A Review of literature in the field on artificial intelligence in education, creative education, creative practice and filmmaking

Abstract

This literature review looks at articles focused on artificial intelligence in education, (AIED), in creative education and practice and a further discussion focused on AI in filmmaking.

The articles reviewed spanned over twenty years of research up to 2000 and highlight the areas of focus and paradigm shifts in AIED research over the period.

The review indicated that AIED research has mainly focused on the technological applications of AIED with little focus on context or the pedagogical requirements of education.

Thus, when the Council of Europe’s, research is published their focus on human rights and protection of children especially in the use of AIED appears desperate and late as this had not been the focus of AIED prior to recent times, (Holmes et al, 2022).

Additionally, though the Department of Education’s ‘call for evidence’ (2023), provides a good indication of impact of use of AI tools, the literature points to a lack of preparedness by government and policy makers in the use of AIED.

The review further looks at the use and impact of AI in creative and filmmaking education and production, indicating positive outcomes when in use whilst calling for attention to be paid to the possibilities of monochrome productions and issues of copyright.

This review calls for immediate research into the impact of AIED and creative practice and filmmaking, not just in the context of its application or capabilities but on its pedagogical application within the context of social, environmental, economic and psychological structures.

Introduction As AI technologies advance, their integration into various domains becomes increasingly significant, particularly in education and creative practices.

The aim and scope of this review are centred on exploring the integration and impact of AI in the education and creative sectors. By examining the roles AI plays in these fields, the review seeks to provide a comprehensive understanding of its implications for educators, policymakers, and practitioners.

This paper will start by providing a specific definition of Artificial Intelligence (AI) which will be the framework around which this literature review is implemented.

This is because so many variations of the definition of Artificial Intelligence exist which can lead to a myriad ways of interpreting this review. An example is this simple definition by Peiming Sun, (2024), who states that most of the definitions can be placed within the ‘following four categories: systems that think like humans, systems that act like humans, systems that think rationally, and systems that act rationally’. (p.1)

Another is this more detailed definition by UNICEF: ‘AI refers to machine-based systems that can, given a set of human-defined objectives, make predictions, recommendations, or decisions that influence real or virtual environments. AI systems interact with us and act on our environment, either directly or indirectly. Often, they appear to operate autonomously, and can adapt their behaviour by learning about the context. (UNICEF 2021: 16).

Although they both provide an accurate definition of AI, for the purposes of this paper and the avoidance of doubt as to the discussion being held around AI the use of the definition by The International Journal of Artificial Intelligence in Education which is published in conjunction with the International Artificial Intelligence in Education Society (IAIED) will be used.

For them AI coverage includes; ‘agent-based learning environments, architectures for AIED systems, bayesian and statistical methods, cognitive tools for learning, computer-assisted language learning, distributed learning environments, educational robotics, human factors and interface design, intelligent agents on the internet, natural language interfaces for instructional systems, real-world applications of AIED systems, tools for administration and curriculum integration, and more’. (Springer Nature Link, 2024)

Adopting the definition of Artificial Intelligence as provided by the International Journal of Artificial Intelligence in Education, the scope of AI is understood to encompass a broad array of technologies and applications that emulate human-like intelligence and decision-making capabilities. This definition is critical in framing the exploration of AI's role within educational and creative practices, where its potential ranges from routine automation to fostering innovative thinking and problem-solving skills.To conduct this review, the following documents were reviewed:

·         Three documents by government and policy makers:

·         Two documents which reviewed AI in four hundred and fifty papers over a twenty-year period:

·         Two on AI in creative education:

·         Four articles on AI in filmmaking education and production.

It is anticipated these writings provided an opportunity to achieve the objectives of this literature review.

 The following sections of this review will delve into a comprehensive analysis of AI in education and creative fields, examining policy implications, historical contexts, pedagogical approaches, and research gaps, thus providing a holistic view of AI's evolving landscape.

To be noted, is the fact that a literature review was attempted to discuss the impact of the use of AI tools on film audiences, but no literature was available.

