The article’s discusses the arrival of Artificial Intelligence Content Generators (Gen-AI) such as Midjourney, Dall E2 and ChatGPT and sets out to explore if there is now any worth in studying creative subjects for young people.
The authors set out to prove that GenAI can improve employment opportunities ‘enhancing access and diversity for under-represented students, and can address the classic challenges of the theory-practice nexus for media production students’.
Given the trepidation around the arrival and use of these tools the focus of the article is to justify studying a creative arts degree.
The author suggests learning institutions should consider their offering to students in the creative sector and he sees GenAI as an opportunity and also as an area which would garner further interest from learners.
It discusses how GenAI can be incorporated into screen media training in higher education, with the understanding that people’s motivation for undertaking creative arts degrees are driven by a ‘love’ for the arts.
‘While the entry points are slightly different including those returning to upgrade their skills or enact a career change, the majority of students (92%) were attracted to the notion of pursuing creativity, in fact for some of these (11%), there was simply no other option’. Daniel and Johnstone (2017, 1025)
He believes GenAI can improve both artistic productivity and expression although there is a need to acknowledge the potential for malpractice such as plagiarism and universities’ drive to manage these, the focus with creative studies is the focus on creation and the end product of the process rather than the didactic, cognitive exercise of other disciplines.
He argues that a broad creative education will be more beneficial as it will allow creatives to pivot within the sector when required. He mentions the constraints around diversity in the sector such as under representation of certain groups.
The writer suggests GenAI will displace jobs in the creative sector especially as the sector is already precarious but argues that since creatives don’t enter the creative learning spaces for jobs but for ‘love’ this will not reduce enrolment.
He also argues the use of GenAi can be useful as assistants whilst taking note of issues around malpractice like plagiarism.
Interestingly he argues that universities have been quick to respond to issues around plagiarism by ensuring more focus on the process and product delivery. This is in contrast to other papers looking at AIED such as the Council of Europe’s report, (2022), and the Department of State’s call for Evidence, (2023), which discuss the difficulty of learning institutions to manage malpractice and call for urgent action in this area.
He criticises what he describes as ‘neoliberal’ practices which encourage training in trade and not traditional education especially in the creative sector. He feels this approach does not benefit learners as trade limits what they can do whilst an education enables them to pivot when they need to as they get an opportunity to learn a more varied curriculum.
The writer posits creative arts students would not be as keen to use GenAI to carry out their work for the very reason suggested above that this is an altruistic pursuit not based on money or fame. He feels the students like writers or artists would not appreciate GenAI writing a script or producing art in totality on their behalf. Of course there is no proof of this at the moment. Further research is required to justify this position.
He feels that given what he has identified as a neo liberal agenda, it would be useful for the creative arts education to present how GenAI will enhance and benefit the sector rather than limit it. He goes on to provide three suggestions to achieve this:
(i) improving graduates’ employment opportunities by boosting their flexibility and refocusing attention on cultivating a creative mindset: Apparently Sam Altman of Open AI and others expected AI to first impact manual labour followed by practices like medicine and ending up with the creative arts, instead it is impacting the creative sector first. The author argues that creative arts students must be trained for employability able to use their skills across sectors bringing creative mindsets and applicability to various roles not just creative roles, and thus learning to use AI tools will not impact on them negatively because they can pivot from just being artistic, a position which makes perfect sense and makes the teaching of AI tools imperative for this generation of students.
(ii) improving options for accessibility, inclusivity and providing opportunities for media arts courses to act as broadening programmes for a greater range of students from other areas: The author agrees that the use of GenAi allows people from underrepresented groups to have easier access to creating creative projects.
He also feels the use of GenAI tools allows people from other fields such as nursing or engineering to use the tools to collaborate or support their work such as using GenAI to provide support in creating shot lists or producing video essays.
(iii) Emphasising the value of aesthetic judgement, critical and theoretical understandings in order to concretely bridge the theory-practice nexus. He suggests that it is always vital for creative students to effectively translate theory into practice using concepts learned in their work.
He suggests that using GenAI will enhance this ability as students must use their knowledge of the topic to effectively generate the prompt which would in turn deliver the required product. For example, to generate the right image one must already have an understanding of lighting, space, mood and so on. The person with this theoretical basis will create a better image using AI tools than the one who does not or that even with script writing GenAI could come up with a script which could be refined by the students due to their theoretical knowledge.
He suggests the above three come together to enable students to use GenAI as useful tools to support the creative process.
The article advocates for the use of Gen AI in creative education as students still need to be trained and learn theories and concepts in order to use the tools effectively. It can serve as a formative or summative assessment tool to determine the understanding levels of students of concepts learned and it would help students hone their articulation and descriptive skills.
Although this was an article in support of GenAI in creative education the author does acknowledge complications and problems around the use of GenAi such as concerns around mechanised creativity, copyright and ownership.
This article was interesting to read, as it suggests a way forward for the integration of GenAI in creative and higher education. With a clear understanding of issues around GenAI such as malpractice, bias and copyright issues, as constantly argued by policy makers, this article suggests a way forward for creative education, clearly demonstrating how GenAI can be utilised by creative educators to enhance learners’ creative skills for employability.
Additionally, although this article is only four years old, the capabilities of GenAI tools within the creative sector are now far higher than the examples he presented in the article, which reenforces his arguments that the tools must be taught to students to enable them to compete effectively after their qualifications.
The only criticism is where the author argues that creative students choose the creative subjects for only altruistic purposes and therefore can pivot into other sectors easily. It is anticipated that creative graduates would want to be employed in the sector which is indicated by a study of 20,000 creative students where 78.8% of graduates freelance, (Firth, Whitefoot, 2023), an indication that they prefer working in their sector, thus more work is required in the sector and not an expectation that they would pivot.
Ultimately the tools are here to stay with ubiquitous access to all whether they are in creative arts education or not. It is imperative that creative arts education makes it a priority to equip students with the ability to use the tools, so they have an advantage over those without the creative arts degrees, otherwise the degrees become redundant.
Additionally, more needs to be done to improve the capacity of the creative sector to employ creative arts students making studying financially viable as in the long run people must pay their bills.
Reference list
Department of Education, Generative AI in education Call for Evidence: summary of responses, 2023, https://assets.publishing.service.gov.uk/media/65609be50c7ec8000d95bddd/Generative_AI_call_for_evidence_summary_of_responses.pdf
Miriam Firth, Elli Whitefoot , What do creative arts graduates do?, November 2023
Stuart Marshall Bender, Coexistence and creativity: screen media education in the age of artificial intelligence content generators
Pages 351-366 | Received 22 Jan 2023, Accepted 14 Apr 2023, Published online: 09 May 2023
Wayne Holmes, Jen Persson, Irene-Angelica Chounta, Barbara Wasson and Vania Dimitrova ARTIFICIAL INTELLIGENCE AND EDUCATION A critical view through the lens of human rights, democracy and the rule of law, 2022, Council of Europe
My course on 'How to Use AI in your Creative Practice' is available at www.famk.co.uk
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