Difference between revisions of "Artificial Intelligence-Generated Art"

Revision as of 00:04, 10 February 2023

Artificial-intelligence-generated art, or AI art, is any piece of art generated through artificial intelligence. AI art is constructed using machine-learning algorithms, which are self-learning. ^[1] These algorithms incorporate elements from digitally available works, including but not limited to images, music, and videos.^[2][3] A user will provide specific parameters that train the algorithms to look at a certain selection of works. These parameters, or prompts, are mainly provided to the algorithms by the user in the form of phrases (text), images, or code. ^[4] The specific method through which the image is produced depends on the decoder that the algorithm is trained on. For text prompts, the algorithm can put the text through an autoregressive or diffusion prior. The autoregressive or diffusion prior then produces an image embedding, which is then fed to a diffusion decoder. The decoder produces the final image based on the image embedding.^[5][6] For image prompts, the image can also be fed to a diffusion decoder to produce the final image.^[7] Neural networks can also be trained on the style of particular artist and used to produce images or videos that emulate that style. The process by which the neural networks achieve this emulation is called neural style transfer. ^[8] For example, the platform DALL-E is trained on an OpenAI model called the Contrastic Language-Image Pre-training (CLIP). CLIP serves as a bridge between text and images.^[9]

Some of the more well-known AI art platforms include DeepDream, DALL-E, WOMBO Dream, GauGAN2, ml5.js, Midjourney, Stable Diffusion, Artbreeder, Flow Machines, and Art Recognition.^[10] Some of these platforms require a subscription to use, while others are free. ^[11][12]

Some platforms encourage users to explore the use of unexpected or creative phrases or combinations of phrases. On the website DALL-E, the main page provides example prompts to stimulate the user’s imagination, with phrases like, “An astronaut,” “riding a horse”, “as a pencil drawing”. With simple tutorials like these, users can recognize that they can input a subject for the art as well as style of the art. ^[13]

History

One of the earliest forms of systems-generated visual art was Jean Tinguely’s “painting machines”. These machines were kinetic sculptures displayed at the Cybernetic Serendipity exhibition, which was held at the London’s Institute of Contemporary Art in 1968. Visitors could choose the color and position of a pen attached to the machine, as well as choose how long the machine should operate. The machine then produced an abstract artwork based on these parameters.^[14]

Another development in systems-generated art came about with computer-generated visual art, which arose in the 1950s and 1960s. Computer-generated art during this time period was limited to creating simple shapes and patterns using basic algorithms. One of the first uses of such algorithms was the creation of “matrix multiplications,” a series of visual art pieces by Frieder Nake. Nake started with a square matrix filled with numbers. The algorithm Nake used likely included an automated process to multiply these numbers. Each number had a form and color assigned to them, and then the shapes were placed on a raster graphic and printed on paper. ^[15][16]

In the 1970s and 1980s the development of computer-aided design (CAD) systems allowed computers to create art involving three-dimensional shapes and more complex subjects, including abstract art. ^[17]

In 1973, artist Harold Cohen developed an algorithm called AARON, which allowed a computer to draw in a style that mimicked the irregularity of human freehand drawing. Specifically, the algorithm was trained on Cohen’s own painting style. Cohen fed commands to the machine that allowed it to make its own artistic decisions, making it an autonomous picture creator. The machine’s value was that it had one of the first algorithms that could generate forms the creator did not anticipate and could create an infinite number of images in that one style. .^[18]

There are other developments that facilitated the creation of AI generators as we know it today. These developments include the creation of open-source projects, the creation and increasing accessibility of public sets of data, computer vision programs, and generative adversial networks (GANs). Currently, most of the AI-art generating platforms use GANs. These networks usually involve two systems: one generates random products based on the input, while other judges these products. For example, a visual art generator will take images from a data set and produce another image similar to the ones it receives. The second system judges the images generated and determines which ones best align with the data set. This process repeats until the second system is fooled into believing that the products are the same as the ones from the data set. ^[19][20][21]

The first known uses of GANs to produce artwork were by technology caompnies. Some exmaples included Google’s creation TensorFlow and Meta’s creation Torch.^[22]

One of the first GAN-made artworks that gained attention on the art scene was the portrait Portrait de Edmond de Belamy made by Obvious, a trio of artists. The trio was composed of Paris-based artists Hugo Caselles-Dupré, Pierre Fautrel, and Gauthier Vernier. The artists trained the algorithm on 15,000 portraits that were painted between the 14th to 20th century. The artists drew these portraits from WikiArt and credited the algorithm as the creator. This was the first piece generated by an AI that was put up and sold at an auction; in 2018, the piece was sold at Christie’s for $432,000.^[23][24]