Methodology The selection criteria for the articles was initially quite broad as it was not clear if or how much research had been carried out in the field. As the research proceeded, five clear themes emerged:

1.      A review of how policy makers including the UK government viewed AIED in order to analyse their position and understand safeguards or actions taken in this space for users, designers and society as a whole. By selecting the Council of Europe there was an overview and understanding of how the European body viewed AIED, by looking at the article for the House of Lords, there was an understanding of how lawmakers approached AIED and a look at the Department of Education’s ‘call for evidence’ provided a specific look at how the department responsible for education in the UK was approaching AIED:

2.      Articles which could provide a historical overview of AIED and thus provide an analysis of paradigm shift in the sector over the years. By selecting some articles which had reviewed articles over a period of 20 years this provided a broad-church, bird’s eye perspective without necessitating an analysis of each individual article:

3.      A review of literature which could provide a discussion on pedagogical approaches within AIED:

4. Any literature which provided a discussion or perspective on AI in the creative sector or within filmmaking specifically:

5. Identify any gaps in research on AIED and AI in filmmaking.

Initially, Poe.com, an AI platform was asked to suggest articles and books which discussed AI in education and in filmmaking. Upon review of the list, several of them were found to be made up and did not exist, thus a large number of the suggestions were dropped.

A further search was then made on google scholar with the same keywords which provided the rest of the articles reviewed.

Writing the Review

Once each article was read, a full review was provided of the ideas, thoughts, findings and conclusions.  These eleven individual reviews were then placed in one article and an AI tool called myStylus was asked to rewrite the document summarising its key findings under the headings provided to it.

The AI tool reduced the literature review from over eleven thousand words to under four thousand words which were then further edited to ensure the document met the objectives of the review and the it was written in the author’s voice.

AI in Education

Policy Makers and Government Perspectives on AIED.The exploration of AI in education and creative practices necessitates a thorough understanding of the perspectives held by policymakers and governments, providing insights into the potential impacts and implications of AI integration. One of the documents reviewed is the House of Lords Paper written by Tobin, (2023), which examines the influence of artificial intelligence on educational systems in the UK. The paper emphasizes the need for a strategic approach to AI adoption, highlighting both opportunities and challenges associated with its deployment in educational settings.Similarly, the Council of Europe’s report, (Holmes et al., 2022), provides a comprehensive perspective on AI in education, stressing the importance of ethical considerations in policy formulation around issues such as democracy, rule of law and human rights. This includes a focus on data privacy, especially when it involves children, advocating for the possibility of consent refusal and withdrawal in schools, accountability by designers, and the equitable distribution of AI technologies.

Both papers decry the fast rise of EdTech tools in schools and the growth of the sector to over £1 billion in a short space of time. Tobin, (2023), refers to this as the ‘EdTech tragedy’, and UNESCO’s further reference to the ‘cannibalisation’ of the sector whilst the Council of Europe’ report, (2022), advocates that this focus on profit by designers is detrimental to the creation of tools which support the developmental needs of learners.

Both reports advocate for collaborative efforts and oversight among stakeholders and member states to ensure potential risks are mitigated.

In contrast to the Council of Europe’s report, (2022), and Tobin’s report, (2023), The Department of Education’s ‘Call for Evidence’, (2023), on the use of GenAI in education offered a more balanced view of AIED with more focus on its positive contribution. The survey was open for 10 weeks in 2023 and it received 567 responses from the education, EdTech and other AI organisations both within and outside the UK.

This report indicated that positive responses on the use of AIED were the norm rather than the trepidation indicated by the Council of Europe, (2022) and Tobin, (2023), an indication that the response to the AI tools differ between users of the tools and the technocrats who create policies and have oversight.

The similarities in this report to the other two was the call by teachers for policy makers to accredit tools in order to create confidence in their use and to ensure equity of access and collaborate with all stakeholders to ensure relevance and mitigate risks.

Policy Implications and Recommendations.

All three papers call for the alignment of AI policies with international standards to facilitate global cooperation and consistency in educational systems in addressing ethical issues around copyright, bias, inequality, good governance rule of law and human rights and ensuring that AI technologies are accessible to all, and the right safeguards are in place for users whilst holding designers accountable. In addition, the COVID-19 pandemic has significantly accelerated the adoption of technology in education, highlighting the critical need for adaptable policies that can withstand the changes. Policymakers are urged to consider the long-term impact of accelerated technology integration, balancing immediate educational needs with future developments.

The language used, however, by policy makers in these reports are negative which can create trepidation and fear of the tools for users. The Council of Europe Report, (2022), for example states that technology is complex and non-linear with ‘dangerous unforeseen consequences’ almost as though there is the presence of a bogey man waiting for all who may try to enter this room of technology.

In a similar vein, Tobin’s report for the House of Lords, (2023), uses UNESCO's label of AIED as the "ED Tech Tragedy” which is a strong statement, potentially instilling fear in policymakers and educators, and stifling innovation and experimentation.

