AI-Generated Art

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Evolution of AI-generated Art


AI in Literature

Literature has been revolutionized by technological advancements that have changed the way humans perceive, interpret, and write. Many writers, authors, and producers all around the world are embracing AI to transform data into captivating stories in a multitude of different ways. Poetry, storytelling, and filmmaking are just a few examples of traditional literary genres.

Benefits of AI in Literature

The role AI plays in literature provides many benefits including, but are not limited to, increased efficiency, time savings, simplicity, cost savings, and better stories.

Increases efficiency: AI can assist writers by enabling them to instantly generate thousands of words and visuals on command with the click of a button. They will always have access to a highly intelligent poet on any given day at any given moment, allowing them to produce a lot more content in a short period of time. Instead of searching for inspiration, writers can quickly and easily generate ideas and translate that into high-quality content with the help of AI. [1]

Saves time: There are many people who want to tell stories, but are unable to devote all their time to writing content. By using AI to help automate tasks that humans can do, writers have more free time to focus on other important aspects such as research and development. [2]

Enhances simplicity: Texts can be automatically modified by AI to make it easier for people to understand and interpret, especially those with cognitive disabilities. Although the way computers compose poems or stories seems ambiguous or nonsensical, writers can simply ask AI to construct a straightforward computed-generated poem and/or story. [3]

Introduces cost savings: Sometimes writers lack the ability to spark new content ideas or design compelling illustrations that convey powerful messages. In situations like this, writers often hire subject-matter experts to help do it for them, resulting in expensive labour in the long run. However, employing AI is known to be very cost-effective due to its ability to identify and correct areas of inefficiencies as well as reduce labour costs. [4]

Produces better stories: A common hurdle to human writers is creating content on topics that are unknown, ultimately leading to writers roadblock. For instance, human poetry is often limited to the personal experiences of the author, so conveying feelings and thoughts on topics outside of those experiences can be challenging. In addition, when it comes to creating stories, many people have ideas floating in their heads for years, but never had the ability to produce the art that goes along with it. Because AI can write on an endless number of topics, it can help to inspire creativity and form unique storylines that consist of generating character descriptions, plot lines, and visuals. [5]

Tools and Applications


Verse by Verse [6]: Google’s AI-powered mused is a tool used to compose poetry inspired by classic American poets. Users will first be prompt to select up to three poets for it to emulate, such as Robert Frost, Emily Dickinson, and Walt Whitman. The AI will then ask users to design the structure of their poem, including its poet form, syllable count, and rhyme scheme. Once these selections are made, the tool will ask users to compose their first line of verse and the AI will take over and provide suggestions for the following verses to complete the poem. The purpose of this tool was created to inspire poetic writers. Verse by Verse will never force users to follow its suggestions, but rather it encourages them to make changes and improvements as they see fit.

Deep-speare [7]: A joint neural model of poetic language called Deep-speare produces sonnet-like stanzas that are reminiscent of Shakespearean pieces. A sonnet is a short lyric poem. The AI poet employs three natural-language-processing models: One assesses word probability by selecting each word, a second checks the rhythm of each line of poetry, and a third verifies that each line conforms to the rhyme scheme. Deep-speare has the ability to compose poems that are based on a particular theme, with the models word selections constrained to that specific theme. Because AI writes its poetry to resemble Shakespearean work, many people have found it difficult to distinguish between the two.


AI plays a vital role in immersing audiences in new levels of engagement and encouraging writers to create new forms of dynamic, interactive stories.

Star Maker: World’s first bot-generated graphic novel to win a fine arts competition

Midjourney [8]: In August 2022, the world’s first bot-generated graphic novel, Star Maker, won a fine arts competition against human artists by leveraging the AI program Midjourney. Author Kevin Hess used this tool to create and design graphic images from text descriptions. Star Maker was originally published in 1937 by Olaf Stapledon. Hess reported that this was his favourite novel of all time, so he decided to turn it into a graphic novel. He took the opportunity to create an epic story to an aged novel that is now off-copyright. His graphic novel became the first fully illustrated novel in human history where all illustrations were created by an AI. The novel consists of 706 fully illustrated pages and it took only 100 hours to construct from start to finish. The visual edition of Star Maker demonstrates a critical example of how powerful AI is in elevating artistic capabilities. While the author viewed his win as a memorable milestone, it has sparked a storm of conflicting views with many artists upset and fearful of being replaced by bots.

