Introduction & Brief History

Post-pandemic, the mainstream introduction of Artificial Intelligence (AI) advanced out of a need for change, highlighting both its potential benefits and risks it poses. In the years that followed, there has been a rapid acceleration in notable tools, each with the capacity to cause a significant shift in the creative industry. This brought forward a critical question at the centre of the creative industry:Will we be replaced? Some might argue that AI could soon perform all creative disciplines more efficiently and at lower costs. This essay will follow the benefits and challenges of integrating Artificial Intelligence, examining its impact on the creative sector and recent technological developments. It will present a balanced argument, investigating AI in this early stage of uncertainty and instability. The purpose of this paper is to discuss my personal experiences of generative AI, the challenges of intellectual property, benefits, ethical implications, and the value of creative skills— specifically focusing on the implementation into product design. The numerous dangers of AI threaten the entire creative sector,from music and writing to video and design. 

Artificial intelligence has been developing for decades, debatably since popular science fiction pictures began romanticising the concept (Hermann, 2021). Its introduction seemingly began with a British mathematician called Alan Turing. Known for playing a crucial role in breaking the infamous Enigma Code by building ‘the Bombe’ (Haenlein and Kaplan, 2019), Turing speculated on the power of such machines, writing a seminal paper on the topic of artificial intelligence called ‘Computing Machinery and Intelligence’. This paper introduces discussion and criteria for machine thinking, and how to test computer intelligence. This test is known as ‘the Turing test’. This test was a way to define the difference between human and artificial intelligence and is used still to measure intelligence in machines. In 1952, Arthur Samuel created the first program to play checkers, and later, in 1959, he created the term ‘machine learning’, explaining in a speech about creating a machine that ‘learns’ to play chess. These developments, and the creation of the term ‘artificial intelligence’ by John McCarthy in 1955, lead to the constant development of the industry. Eventually leading to the creation of Joseph Weizenbaum’s ‘ELIZA’ – the first ever chatbot, that could converse with humans. Now for the contemporary issue – AI chatbots have begun to ‘pass’the Turing test. Jones (2024) simulated a randomised, controlled test where humans had to guess whether the conversation they are having is with another human or artificial intelligence. This development is one of many AI advancements that have implications for creativity.

Personal Experience of Experimentation

Recent developments in the industry show an increase of generative AI tools (Haan, 2023), in business & natively into our design tools of choice. This shift has also transformed my own design practice, with tools like Webflow announcing their own AI-powered features (Webflow, 2024). Other major tools such as Figma, Adobe, Wix and Google have followed suit, enhancing efficiency and productivity. Extensions for Visual Studio Code can now generate code for the user, replacing the demand for developers. Over the past few weeks, I included several of these features into my workflow to gain a first-hand account of the uses and limitations. Firstly, it is worth noting that a lot of these are in testing stages. Despite this, plenty worked extremely well, and did enhance productivity. While some, like Wix Studio’s responsive AI, can save significant time by automating tedious layout changes, others, like Photoshop’s image generation, demonstrated limitations such as various artifacts, and a lack anatomical knowledge. It’s important to note that in the example below, I have only used a one-word prompt, without any recommended blending on the area. While both tools are remarkable, it is clear that there is still some way to go. However, Photoshop’s generative AI is trained on a large dataset of images, hosted privately on Adobe’s servers, with more changes being made (Rogez, 2024), allowing it to improve over time. According to Mishkin (2022), image generation tools are trained on pairs of images and captions from public sources, so the AI can understand the links between word and image. Discussions on platforms such as Reddit claim that Adobe’s AI may add unwanted, lateral objects into a scene, though I’m yet to run into this issue.