The usefulness of the Council of Europe’s, (2022), document is its discussion on human rights, the rule of law and democracy as it provides a key perspective in the deployment of AIED with human rights and law at the fore of any decisions or consideration in all learning tools including AI tools.

Additionally, they discuss concepts such as ‘data rent’, ‘AI loyalty’, and ‘AI colonialism’, ideas not readily discussed in the mainstream, but which are all important considerations in AIED.

All three papers call for the collaboration of stakeholders in the sector to ensure protection, quality and equity, yet none of them propose who will be responsible or activating or managing this process or how it will be done. The Council of Europe, (2022), have called for designers to lead the process whilst, in the Department of Education report, (2023), the respondents have suggested the government should lead this process. This makes more sense as the organisations responsible for the protection of human rights should lead this process especially as they decry the money-making focus of designers. 

The reports acknowledge the benefits of AIED around giving teachers more time, the provision of support for students especially around SEND, students for whom English is an additional language, subject specific support and also agree that AIED will not replace teachers in the classroom even though some of its uses could support the lack of teachers in remote places for example.

Although both the Council of Europe, (2022), and Tobin’s report, (2023), criticise AIED designers for providing tools whose pedagogical frameworks are cognitivist they fail to recognise that the designers are not the organisations which decide on pedagogical frameworks. These are decided by learning institutions. And though they feel AIED has failed to provide more social constructivist learning pedagogy they fail to recognise that designers will only respond to the demand for tools and not create or dictate learning pedagogies. Thus, it is for learning institutions to determine the pedagogical directions and demand those from the designers which makes the request for oversight by teachers relevant, (Department of Education, 2023).

All three reports have called for further research on the impact of AIED on learners especially around their psychological, cultural, social and economic influences.

Evolution of AI in Education 

The evolution of Artificial Intelligence in Education (AIED) over the past three decades has been marked by significant paradigm shifts and technological advancements.

A review of literature by Guan, Mou and Jiang (2020), provides a twenty-year analysis of AIED based on 425 articles published between 2000 and 2019 traced these shifts over the years. 

Although Ido Roll and Ruth Wylie, (2016), was one of the articles reviewed by Guan, Mou and Jiang (2020) this article which reviewed 47 articles on AI in Education from ‘three years in the history of the Journal of AIED (1994, 2004, and 2014)’, was reviewed on its own for a more specific analysis of its findings.

The reports indicate that Initial efforts in AIED focused on rule-based systems that attempted to mimic instructional roles traditionally held by educators. These systems were limited in their adaptability and flexibility, often providing routine traditional, cognitive systems of  learning experiences rather than dynamic engagement.As AI technology advanced, the development of intelligent tutoring systems (ITS) introduced a new era of personalized education. These systems leveraged data-driven algorithms to customize learning experiences based on the individual needs of students, thereby offering a more personalized approach to education. The advent of machine learning and natural language processing further enriched these capabilities, enabling real-time feedback and interactive learning environments that facilitate deeper engagement and understanding.Recent advancements have seen the incorporation of AI into adaptive learning technologies, which adjust the complexity of educational content in response to student performance. This iterative adaptation fosters a tailored educational journey that can accommodate diverse learning styles and paces. Furthermore, the integration of AI with emerging technologies like virtual and augmented reality has expanded the scope of immersive learning experiences, providing students with practical, hands-on opportunities to apply their knowledge in realistic scenarios.

Roll and Wylie, (2016), go on to add they believe the human tutor may be coming to the end of its days as AIED supersedes borders, times, and number of learners. They feel these capabilities should be exploited to further augment, grow and solidify AIED.

They say they are not calling for the total disappearance of the teacher but rather a new kind of teacher that comes alongside the student as a mentor supporting life-long skills development and not just ‘domain knowledge’.  This is interesting as one of the articles reviewed for this paper, ‘Exploring the Use of Generative AI to Support Lecturing in Higher Education’ by Darius Hennekeuser et al., (2024),  suggest that universities must continue to provide domain knowledge which incorporates AI as it allows learners to more effectively apply their knowledge across sectors rather than what they feel is a pandering to left-wing ideology of limited skills development.

