MG4G7      Half Unit
Contemporary Topics in Advanced Technology Management

This information is for the 2017/18 session.

Teacher responsible

Dr Edgar Whitley NAB 3.32

Availability

This course is available on the MSc in Management of Information Systems and Digital Innovation and MSc in Media and Communications (Data and Society). This course is available with permission as an outside option to students on other programmes where regulations permit.

Pre-requisites

This course assumes a general knowledge of information systems and their management equivalent to MG472 Global Strategy, Management and Information Systems.

Course content

This course introduces students to two Contemporary Topics in Advanced Technology Management.  It uses academic perspectives on the topics to provide a detailed contextualisation of technology’s historical and intellectual development and combines this with practitioner perspectives to highlight the management challenges associated with these technological developments.

In the first year, the topics are expected to be Artificial intelligence and Machine learning and Financial Technologies including Distributed Ledgers and Blockchains.

Teaching

9 hours of lectures, 10 hours and 30 minutes of lectures and 9 hours of seminars in the LT.

The lectures will be split into three 3-hour sessions and seven 90-minute sessions – a detailed schedule is available on Moodle.

A reading week will take place during Week 6. There will be no teaching during this week.

Formative coursework

Students will be expected to produce 2 presentations, 1 essay and 1 other piece of coursework in the LT.

Indicative reading

The reading list will be technology specific, and determined by the guest academics.  As such, they are likely to vary from year to year.  Detailed readings will be made available on Moodle.

Artificial intelligence and Machine learning

  • Fogel, M. (2016). The 10 Best AI, Data Science and Machine Learning Podcasts, Medium (available at https://medium.com/startup-grind/the-10-best-ai-data-science-and-machine-learning-podcasts-d7495cfb127c#.v7943hwof).
  • Minsky, M. L. (1988). Society of mind, Simon and Schuster London.
  • Rometty, G. (2016). Digital Today, Cognitive Tomorrow, MIT Sloan Management Review (available at http://sloanreview.mit.edu/article/digital-today-cognitive-tomorrow/).
  • Witten, I. H., Frank, E., Hall, M. A., and Pal, C. J. (2017). Data mining : practical machine learning tools and techniques., Morgan Kauffman Amsterdam.

Financial Technologies including Distributed Ledgers and Blockchains

  • Birch, D., Brown, R. G., and Parulava, S. (2016). Towards ambient accountability in financial services: Shared ledgers, translucent transactions and the technological legacy of the great financial crisis, Journal of Payments Strategy & Systems 10(2), 118–131.
  • Filippi, P. D., and Hassan, S. (2016). Blockchain technology as a regulatory technology: From code is law to law is code, First Monday 21(12) (available at http://firstmonday.org/ojs/index.php/fm/article/view/7113).
  • Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System, Bitcoin.org (available at https://bitcoin.org/bitcoin.pdf).
  • UK Government Chief Scientific Adviser (2016). Distributed ledger technology: Blackett review, (available at https://www.gov.uk/government/publications/distributed-ledger-technology-blackett-review).
  • Underwood, S. (2016). Blockchain Beyond Bitcoin, Communications of the ACM 59(11), 15–17.
  • Walsh, C., OReilly, P., Gleasure, R., Feller, J., Li, S., and Cristoforo, J. (2016). New kid on the block: a strategic archetypes approach to understanding the Blockchain, ICIS 2016 Proceedings (available at http://aisel.aisnet.org/icis2016/Crowdsourcing/Presentations/6).

Assessment

Essay (50%, 2500 words), presentation (15%), presentation (25%) and class participation (10%) in the LT.

The individual essay will focus on the emergent management challenges introduced by one advanced technology not covered in the lecture.

 

Key facts

Department: Management

Total students 2016/17: Unavailable

Average class size 2016/17: Unavailable

Controlled access 2016/17: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Self-management
  • Team working
  • Application of information skills
  • Communication
  • Commercial awareness
  • Specialist skills