Another example of a graphic novel that utilized Midjourney to develop its illustrations is the making of Lungflower [9]. Lungflower is the first AI drawn graphic novel to publish in June 2022 by science fiction writer Brian Martinez. The novel is an emotional, one-of-a-kind horror experience consisting of eerie, wild, and vivid artwork.


Today, AI is used in all stages of film production from writing and analyzing scripts, predicting the success of a film, selecting actors, promoting movies, and producing movies. With several people starting to embrace the advantages of technology, AI has played a crucial role in helping creators understand what the audience desires as well as new ways to produce and present content. As a result, AI technology enables these creators to stitch together an engaging and exciting narrative.

For example, German tech entrepreneur Fabien Stelzer is making an entire movie using DALL·E 2, Midjourney, and GPT-3 to generate the films imagery, audio, and script. Stelzer has zero experience and background in film production and is relying solely on AI tools to produce his short sci-film ‘Salt’, which is currently in the making.[10]

Image generated from Arturo Tedesch's initial text description: ‘a b/w scene of a man and a woman seated on a bench, in New York, Queensboro bridge in the background, foggy atmosphere’

DALL·E [11] : The generative AI system DALL·E, used to generate digital images from natural language descriptions, has unlocked new possibilities in Arturo Tedesch’s recent work of film storyboarding. Italian artist Tedeshi decided to convert storyboard texts into striking visuals inspired by famous movies like ‘Pulp Fiction’ and ‘Manhattan’. Using this compelling technology, he created his first image with text that described a scene in the 1979 film ‘Manhattan’. In addition to his initial text description, ‘A b/w scene of a man and a woman seated on a bench, in New York, Queensboro bridge in the background, foggy atmosphere’, he uploaded a few pictures of the Queensboro bridge to better represent the scene. Based on his inputs, the AI-generated image was created in 15 seconds. His latest collaboration with technology signifies how AI can be easily accessible, powerful, and efficient in visualizing ideas. According to Tedeshi, “the art of storyboarding deserves attention not only for the graphic quality, technique, or quick trait, but as a creative bridge between screenplay and film or, if you like, as a link between language and images”.

Cinelytics [12]: A SaaS platform called Cinelytic combines AI and cloud-based technology to help professionals in the entertainment industry make quicker and more informed decisions about the packaging, funding, production, distribution, and marketing of content. As an example, the Warner Brothers using this engine to improve the script of films, predict expected earnings, and gain deeper insights into how a particular movie will perform once it gets released to the public [13].

It's No Game co-written by AI-writer Benjamin

Benjamin: Benjamin is a notable AI-writer, widely referred to as a long short-term memory (LSTM) recurrent neural network [14]. The LSTM algorithm is very effective in predicting entire paragraphs rather than a select few words and provides originality when it comes to generating whole sentences. Benjamin was trained by creative writer Ross Goodwin and was fed with a range of sources found on the internet, including Shakespeare, Golden Age movies, the scripts of Hasselhoff films, and a dictionary of choreographic instructions [15]. In 2017, a short sci-fi film called ‘It’s No Game’, starring David Hasselhoff, was co-written by the AI model Benjamin.

Text-generator Limitations

Generative Pre-trained Transformer 3 (GPT-3): GPT-3 is an autoregressive language model that generates human-like text. It is commonly known as a text generator that processes a vast amount of content, including books, online conversations, Wikipedia, and scientific papers, in order to write on command. GPT-3 is available through OpenAI’s API and is trained to generate any type of text. It has been widely used to compose poetry, articles, narratives, news reports, and dialogues. The model leverages deep learning to respond to a users initial text input and creates the most likely output to complete the prompt. While GPT-3 is the largest and most powerful trained model, it has several limitations that constrain its capabilities. [16]

Model is not constantly learning: Because GPT-3 has been pre-trained, it lacks an ongoing long-term memory that continuously learns from every interaction. Additionally, GPT-3 shares the same drawbacks as all neural networks in that it is unable to analyze and explain why specific inputs lead to certain outputs. In other words, it is incapable of remembering previous inputs or outputs that it has seen, therefore lacking any form of memory. [17]