The articles indicate that the emphasis has shifted from simply automating instructional practices to creating intelligent systems that enhance the learning experience and outcomes. This evolution reflects a broader trend in AIED toward creating human-centred AI systems that augment rather than replace traditional educational practices thus Roll and Wylie, (2016), have stated that AIED designers have failed to be innovative in their design of the tools and rather have become complacent in replicating traditional pedagogical systems instead of creating new more innovative ones an accusation levied at AI designers by the Council of Europe’s report as well. (Holmes et al, 2022).

One significant lesson from past developments is the importance of ensuring that AI systems are designed with the user's needs in mind. Early AIED systems often failed to account for the diverse learning styles and preferences of students, resulting in a one-size-fits-all approach that limited engagement and effectiveness. As a result, contemporary AIED strategies now emphasize personalization and adaptability, ensuring that educational content is aligned with individual learner profiles. On the other hand, Holmes at al, (2022) counter the idea that AIED tools have effectively provided individual learning routes for users. They indicate in their report that the tools have followed cognitive learning theories to provide linear systems of learning to arrive at the same outcome from assessments rather than individual outcomes from individual routes. Furthermore, historical experiences have demonstrated the necessity of interdisciplinary collaboration in AIED projects. The complexity of creating effective AI-driven educational tools demands input from experts across fields such as education, computer science, psychology, and cognitive science. This interdisciplinary approach fosters the development of holistic systems that address both technical and pedagogical challenges in AIED, an idea the reports by policy makers support but which appears elusive.

Challenges and LimitationsAccording to (Holmes et al, 2022; Tobin, 2023; (Department of Education, 2023), one of the primary concerns is the issue of bias which they say is inherent within AI systems. They believe AI algorithms can inadvertently perpetuate existing biases found in the training data, leading to potentially discriminatory outcomes that can disadvantage certain groups of students, and they feel this raises ethical considerations that require careful scrutiny and mitigation to ensure fairness and equity in educational settings. The writers believe the implementation of AI in education demands a critical assessment of data privacy and security. Educators, institutions, and developers must navigate complex legal and ethical landscapes to protect sensitive information while leveraging AI technologies. Ensuring that robust safeguards are in place to protect student data is essential for building trust and maintaining the integrity of educational practices. (Holmes et al, 2022; Tobin, 2023; (Department of Education, 2023)They feel the rapid pace of technological advancement poses challenges in terms of resource allocation and infrastructure. Schools and educational institutions may face difficulties in acquiring the necessary technology and expertise to implement AI effectively. Lack of access to resources can exacerbate educational disparities and create digital divides, making it imperative to develop strategies that ensure inclusive and equitable deployment of AI tools. (Holmes et al, 2022; Tobin, 2023; (Department of Education, 2023)It should be noted that AI as a tool is not biased. The world it is inherently biased, and it simply produces based on input and demand. Educational authorities, policy makers and governments need to have a better understanding of AI in relation to bias instead of this one-sided view which leads people away from engaging with AI for a fear of bias which does not actually exist.

Additionally, educational settings are most likely the safest places for children in regard to the internet as they have several safeguarding measures in place to protect their students. Thus, instead of stoking fear among educational establishments, guidance should be provided on how to enhance their safeguards.

Inequalities are not caused by AI tools, rather they exist in the real world across nations, schools, communities and these inequalities need to be dealt with if access to AI tools are to be equally accessed. Alternatively, governments, instead of complaining about it, have the power to invest in poorer areas to create AI equity.

Finally, the writers, (Holmes et al, 2022; Tobin, 2023; (Department of Education, 2023), posit that while AI holds the promise of transforming pedagogical models, it necessitates a re-evaluation of traditional teaching practices and methodologies.

This is of course problematic as well, as AI developers are not educators but simply build on the existing pedagogical frameworks which exist. Thus, it is educators and policy makers who must adapt to new roles and responsibilities, often requiring professional development and training. The transition to AI-supported education systems also demands openness to innovative pedagogies that align with 21st-century learning needs and once these are clear, developers will be able to respond. (Rolf and Wylie, 2016; Guan, Mou and Jiang, 2020).

AI in the Creative Sector

AI in Creative EducationThe impact of Artificial Intelligence (AI) on creative education has the potential to reshape the way creative disciplines are taught and practiced in academic settings. According to Yang et al, (2023), and  Stuart, (2023), as AI technologies are integrated into creative curricula, a new paradigm becomes possible which balances student learning and creativity with AI efficiency and innovation.

The writers believe these tools enable students to experiment with cutting-edge technologies, offering opportunities to explore new forms of artistic expression and media production. The study by Yang et al, (2023) aimed to explore the benefits of incorporating AI tools within filmmaking education from script writing through to production and post-production.

