSR and sustainability
  • Information technology
  • Organisation
Teaching methods
  • Online teaching
Last updated on 15-05-2020

Relevant links

Learning objectives
At the end of the course, students should be able to:
  • Identify economic, political, legal and ethical issues regarding a concrete datafication problem in an organizational context, making use of good searching principles and techniques.
  • Evaluate information sources on datafication, distinguishing scholarly sources from other content and critically assessing information from internet and other sources.
  • Manage information on datafication using online and other resources as well as appropriate citing and referencing techniques.
  • Effectively communicate and work together with students from Leuphana University in Germany meeting deadlines
  • Construct coherent and persuasive arguments in writing on current issues related to datafication, structuring the arguments logically and supporting them with relevant evidence
  • Plan and deliver an engaging and well-argued written presentation that coherently address both research question and audience
Examination
Challenges and Opportunities of Datafication: Interdisciplinary Perspectives:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 10 pages
Assignment type Written assignment
Duration Written product to be submitted on specified date and time.
Grading scale 7-point grading scale
Examiner(s) Internal examiner and second internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
If the student fails the ordinary exam the course coordinator chooses whether the student will have to hand in a revised product for the re-take or a new project.
Course content, structure and pedagogical approach

Information communication technologies (ICTs) and big data have given rise to a fundamental digital transformation across public and private sectors, a process referred to as datafication This course offers students the advanced theoretical and analytical skills needed to articulate, develop and understand the social implications of these digital transformations, their challenges and opportunities.

 

To provide conceptual and analytical frameworks that can help students develop, manage and reflect on data-driven strategies in organizations, this course will identify key economic, social, legal and ethical issues at the intersection of technology, business and society. 

 

Because of the organizational complexity of ICTs and big data, the course mobilizes cross-disciplinary insights to facilitate a range of analyses and management positions across private, public and non-profit organizations. Hence, the course brings together different perspectives, research methods, and practices from business studies, sociology, law, communication and data science. What is more, it includes perspectives from key stakeholders including entrepreneurs, policy-makers, journalists, and public intellectuals.

 

Following an introductory session the course will cover eight interdisciplinary topics: 

  1. AI and machine learning
  2. Datafication of text
  3. Datafication and organizational studies
  4. Datafication as power
  5. Big data analysis and data-driven business models
  6. Datafication and corporate digital responsibility 
  7. Crowdsourcing
  8. Sustainability  and environmental data 

 

Students will be taught these key focus areas and understand challenges and opportunities of datafication in public and private organizations. The course will include real-world cases, which will enable the students to contextualize and situate relevant case-based examples within existing scientific debates concerning big data, economy and society. 

Description of the teaching methods
The course is taught as a global classroom. This entails that it is open to MA students from CBS and Leuphana University who both participate and do the required coursework while they are encouraged to engage with each other and work collaboratively. For each week there is a split between lecture and tutorial. Lectures are pre-recorded and will be made available to all participating students from both universities. Each lecture introduces a topic and raises basic questions. In the tutorials students tackle practical problems which emerge from the topics raised in the lecture. The tutorials are also the forum where students are motivated to work collaboratively together in person. Additionally, as part of the tutorials, the course will make use of video conference tools in order to facilitate the interaction between the Danish and the German students in an innovative manner.

The course combines online academic lectures, online guest lectures, digital resources, digitally mediated group work, student presentations, and case studies in an engaging, participatory and global learning environment.
Feedback during the teaching period
Feedback takes a number of shapes in the course. We will discuss ideas for term papers throughout the course, students will be offered individual feedback through online forums and there will also be opportunities for students to engage in digitally mediated peer feedback.
Student workload
Reading 40 hours
Online Lectures and other videos 46 hours
Online activities 60 hours
Exam and preparation for exam 60 hours
Total 206 hours
Expected literature

The literature can be changed before the semester starts. Students are advised to find the final literature on Canvas before they buy the books. 

 

  • Yeung, K. & Lodge, M. (2019) Algorithmic regulation. Oxford: OUP.
  • Clemens Apprich, Wendy Hui Kyong Chun, Florian Cramer and Hito Steyerl (2019) Pattern Discrimination. University of Minnesota and Meson Press. Open Access
  • Lilly Irani (2019)Chasing Innovation: Making Entrepreneurial Citizens in Modern India. Princeton University Press. Open Access Penultimate Proofs
  • Starosielski, N., & Walker, J. (2016). Sustainable media: Critical approaches to media and environment. Taylor and Francis Inc. https:/​/​doi.org/​10.4324/​9781315794877
  • Arnim Wiek et al. (2013) A global classroom for international sustainability education. Creative Education4(4): 19-28.
  • Shoshana Zuboff (2019 The Age of Surveillance CapitalismThe Fight for a Human Future at the New Frontier of Power.  PublicAffairs 
Last updated on 15-05-2020