The test period provided valuable insight into the tool’s capabilities to create, and to improve productivity. It is suggested that using such tools vastly improves efficiency. This is supported by Zhou and Lee (2024), stating that ‘text-to-image generative AI can help individuals produce nearly double the volume of creative artifacts that are also evaluated 50% more favourably by their peers over time’. However, Hong and Curran (2019) argue that the bias attitude toward AI created art is reversed when people learn of the origins. While AI can assist decision-making and improve creative outcomes by applying human datasets, it struggles to replicate critical thinking and emotional depth. Dartnall (2011) questions creativity as a ‘human’ attribute, highlighting its links with emotion. A key limitation of Artificial Intelligence I noticed is the inability of original thought. Marr (2023) compares AI’s generative capabilities to that of human free thought, as both are typically based off data sets (in our case, what we see or hear). Then arguing the key difference between the two is that our ‘data set’ is filtered through emotion, beliefs and experiences that change how we perceive the world around us. Despite that, human’s perception can limit ideas, achieving a state of emotional and mental exhaustion – known as creative block or burnout. I found that restricted use of AI can influence further development of thoughts, joining the two processes. Turner (2014) claims that ‘blending is the origin of ideas’, reasoning that we forge ideas from other ideas. Within this context, AI can be considered a beneficial tool to inspire creativity during a block. In some cases, the use of generative AI challenges my own perception of originality in my work. For example, I was able to produce an entire section of GSAP JavaScript for a portfolio, effectively creating what I described with minimal effort. In this example, the output did not provide the usual sense of accomplishment that manual coding would have – it felt like cheating. In contrast, smaller-scale use such as debugging code avoided substantial frustration, keeping a sense of originality. Therefore, some applications of AI could be argued to be worth the lack of authenticity, as the time saved takes precedence.

The Challenge of Intellectual Property

The World Intellectual Property Organization (WIPO, 2024) defines Intellectual Property as ‘creations of the mind, such as inventions; literary and artistic works; designs; and symbols, names and images used in commerce’. There are two ways in which AI challenges this – firstly, can work generated by artificial intelligence be included in these laws, and secondly, is the use of public source data sets legal, immoral or not liable. Traditionally, views of authorship relate to human nature, the inclusion of computers completely flips this idea. One amusing outlier is a series of legal disputes surrounding the copyright of a monkey taking a selfie (Guadamuz, 2018). This instance debates whether copyright is confined to just humanity. Copyright ownership in regards to generative AI outputs are being discussed across the world with ownership available in the UK, EU & China (Cooley, 2024). In the US, little protection is granted to ‘AI artists’, because it fails the human authorship required. Therefore, artists could create a work across several hours, only to then have no protection if someone were to copy it. This could discourage innovation and cause issues for those investing in it. For instance, ‘Théâtre D'opéra Spatial’ is an AI created [and digitally manipulated] image created by Jason M. Allen, that was entered and won a category of the Colorado State Fair competition (Roose, 2022). Later, the image was refused copyright, due to the significance of the amount of AI used (Wilson, 2023). This has substantial implications for the future of creativity, considering that the use of AI will be imminent. Another example, covering the use of public sources as a data set, is the Getty Images vs Stability AI legal case. In this dispute, Stability AI’s Stable Diffusion is being accused of infringing on the copyright of Getty Images, through its training and reproduction of Getty copyright, including its watermark, which the AI tool has been known to inadvertently generate onto pictures (Davies and Dennis, 2024). According to Coulter (2024) we can determine that this case and generative AI as a whole, presents several new problems in intellectual property and copyright law, that are yet to be discussed.

Originality is an important concept worldwide, across industries. If a work is unoriginal, or plagiarised it is often disregarded, due to the moral implications of ‘stealing’ ideas. Inspiration, on the other hand, is well regarded as a useful stimulation to process new ideas – especially that of creative nature. One can argue that artificial intelligence and humans are both ‘original’ in how we are incentivised to generate new creations. There was always a blurred line at the intersection of originality and inspiration, even more with the additional of AI. Data sets are again key to this discussion, as generative AI relies on existing works, and reproduces them depending on text prompts associated with the images (Caldwell, 2023). Without the requirement for human image data sets, generative AI would not be able to produce a picture, whereas the opposite can be said for humans. Additionally, Caldwell (2023) goes on to argue that humans struggle to distinguish whether a work is made by AI or not. This could easily result in deceitful use of AI to create unauthentic art that replaces or deceives customers, not only presenting questions of the integrity of the art, but also form commercial copyright complications. Yet, a modern artificial intelligence system still does not think. Marr (2023) states that they are ‘always built from blocks carved out of the data that’s used to train it’. The aforementioned sources are required to evolve the machine learning algorithms. If an artificial intelligence can gain sentience, would it then be eligible of equal justices and conditions as humans? With the integration of artificial intelligence into industry, our laws must evolve to coincide with the how the AI is used, and how it evolves – even, to think.

