[MA/PA] Designing a tool for Artificial Intelligence Use-Cases

Thesis Advisor:

Thesis Description:

General Topic: Designing a tool for Artificial Intelligence Use-Cases

Problem Statement:

Artificial Intelligence (AI) is a buzzword, but also entails a range of unique technologies and methods that solve problems that humans were unable to address for a long time. As a general purpose technology (Agrawal & Goldfarb, 2019) it can be applied in many different areas but imposes context-dependent challenges to those developing and using it.

Not all organisations have the resources and capabilities (Sturm et al., 2021; e.g. Hofmann et al., 2021) to create new-to-the-world AI-solutions (Booz & Hamilton, 1982; Olson et al., 1995), but instead adopt existing AI-use-cases. However, it is challenging for organisations to describe such use-cases to classify, document and communicate them with other stakeholders.

Objectives: The goal of this thesis is to develop an interactive tool (artifact) that allows organisations to describe AI-use-cases systematically. You thereby build on an existing ontology by which such use-cases are described and transfer this ontology into a tool that can be used by practitioners.

Requirements: This thesis offering is in the field of IS and requires business understanding, motivation to learn new applications to create the tool and interest in academic research. Coding skills are required, depending on the tool with which you aim to create the solution.

Approach: This thesis takes an Design Science Research (DSR) approach (Hevner et al., 2004) to develop a solution (artifacts). A free course on DSR is provided online: Design Science Research – Essentials Series

The thesis can be written in English or German.

 

Process:

  1. Apply for this thesis by sending an e-mail with a short motivational text, your CV and current transcript to julius.kirschbaum@fau.de
  2. Initial meeting to discuss the topic and get to know each other
  3. Drafting an exposé
    1. Refine the problem statement
    2. Demonstrate the relevance
    3. Find your research question
    4. Build your research design
  4. Feedback meetings with supervisor during development
  5. Hand-in your thesis

 

References

AGRAWAL A, GANS J and GOLDFARB A (2019) Economic policy for artificial intelligence. Innovation Policy and the Economy 19(1), 139–159.

BOOZ and HAMILTON A& (1982) New products management for the 1980s. Available at: http://books.google.com/books?id=pP8JAQAAMAAJ&pgis=1.

HEVNER AR, MARCH ST, PARK J, RAM S, MARCH ST, PARK J, RAM S and MARCH ST (2004) Design science in information systems research. MIS Quarterly: Management Information Systems 28(1), 75–105.

HOFMANN P, JÖHNK J, PROTSCHKY D and URBACH N (2020) Developing purposeful ai use cases – A structured method and its application in project management. 15th International Conference on Wirtschaftsinformatik (WI).

OLSON EM, WALKER OC and RUEKERT RW (1995) Organizing for Effective New Product Development: The Moderating Role of Product Innovativeness. Journal of Marketing 59(1), 48.

PEFFERS K, ROTHENBERGER MA, TUUNANEN T and VAEZI R (2012) Design science research evaluation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7286 LNCS, 398–410.

STURM T, FECHO M and BUXMANN P (2021) To Use or Not to Use Artificial Intelligence? A Framework for the Ideation and Evaluation of Problems to Be Solved with Artificial Intelligence. In Proceedings of the 54th Hawaii International Conference on System Sciences pp 206–215. Available at: http://hdl.handle.net/10125/70634.