Model has limited input and output size: Users inputting text as prompt for the output are limited to a few sentences, in which GPT-3 can only take in and output approximately 1,500 words. In addition to the model restricting users to a certain amount of text, it still suffers from slow performance when generating results based on inputs. [18]

Model has machine learning biases: GPT-3 is known to have gender, racial, and religious bias by OpenAI, posing a great danger toward marginalized populations. Such harms include, but are not limited to, discrimination, structural inequalities, and unfair treatment. Because the model was trained from information discovered on the internet, such as Twitter tweets, it generates several biases that humans exhibit in their online conversations, which are typically unfiltered [19]. These biases introduce a large concern that GPT-3 will create false stories and deceitful outputs, resulting in misled user perceptions. Common examples of biases include the following: black people described in negative terms, white people described in positive terms, Muslims linked to violence, and men not being connected to occupations in nursing or receptionist work [20].

GPT-3 is far from perfect with developers facing many challenges in identifying the optimal solution to overcome societal biases that the model exhibits. Such challenges relate to decisions around what topics to exclude, what words are considered ‘bad’, as well as difficulties in locating unwanted bias like racial slurs or subtle associations [21]. Additionally, if language models, like GPT-3, were blinded, there is a possible risk that results may return invalid and unreliable. Consequently, if a user asked ‘does racism exist in this world?’ and the model had never been exposed to this topic, the answer could be factually incorrect and state ‘no’.

AI in Visual Arts


AI in Performing Arts


AI in Beauty

Looking at fashion, you could see how it was dominated by creative minds who have thought out of the box to think of new trends. This creativity is slowly becoming obsolete as AI has now been able to take over manufacturing jobs of many at a cheaper cost while also working on the frontend and AI can now detect new trends with demand being one step ahead of what’s going to be in style next. The makeup industry has also made strides in introducing AI these last few years. The application of makeup isn’t even required to see how the product will look on your skin. With all these new screens being added into stores and applications on our cellular devices, beauty is changing how you look virtually to help make you decide if you want the product.[22]

Benefits of AI in Beauty

Personalization: The AI technology offers shoppers a personalized experience, making shopping more targeted to them and easier. This is accomplished by using shade matching try-on so consumers can preview the product on themselves before purchasing or having to go into the physical store.

Brand Loyalty: Through targeting customers and providing personalized solutions, consumers spend more time connecting with a brand, this can be done online or in-store. The ability to have these virtual interactions with skincare products allows customers to have more positive experiences, coming from the impactful results of having personalized options.

Customer experience interactions: The introduction of chatbots has transformed the way customers interact with brands. They help brands and retailers in managing everything from tracking sales to recommending products to enhance customer experiences.

Improved inventory management: AI uses predictive analytics to help fashion retailers understand customer behaviour and plan inventory accordingly. It also allows businesses to see the outflow of certain styles to plan accurate inventory for products that are in style.

Breakdown of AI in Fashion

AI is now used in all steps of fashion, beginning with the initial creation of the product moving its way to visualizing how the product looks on consumers before they make a purchase. AI now works on creating new trends by analyzing past trends and using that information to create new designs or improve current products. [23]

Examples: iLUK is an AI-based personal stylist, using computer vision-based and 3d reconstruction technology to make personal styling based on technology possible. It is designed as a pod that will be placed at retail outlets.

Van Heusen created a similar concept as it implements its virtual mirror in retail environments to let users see how outfits would look on them by scanning the item's barcode. Once scanned, customers can stand in front of the mirror as the virtual garment are projected onto the screen to match the customers body. This is just one feature; the video below will show all concepts the style studio is programmed to do.

Breakdown of AI in Makeup

The cosmetic industry has focused on using AI algorithms to detect the face through a camera by focal points and map the face. By getting this scan of a customers face it allows them to apply the cosmetics on their faces virtual to see how tones work against their skin and get a better personalization for makeup choices offered by brands. [24]

Examples: The company Perfect corp. unveiled their AI-powered makeup tutorial platform last year. The launch provided a new digital makeup tutorial with step-by-step lessons using AI. YouCam tutorial is the makeup tool that virtually educates consumers on correct makeup application techniques. [25]

AI in Social Media


Critisms and Considerations


Final Thoughts

Is AI-generated art considered real art?


Future Senario



Lauren Dar Kristina Nguyen Clara Wong Aleena Zaidi Jasdeep Hari Anthony Wallace
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada


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