Perspectives on Information and Society

Course manual 2020/2021

Course content

The main aim of the course is to critically reflect on concepts central to Information Studies in terms of assumptions, limitations, and social and ethical implications. As information is the central notion of Information Studies we start with information. We approach information by using hermeneutics; this perspective highlights the characteristics of human understanding and is compared with an engineering perspective on information. Secondly we highlight current critique related to the use of data and algorithms in society; from this critical perspective we explore opportunities to improve the design of algorithms and information systems. Thirdly we explore the fundamentals of management and relate these to digitalization of society. We identify challenges for management and control from a traditional scientific management approach and from the perspective of Complex Adaptive Systems. The last topic is power. We identify characteristics of power both from a static and dynamic perspective and explore related challenges for IS-topics.

The course is divided in two parts. The focus during the first part is on understanding the different perspectives described above. In the second part, students are challenged to apply, explore and discuss the different perspectives in relation to specific IS-topics like design, implementation and living with numbers in a digital society. A variety of articles -incl. practical cases- is used to support this exploration.

Students are explicitly invited to share their work experience during the course, esp. students with jobs in the IS-field. These real-life situations can then be explored and assessed from the perspectives under discussion.

Study materials

Literature

• In the first part of the course we use several chapters from the book of Lucas D. Introna called Management, Information and Power. 1997. ISBN 0333698703. https://link.springer.com/book/10.1007/978-1-349-14549-2

   

  For lecture 5 on Data & Algorithms we use a short intro article: Richards & King (2013) Three paradoxes of Big Data.  https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2325537

   

  In addition: on Canvas there are links to other literature and material that relate to the topics dealt within the lectures.

   

  For the second part of the course we use the following literature:

  1. Lindberg, Meinel, Wagner (2011) Design Thinking: a fruitful concept for IT development?

  In: Meinel, Leifer, Plattner (eds) Design Thinking. Understanding Innovation. Springer, Berlin, Heidelberg.

  2. Introna, Whittaker (2002) The phenomenology of Information Systems evaluation: overcoming the subject/object dualism.

  In: Global and Organizational Discourse about Information Technology, [eds] Wynn, Whitley, Myers & DeGross, Kluwer: Boston, Mass.

  3. Lee etal (2015) Working with machines - the impact of algorithmic and data-driven management on human workers.

  Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp 1603-1612

  4. Tanweer etal (2017) Mapping for accessibility: a case study of ethics in Data Science for social good.

  Presented at the Data For Good Exchange 2017.

  5. Petrakaki, Hayes and Introna (2009) Narrowing down accountability through performance monitoring technology: E-government in Greece. Qualitative Research in Accounting & Management, vol6/nr3/p160-179

  6. Fay, Introna and Puyou (2010) Living with Numbers: Accounting for subjectivity in/with management accounting systems. Information and Organization, vol20/p21-43

Objectives

• The student is able to identify and explain two perspectives on information i.e. representational knowing and hermeneutic understanding
• The student is able to identify and explain current critique related to the use of data and algorithms in society
• The student is able to contrast management as scientific management and as manus management
• The student is able to identify and explain a static and dynamic perspective of power
• The student is able to relate the different perspectives described above.
• The student is able to develop and formulate implications of different perspectives for several IS-related topics.
• The student is able to critically assess the different perspectives described above.

Teaching methods

• Lecture
• Presentation/symposium
• Supervision/feedback meeting
• Working independently on e.g. a project or thesis
• Self-study

Learning activities

Attendance

In TER part B of this programme no requirements regarding attendance are mentioned.

Additional requirements for this course:

Presence in the lectures is mandatory for the following parts:

• 6 of the 7 Lectures during the first part of the course (first 4 weeks)
• The Exam in week 4
• 5 of the 6 Discussion Lectures in the second part of the course (last 3 weeks)
• The Discussion Lecture where your group is scheduled for the Discussion Assignment

Assessment

Check Canvas for detailed descriptions.

Inspection of assessed work

Will be announced on Canvas or in the lectures during the course.

Assignments

Check Canvas for detailed descriptions.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Timetable

The schedule for this course is published on DataNose.

Additional information

Please get familiar with the Course Design by checking the Canvas-site of the course.

Contact information

Coordinator

• drs. Arjan Vreeken