Benefits & Ethical Implications

‘Creativity’ expands across a vast industry – design, music, writing, video and more. Each individual industry has their own set of physical and digital tools to aid in the creation of quality projects. And now, each gather more, with the assistance of AI. For example, Adobe Podcast is an audio processing artificial intelligence that equalises, compresses and removes echo/noise for podcast audio clips (Adobe, 2024). I used this to automatically make voiceovers sound sublime for commercial-grade video. Such tools as these enhance creative output by replicating lengthy, straightforward processes for efficiency, and additionally removing technological limitations for the less fortunate. In a sense, AI has a significant potential role in making creativity accessible. One may conceptually develop a thorough low-budget project, with virtually no limitations to creativity, allowing them a further reach into an industry full of studios and teams. Furthermore, it can benefit those with disabilities - such as tools that can describe images in seconds for those with visual impairment or giving the ability to ask questions about a film or series for those with cognitive disabilities (Aldridge, 2023). This is integral to assist the collaboration of creativity and accessibility, allowing for more people than ever to create. It is my belief that collaboration is essential for an effective future with AI, using it to assist, not replace. In doing so, one can create without obstructions, with tools that support, producing unique outputs that break traditional art forms, expanding creative expression beyond what is currently possible. Using generative AI does have many beneficial implications in design, but there are many ethical concerns that should be considered. Companies may want to substitute creatives with artificial intelligence, as its efficient and inexpensive, but that would invoke a negative public opinion due to the ethics behind AI’s data – see Coca-Cola’s 2024 Christmas advert, or Sketchers’ Vogue December issue advert. Moreover, with the instability of law and copyright surrounding artificial intelligence, the creative output could potentiate disputes that impact the company using it.

Al-kfairy et al. (2024) discusses the conditions of ethics in artificial intelligence, from a multidisciplinary perspective, recommending techniques to future-proof AI - emphasising the importance of human rights and transparency. Essential in the future of this topic, transparency in business ensures that morale is kept high (Dublino, 2024), and employee retention rates are boosted. This shows the importance of being transparent, outside of the AI sector. Tang et al. (2023), explores generative AI & transparency in academic writing, stating that ‘declaring the use of AI in the research process is vital to uphold the integrity and credibility of academic research writing’. This goes for the entirety of the creative industry, with backlash surrounding artificial intelligence everywhere, its integral to announce its use. The discussion of ethics surrounding AI presents questions of the use of datasets, replacing human jobs, false news & scams. Fears regarding the "death of the artist" are unwarranted according to Harper-Nichols and Hutson (2023), as technology has evolved repetitively, like how computers [supposedly] replaced the paintbrush, artists must adapt to new technologies. This is a morally grey area, that is not right, but perhaps necessary. Another ethical challenge is the increase of false news, where people (particularly the elderly) may be deceived by faked images or voices that use AI. This can lead to discrepancies such as broken elections, damage to reputation and legal cases, based off fabricated information. Additionally, it has potential to develop into resentment for creatives that don’t use such tools and impact their work. A quick Google search can find many cases of artists defending their work from accusations of artificial intelligence, that may have already impacted their popularity and commissions.

Furthermore, scammers are developing to utilise the advancements in technology, especially voice generators. Kalyeena Makortoff (2024) writes on the exploitation of videos on social media to replicate voices and scam family out of their money. These various ethical concerns are considerations for rules to be implemented that protect the business and consumer ends, like a digital tag that is attached to all generated files. The idea behind this rule is to protect creativity and ensure that AI is used for a positive impact, without negative consequence, whether morally or corporately.

Artistic Mastery and Value of Creative Skill

The ability to be an artistic master is a skill of great merit. Years of training and practice hone one’s craft to perfection – the combination of physical proficiency, critical analysis and creative experience. Legally, one can be at this level after a Master of Art (MA) university degree, but true mastery can be considered plenty more experienced. For centuries masters of various creative sectors have impacted the evolution of technology, society and culture. Mehta and Dahl (2018) argue that creativity impacts daily life, from mundane tasks to leisure. This shows its importance within society, and how it must stay protected. Art and creativity not only impact our present life, but also key historical developments with iconic names like Aristotle, Da Vinci & Einstein, examples of creative masters that are still highly valued in contemporary society. With the argument of creativity being an exclusively human trait, does the use of artificial intelligence devalue human skill? Generative AI is particularly good at replicating humanity in art, be it detailed painting, comic halftone or studio photography. This can be threatening to experts in creative fields, especially where artificial intelligence replicates artist styles, which could also infringe on the artist’s copyright.