The article itself agreed new tools are being developed and indeed since this article was written in 2023, there are filmmaking tools which can be used in film production not just in pre, post or VR but in actual filmmaking production specifically tools like Gen-3 Runway, Kling and Sora. 

They suggest filmmakers may be overwhelmed when confronted with the plethora of tools in the market, a concern raised by teachers in the survey carried out by the Department of Education, (2023) who also called for guidance and accreditation of tools that can be used within educational settings. 

The study showed the impact of AI in education was positive for both learners and teachers. It indicates AI can enhance learning, but which educators are not widely utilising.

AI-powered software assists in tasks such as design, music composition, and visual effects, providing students with new and different ways to engage with their craft and broaden their creative horizons.

Stuart Marshall Bender,(2023), 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.

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 without it.

Both articles advocate that the introduction of AI in creative education encourages a more dynamic learning environment. It allows educators to devise interactive and personalized teaching methodologies that cater to the diverse needs of students. By supporting adaptive learning pathways, AI enhances the educational experience, ensuring that students can progress at their own pace and develop competencies aligned with industry standards.Stuart Marshall Bender,(2023),argues that while AI can automate certain processes, it is essential to retain the emphasis on creativity, critical thinking, and originality. Educators must navigate the integration of AI by fostering a curriculum that encourages innovation while grounding students in the fundamentals of creative practices, giving them an edge over competitors who do not have this grounding.The articles suggest that as AI continues to evolve, its impact on creative education will increase, requiring ongoing adaptations in teaching methodologies and curricular design. The collaboration between educators and technologists is vital to ensure that the implementation of AI enriches creative education without overshadowing the essence of artistic and creative inquiry. (Yang et al, 2023; Stuart Marshall Bender,2023), a suggestion advocated for by the policy makers mentioned above.

Role of AI in FilmmakingFrohlick, (2020), discusses AI's role in filmmaking as it spans across several processes, from pre-production to post-production, providing innovative solutions that streamline creative workflows and opens new avenues for artistic expression:In the pre-production phase, AI tools are being employed to analyse script patterns, predict audience preferences, and assist in storyboarding, enabling filmmakers to make data-driven decisions that align with market trends. AI algorithms can sift through vast amounts of data, extracting insights that inform screenplay development and casting choices, ultimately increasing the likelihood of a film's commercial success.During production, AI technologies are utilized in areas such as visual effects, animation, and cinematography. Machine learning algorithms can enhance image processing and editing, resulting in more realistic and engaging visual content. AI-driven robotics and drones are also being used to capture innovative camera angles and perform complex shots that would be challenging for human operators.

In post-production, AI is revolutionizing the editing process by automating tasks such as colour grading, sound editing, and video summarization. AI systems can learn the stylistic preferences of filmmakers to craft cohesive and visually appealing narratives efficiently. Additionally, AI tools support subtitling and translation services, facilitating global distribution and accessibility.

Ali Khosh, (2017), discusses the use of AI in journalism and AI’s ability to understand patterns, predict news and conflict areas and support the writing process whilst Eric Zhou and Lee, (2024), used a ‘dataset of over 4 million artworks from more than 50,000 unique users’ to acknowledge that AI tools can now produce content originally considered creative and the domain of humans. Tools such as Midjourney Dall E 3, Stable diffusion, and ChatGPT enable human participation in the creative process through text or visual input.

All three articles acknowledge the opportunities for enhancing creativity in creative practice and filmmaking through AI are vast. By automating routine tasks and providing insights into creative decisions, AI allows creatives and filmmakers to focus more on artistic storytelling and experimentation.

Zhou and Lee, (2024), and Bender, (2025), further discuss that the integration of AI could pose challenges, such as ethical considerations regarding authorship and the potential homogenization of creative content but suggest that its use pushes the boundaries of creativity for users especially people already skilled as creative practitioners. In summary, the three articles suggest AI is proving to be a valuable collaborator in the creative and filmmaking process, driving efficiency and innovation. What is quite clear, however is the speed at which GenAI tools are innovating. This makes some of the tools made in the research documents reviewed already redundant as new tools become available which can make films and are becoming more efficient, precise and innovative.

