Generative Artificial Intelligence - APA 7th Edition - Citation Guide - CBS Library

GenAI

Generative Artificial Intelligence (GenAI) is a technology that has enjoyed quite a lot of attention recently with the launch of a number of end-user services, including Bing from Microsoft, ChatGPT from OpenAI, and Bard from Google. The technology is programmed to generate new and original content, including prose and images, by pre-training patterns from existing data.

In this way, GenAI is able to author well-composed and seemingly well-written papers with only the slightest prompt from a real person, which would seem to make it the perfect companion in higher education, and indeed in education everywhere, especially during peak periods where the workload may feel overwhelming.

Plenty of Pitfalls

There are, however, lots of problems associated with using GenAI in academia and elsewhere.

One of the more serious problems with the GenAI technology, not only in a high-intensity learning environment like CBS, but also in the world as such, is its inability to distinguish between true and false. Generative AI is not in the business of providing reliable content but only of prediction and probability and for that reason it is very prone to fabrication. In fact, to be able to utilize the technology with any kind of confidence, you would need to have a robust understanding of the topic at hand, an understanding that may take many years to cultivate.
Generative AI can replicate or even amplify negative content and may perpetuate biases and stereotypes about people and ideas. This issue has to do with the pre-training of the software. If the topic you are exploring is contentious, you may find yourself inadvertently reproducing fake news, conspiracy theories, etc. as the software is no better, no wiser, and no more beholden to the truth than the data, from which it learned. Online trolling goes on online on an industrial scale every single day, so if you just happen to tap into a minefield of viciously competing ideas when working with these services, you could be seriously compromised in your exam submissions.
With the relative dominance of English-language training data, there is a high likelihood that the responses you get will reflect a worldview that is specific to that part of the world. More likely than not, content generated by GenAI services is prone to represent Western perspectives and people and to drown out or misrepresent alternative, non-Western experiences, attitudes, and ideas.
Finally, because of the costs involved, in terms of both money and energy, the service is not retrained on an ongoing basis and as such cannot necessarily be relied on to reflect current ideas and insights. In other words, a lot of output data will quickly become outdated.

Banned!

To safeguard the purpose and integrity of the exam situation, which is to assess the knowledge, understanding, skills, and abilities of individual real-life students, CBS has decided to ban the use of GenAI in all exams other than bachelor´s theses, master´s theses, and final projects (HD / executive education), unless otherwise stated in the specific regulations for a particular exam.

This means that you are not allowed to submit for assessment any content that has been generated, manipulated, or otherwise processed using generative AI, as this under the current CBS guidelines would constitute unwarranted collaboration, a violation of CBS regulations that carries a legal sanction if detected.

The moment you start setting pen to paper, you are required to do so without the assistance or intermediation of GenAI or any other such intervention. In other words, everything submitted for assessment must be the result of your own, independent, and unassisted efforts.

Two Exceptions

Exception 1: Bachelor´s theses, master´s theses, and final projects (HD / executive education)

When writing their bachelor's theses, master´s theses, and final projects (HD / executive education), CBS students are permitted to use GenAI software for the following purposes:

As a language assistant. This is comparable to using language and spell-checking tools built into text-editing software.
As a search engine. This is comparable to searching for information using Google or similar discovery systems.
For idea generation and conceptualization, e.g. for suggesting a structure for a paper or elaborating on concepts and ideas but only if declared openly and transparently (cf. below).
As a generator of text, images, or other content but only if declared openly and transparently (cf. below).

For more details, check out the announcement memo in the right-hand menu

Exception 2: GenAI as a research object

The only general exception to the ban on generative AI in your exam submissions are those cases where the software itself is the object of an empirical investigation, i.e. where the purpose is to test, describe, and eventually understand the inner workings of the software and/or the quality of its outputs.

How to declare the use of GenAI

if you decide to use GenAI in a written assignment, you are required to follow the below guidelines to declare your use in an open and transparent way. This is to make sure that your assessors at all times are able to distinguish between your own intellectual and autonomous contributions and those contributions that originate in interactions with a GenAI platform.

If you use a GenAI tool for ideation or concept generation, you are required to mention this in the Methodology section of your paper. Alternatively, if your paper does not contain a separate Methodology section, you may also mention it in the Introduction. It is important to mention it early on, as in that case, your assessors will know what to expect.

Example of Methodology section declaration:

In this paper, I have used Microsoft Copilot to aggregate and summarize the results of 15 interviews conducted amongst CFOs in small- and medium-sized companies and based on these interviews to make suggestions for best practice financial reporting in SMEs.

Whenever you draw on GenAI output in the body text of your paper, you need to declare this by leaving in both the prompt and the relevant part of the response as well as a citation. On top of this, you need to leave the full response as an appendix for context.

Example of in-text declaration and citation (in the style of APA 7):

When prompted with "What is considered best practice financial reporting in SMEs?", Microsoft Copilot mentions a whole slew of attention points, including "adopting a financial reporting framework" and "using technology to streamline financial reporting" (Microsoft, 2023)

Whenever you leave an in-text citation in the body text of your paper, it should always be accompanied by a reference. This is no different than referencing a published work like a book or a journal article.

In APA 7, the in-text citation and reference should look like this:

Template:

(provider name, version year)

provider name. (version year). application name (version number) [Large Language Model]. URL

Applied to Microsoft Copilot, the reference would look like this:

(Microsoft, 2023)

Microsoft. (2023). Copilot (Feb 7 version) [Large Language Model]. https://www.bing.com/search