An example of this replicating of artistic mastery is ‘Edmond de Belamy’, an AI portrait of a fictional character in a series of generated family portraits. This portrait was sold at Christie’s for $432,500 in 2018. There are some debates whether this portrait (and AI in general) can be considered art. Christie's (2018) wrote an article discussing the topic, comparing the work to Glenn Brown’s appropriations. The article explores how the piece breaks traditional art forms, considering it as conceptual art, similar to that of Duchamp. This particular exploration of AI was quite early, before [popular] mainstream introduction of image generation technology like Dall-E’s public release in 2021. The creation of this piece, whilst utilizing an intricate, custom algorithm to generate it (rather than a simple word prompt like Chat-GPT), steps on the toes of traditional artists that spend hundreds of hours painting, and thousands more learning, to create something of a comparable level. In particular, the introduction of AI causes complications for the perception of artistic skill. Horton Jr, White and Iyengar (2023) found that art labelled as human-made was seen to be both of more value, and more creative than its AI counterpart. Whilst this shows that human creativity is seen to be of more value, the speed and price of using artificial intelligence is incomparable to hiring an artist. For example, my own practice (in this case, web design) can be entirely replaced by Durable’s AI website builder (Durable, 2024). Admittedly, the output is great, I can understand being enticed by the simplicity and affordability of the transaction. However, the output may be less detailed, customised to the individual or capture the personality of a brand as a handmade one may. If we fuse both techniques, creating hybrid skills and investigate assistive technologies so human & AI may work together as the importance of human creativity is irreplaceable.

What makes the human touch immortal is our ability to understand and employ emotion, culture and context into our work, such as interpreting the tone of voice of a brand. In doing so, a designer may create eccentricities or adopt a subdued visual language that relates to consumers and conveys emotional value. Yet, we are animals, capable of adapting. And humans may be the very best at doing so. Our ability to adapt keeps us ahead, able to evolve in response to challenges galore. So, creativity and art, must adapt.

Conclusion

One thing we can say for certain is the surge of artificial intelligence causes complications, that people have the right to worry about. Creatives, lawmakers and consumers alike must amend to these changes, as they have for centuries. This discussion confirms the instabilities of this industry in an age of AI, from the inability to globally understand laws surrounding the use of AI, to the morality of exploiting these remarkable tools to our advantage. That usage is highlighted to be controversial, with backlash and lawsuits behind the corner of every aspect of AI, it’s easy to see the difficulties in employing it industry-wide. The benefits of artificial intelligence may balance the challenges, like eliminating accessibility limitations, finally allowing for all to experience the joys of creativity. Another benefit is the superior efficiency – removing tedious tasks that exhaust our most precious resource: Time. Of course, there will be restrictions set, laws made, and opinions held. Yet no matter what is said, artificial intelligence is an impressive feat, marking a fundamental milestone in technology that will likely boost further advancements in the coming years, and no doubt aid the next generation of creativity.