Additionally, the issues around the use of GenAI tools and the issue of ownership is a constant battle fought in the courts and in the media as writers, actors and other creatives seek for legal protections whilst developers push back insisting that creatives are slowing down the pace of progress and governments remain in a conundrum unsure of which side to protect.(Oguntola, 2025).  Interestingly, Finland have passed a law which gives people legal ownership of their image and other physical attributes thus requiring permission before they are used within GenAI, (Guardian 2025), proving the leadership and guidance other governments need to emulate.

Research Gaps

The integration of AI into education and creative practices is still in its early stages despite the large strides it has made, and consequently, there are significant areas where research is insufficient. One primary area of concern is the long-term impact of AI on educational outcomes and artistic expression. While short-term benefits of AI implementation, such as enhanced engagement and personalized learning, have started to be documented, comprehensive studies of impact are scarce. The Council of Europe, (Holmes et al, 2022), called for research on the psychological, social, cultural impact of this integration as well. Data discussing the psychological impact of AI on educators, creatives and users is missing in the field and is necessary.The intersection between AI and interdisciplinary studies is another area requiring further investigation. As AI begins to permeate diverse academic and artistic disciplines, understanding how these intersections can be leveraged to foster innovation is crucial. Studies exploring the integration of AI across creative education, in particular filmmaking, could provide valuable insights into collaborative methodologies potential applications and inspire new pedagogical approaches.

Research does not exist on the impact of AI created content on consumers. As AI tools and AI generated content continue to permeate the landscape, it is vital that research is undertaken to understand consumers’ response especially in terms of their psychological, cultural and social influences and backgrounds.

In summary, addressing these research gaps is essential for the responsible and innovative integration of AI in education and creative practices. By focusing on these areas, future research can provide a more holistic view of AI's role and facilitate a better understood, coherent and sustainable deployment.

Reference List

Alex Frohlick, Artificial Intelligence and Contemporary Film Production: A Preliminary Survey, July 2020, Goldsmiths, University of London

https://www.researchgate.net/publication/342978310_Artificial_Intelligence_and_Contemporary_Film_Production_A_Preliminary_Survey

Ali Khosh, Storytelling in the Age of Artificial Intelligence, 2017, https://khoshgozaran.com/ai-story-telling/

Anita Chaudhary, Innovative Educational Approaches: Charting a Path Ahead , ARTIFICIAL INTELLIGENCE IN EDUCATION, (Page 57-61), 2023,  https://parabpublications.com/books/pdf/innovative-educational-approaches-charting-a-path-ahead.pdf#page=57

Chong Guan, Jian Mou, Zhiying Jiang, 2020, 'Artificial intelligence innovation in education: A twenty-year data-driven historical analysis, https://doi.org/10.1016/j.ijis.2020.09.001

Darius Hennekeuser, Daryoush Daniel Vaziri, David Golchinfar, Dirk Schreiber & Gunnar Stevens, 2024, Enlarged Education – Exploring the Use of Generative AI to Support Lecturing in Higher Education, https://link.springer.com/article/10.1007/s40593-024-00424-y

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

Eric Zhou, Dokyun Lee, Generative artificial intelligence, human creativity, and art 

PNAS Nexus, Volume 3, Issue 3, March 2024, page 52,  https://doi.org/10.1093/pnasnexus/pgae052

Guardian newspaper, 2025, Denmark to tackle deepfakes by giving people copyright to their own features

https://www.vice.com/en/article/denmark-is-fighting-ai-by-giving-citizens-copyright-to-their-own-faces/#:~:text=To%20tip%20the%20scales%20back%20in%20favor%20of,someone%20who%20uses%20their%20image%20without%20their%20consent.

Ido Roll1 & Ruth Wylie,  Evolution and Revolution in Artificial Intelligence in Education, 2016, International Artificial Intelligence in Education Society 2016

James Tobin, (2023), Educational technology: Digital innovation and AI in schools, House of Lords Library, https://lordslibrary.parliament.uk/educational-technology-digital-innovation-and-ai-in-schools/

Oguntola Nana, 2025, 'Get around the table' is my call, https://www.nanaoguntola.me/post/get-around-the-table-is-my-call

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

Wei Yang, Hyemin Lee, Ronghui Wu, Ru Zhang, Younghwan Pan, (2023)

Using an Artificial-Intelligence-Generated Program for Positive Efficiency in Filmmaking Education: Insights from Experts and Students

https://www.researchgate.net/publication/376014367_Using_an_Artificial-Intelligence-Generated_Program_for_Positive_Efficiency_in_Filmmaking_Education_Insights_from_Experts_and_Students

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