Reference List  ⁴⁵

Adobe (2024). Adobe Podcast | AI Audio Recording and editing, All on the Web. [online] podcast.adobe.com. Available at: https://podcast.adobe.com/.
Al-kfairy, M., Mustafa, D., Kshetri, N., Insiew, M. and Alfandi, O. (2024). Ethical Challenges and Solutions of Generative AI: an Interdisciplinary Perspective. Informatics, 11(3), pp.58–58. doi:https://doi.org/10.3390/informatics11030058.
Aldridge, L. (2023). How Artificial Intelligence Can Revolutionise the World of Accessibility | AbilityNet. [online] abilitynet.org.uk. Available at: https://abilitynet.org.uk/news-blogs/how-artificial-intelligence-can-revolutionise-world-accessibility.
Bond, S. (2023). AI-generated Images Are everywhere. Here’s How to Spot Them : Life Kit. [online] NPR. Available at: https://www.npr.org/2023/06/07/1180768459/how-to-identify-ai-generated-deepfake-images.
Caldwell, M. (2023). What Is an ‘Author’?-Copyright Authorship of AI Art through a Philosophical Lens. Houston Law Review, [online] 61(2), pp.411–442. Available at: https://houstonlawreview.org/article/92132-what-is-an-author-copyright-authorship-of-ai-art-through-a-philosophical-lens.
Christie's (2018). A Collaboration between Two Artists One Human One a Machine 9332. [online] Christies. Available at: https://www.christies.com/en/stories/a-collaboration-between-two-artists-one-human-one-a-machine-0cd01f4e232f4279a525a446d60d4cd1.
Coca-Cola (2024). The Holiday Magic Is coming. [online] YouTube. Available at: https://www.youtube.com/watch?v=4RSTupbfGog.
Cooley (2024). Copyright Ownership of Generative AI Outputs Varies around the World // Cooley // Global Law Firm. [online] www.cooley.com. Available at: https://www.cooley.com/news/insight/2024/2024-01-29-copyright-ownership-of-generative-ai-outputs-varies-around-the-world.
Coulter, M. (2024). Aiming for Fairness: an Exploration into Getty Images v. Stability AI and Its Importance in the Landscape of Modern Copyright Law Case Summaries. DePaul Journal of Art, Technology & Intellectual Property Law, 34(1).
Dartnall, T. (2011). Artificial Intelligence and Creativity : an Interdisciplinary Approach. Dordrecht ; London: Springer.
Davies, C.W. and Dennis, G. (2024). Getty Images V Stability AI: the Implications for UK Copyright Law and Licensing. [online] Pinsent Masons. Available at: https://www.pinsentmasons.com/out-law/analysis/getty-images-v-stability-ai-implications-copyright-law-licensing.
Dublino, J. (2024). How Transparency Will Benefit Your Business. [online] business.com. Available at: https://www.business.com/articles/transparency-in-business/.
Durable (2024). Generate Your Website with AI in 30 Seconds. [online] durable.co. Available at: https://durable.co/ai-website-builder.
Freed, S. (2020). AI and Human Thought and Emotion. Boca Raton, Fl: Crc Press, Taylor & Francis Group.
Gajjar, D. and Jeary, L. (2024). Artificial Intelligence and New Technology in Creative Industries. [online] POST. Available at: https://post.parliament.uk/artificial-intelligence-and-new-technology-in-creative-industries/.
Guadamuz, A. (2018). Can the Monkey Selfie Case Teach Us Anything about Copyright law? [online] WIPO Magazine. Available at: https://www.wipo.int/en/web/wipo-magazine/articles/can-the-monkey-selfie-case-teach-us-anything-about-copyright-law-40287 [Accessed 18 Dec. 2024].
Haan, K. (2023). How Businesses Are Using Artificial Intelligence in 2024. [online] Forbes. Available at: https://www.forbes.com/advisor/business/software/ai-in-business/.
Haenlein, M. and Kaplan, A. (2019). A Brief History of Artificial intelligence: on the past, present, and Future of Artificial Intelligence. California Management Review, [online] 61(4), pp.5–14. doi:https://doi.org/10.1177/0008125619864925.
Harper-Nichols, M. and Hutson, J. (2023). Generative AI and Algorithmic Art: Disrupting the Framing of Meaning and Rethinking the Subject-Object Dilemma. Global Journal of Computer Science and Technology: D Neural & Artificial Intelligence, 23(1), pp.59–61.
Hermann, I. (2021). Artificial Intelligence in fiction: between Narratives and Metaphors. AI & Society, [online] 38. doi:https://doi.org/10.1007/s00146-021-01299-6.
Hong, J.-W. and Curran, N.M. (2019). Artificial Intelligence, Artists, and Art: Attitudes toward Artwork Produced by Humans vs. Artificial Intelligence. ACM Transactions on Multimedia Computing, Communications, and Applications, 15(2s), pp.1–16. doi:https://doi.org/10.1145/3326337.
Horton Jr, C.B., White, M.W. and Iyengar, S.S. (2023). Bias against AI Art Can Enhance Perceptions of Human Creativity. Scientific Reports, [online] 13(1), p.19001. Available at: https://www.nature.com/articles/s41598-023-45202-3 [Accessed 10 Nov. 2023].
Jones, C.R. (2024). People Cannot Distinguish GPT-4 from a Human in a Turing Test. [online] Available at: https://arxiv.org/html/2405.08007v1.
Kalyeena Makortoff (2024). Warning Social Media Videos Could Be Exploited by Scammers to Clone Voices. [online] The Guardian. Available at: https://www.theguardian.com/money/2024/sep/18/warning-social-media-videos-exploited-scammers-clone-voices [Accessed 7 Oct. 2024].
Marr, B. (2023). The Intersection of AI and Human Creativity: Can Machines Really Be Creative? [online] Bernard Marr. Available at: https://bernardmarr.com/the-intersection-of-ai-and-human-creativity-can-machines-really-be-creative/.
Mehta, R. and Dahl, D.W. (2018). Creativity: Past, present, and Future. Consumer Psychology Review, 2(1), pp.30–49. doi:https://doi.org/10.1002/arcp.1044.
Metz, R. (2022). AI Won an Art contest, and Artists Are Furious. [online] CNN. Available at: https://edition.cnn.com/2022/09/03/tech/ai-art-fair-winner-controversy/index.html.
Mishkin, P. (2022). DALL·E 2 Preview - Risks and Limitations. [online] GitHub. Available at: https://github.com/openai/dalle-2-preview/blob/main/system-card.md#model.
Patrecia Meliana (2024). Coca-Cola AI Christmas Ad Criticized for Lacking Authenticity. [online] ContentGrip. Available at: https://www.contentgrip.com/coca-colas-ai-christmas-ad/.
Rani, S., Jining, D., Shah, D., Siyanda Xaba and Prabhat Ranjan Singh (2023). Revolutionizing the Creative process: Exploring the Benefits and Challenges of AI-driven Art. Lecture Notes in Networks and Systems, [online] 854(1), pp.234–243. Available at: https://link.springer.com/chapter/10.1007/978-3-031-50151-7_23.
Rogez, B. (2024). Adobe Updates Photoshop: New Generative AI Model for Firefly, More Control and realism, but What about the dataset? [online] 3DVF. Available at: https://3dvf.com/en/adobe-updates-photoshop-new-generative-ai-model-for-firefly-more-control-and-realism-but-what-about-the-dataset/ [Accessed 16 Dec. 2024].
Roose, K. (2022). An A.I.-Generated Picture Won an Art Prize. Artists Aren’t Happy. The New York Times. 2 Sep.
Roser, M. (2022). The Brief History of Artificial intelligence: the World Has Changed Fast – What Might Be next? [online] Our World in Data. Available at: https://ourworldindata.org/brief-history-of-ai.
Smits, J. and Borghuis, T. (2022). Generative AI and Intellectual Property Rights. Law and Artificial Intelligence, [online] 35(1), pp.323–344. Available at: https://link.springer.com/chapter/10.1007/978-94-6265-523-2_17#keywords [Accessed 8 Oct. 2024].
Surnit, A. (2024). Skechers Faces Backlash over AI-Generated Ad in Vogue’s December Issue. [online] Designrush.com. Available at: https://www.designrush.com/news/skechers-faces-backlash-over-ai-generated-ad-in-vogue-december-issue [Accessed 21 Dec. 2024].
Tableau (2023). What Is the History of Artificial Intelligence (AI)? [online] Tableau. Available at: https://www.tableau.com/data-insights/ai/history.
Tang, A., Li, K., Kin On Kwok, Cao, L., Luong, S. and Wilson W.S. Tam (2023). The Importance of transparency: Declaring the Use of Generative Artificial Intelligence in Academic Writing. Journal of Nursing Scholarship, 56(2). doi:https://doi.org/10.1111/jnu.12938.
Turing, A.M. (1950). Computing Machinery and Intelligence. Oxford University Press.Turner, M. (2014). The Origin of Ideas: blending, creativity, and the Human Spark. Oxford ; New York: Oxford University Press.
Vincent, J. (2023). Getty Images Sues AI Art Generator Stable Diffusion in the US for Copyright Infringement. [online] The Verge. Available at: https://www.theverge.com/2023/2/6/23587393/ai-art-copyright-lawsuit-getty-images-stable-diffusion.
Weatherbed, J. (2024). Adobe Demos Illustrator Tools That Rotate Vectors and Finish Sketches. [online] The Verge. Available at: https://www.theverge.com/2024/10/17/24272971/adobe-illustrator-sneaks-experimental-tech-demo-rotate-vector [Accessed 19 Oct. 2024].
Webflow (2024). Webflow Conf 2024 Keynote. [online] YouTube. Available at: https://www.youtube.com/watch?v=u7zm19YgQBA [Accessed 11 Nov. 2024].
Wilson, S.V. (2023). Second Request for Reconsideration for Refusal to Register Théâtre D’opéra Spatial.WIPO (2024). What Is Intellectual Property? [online] World Intellectual Property Organization. Available at: https://www.wipo.int/about-ip/en/.Zhou,
E. and Lee, D. (2024). Generative Artificial intelligence, Human creativity, and Art. PNAS Nexus, 3(3). doi:https://doi.org/10.1093/pnasnexus/pgae052.