In 2018, François Pachet and the label Flow Records released Hello World, the first music album composed with AI.^[25] The following artists collaborated with Pachet to create the album: Virgille Allien, Alys, Joseph André, Cyril Baleton, Laurent Bardainne, Camille Bertault, Florianne Bonani, Lionel Capouillez, Benoit Carré (aka SKYGGE), Raphael Chassin, Benjamin Chollet, Médéric Collignon, C Duncan, Fred Decès, Christian Dessart, Freddy Garcia, Renaud Gieu, Mariama Jalloh, JATA, Kiesza, Kyrie Kristmanson, Jérôme Lavaud, Michael Lovett, Gilles Martin, Ana Millet, Rachid Mir, Napkey, Adrien Pallot, Jérémy Pasquier, The Pirouettes, Marie-Jeanne Serrero, Stromae, The Bionix, Twenty9, Ash Workman, Sarah Yu Zeebroek. This collaboration was the result of a project exploring the possibility of algorithms emulating different musical “styles”. Although the project was initially launched to conduct research, it later produced Daddy’s Car, which was released in 2016. This song was created with the aim of emulating the style of the The Beatles. Afterwards, more artists then joined the project. ^[26]

In 2019, harpsichordist Mahan Esfahani, mathematician Marcus du Sautoy, and composer Robert Thomas collaborated to produce a musical piece based on Bach’s compositions. The three used an algorithm created by Parag K. Mital to produce a mashup of Bach’s compositions and a new piece created by the algorithm. Esfahani played the mix at a concert at the Barbican in London on March 9, 2019. The concert audience was challenged to differentiate and find the transitions between the new piece and Bach’s original compositions.^[27]

Uses and Benefits of AI-generated Art

AI can be used to produce a unique image that has never been created before or illustrate a concept that would otherwise be expensive to create through traditional art.^[28] For example, Generative Adversial Networks (GANs) can be used to generate new fonts, human faces, new cartoon and anime characters, sketches, and more. The algorithms can also generate realistic or hyper-realistic art, which is useful when the desired creation is difficult to produce in real life. An example of some products that are difficult to produce in reality, but are possible with AI, are movie scenes involving superpowers. ^[29]

Many of these platforms are available for use by the public. Because many algorithms are able to produce art based on phrases, it has made the creation of art more accessible to novice artists. ^[30]

Artists can also

Popularity boom TikTok

Limitations of AI-generated Art

Given that the algorithm is dependent on data to produce these images, if the AI model has only been trained on a limited amount of data, the model can potentially produce the same image repeatedly. ^[31]

Additionally, as AI image generators are a relatively new tool, the algorithms still struggle with creating hyperrealistic products that accurately represent living beings. For example, many algorithms are unable to render hands that look ‘human.’^[32]

Ethical Dilemmas

There are ethical dilemmas arising from the questions of ownership and the morality of the sources from which the algorithms pull their data and over the finished product. There are also concerns regarding how responsibility and credit should be given to artists who use AI. Additionally, although many of the platforms which algorithms are hosted on have copyright or safety guidelines, the effectiveness of these platforms at vetting the finished products and ensuring that all the content follow copyright guidelines is unknown.

Copyright Infringement

Many artists expressed concern about the theft of their artistic trademark. Some artists have even noted that visual art produced by Midjourney and Stable Diffusion have their tags or signatures on them.

Some platforms have guidelines that explicitly say that users should only share photos and videos that the user owns or has the right to share. For example, Deep Dream Generator says that users should “post authentic content” and not post “anything you’ve copied or collected…that you don’t have the right to post.” ^[33]

The terms and conditions of the platforms WOMBO and WOMBO Dream state that they do not allow content that infringes copyright. However, they also recognize that there are exceptions to copyright infringement that allow the use of copyrighted content without authorization. In certain cases, these exceptions are provided by under the fair use doctrine in the United States. If users believe that their copyrighted content is being infringed on, they may submit a claim to the company. ^[34][35]

Automation

There are ongoing debates about whether these algorithms put creatives at risk. In other words, artists are concerned that the process of creation is being automated, which would take away their means of making a living. ^[36]

On one hand,

On the other hand, many say that the concern about automation is an ‘alarmist’ narrative and should not be a concern at all. Reasoning for this justification include

“art is dead”

^[37]

Data Scrapping

Data scrapping is also a concern. In regards to AI-generated art, companies that host these algorithms may use data scrapping or extraction tools to provide images to train the algorithms.^[38] However, the sources from which the companies take the art can include copyrighted content or even sensitive materials, such as private medical or police records. These materials are often taken without the creators’ knowledge or consent. For these creators or the people whose records are being used, it is difficult to get any recourse to remove the materials from the data set. ^[39][40]

NVIDIA, the parent company of the generator GauGAN2, expects that users will not use any data scrapping or extraction tool in posting, submission, creation, or transferring any content to and from the platform.^[41]

Harassment and Discrimination

Many algorithm platforms have community guidelines or usage policies which state their anti-harrassment and discriminatory policies. This includes, but is not limited to, using data or producing content that relates to sexual intercourse, sexual content involving minors, violence or discrimination aimed towards a certain group, unlawful activities, deception, and threats to personal safety. ^{[42] [43][44]}

Kim Jung-gi Case

to be written

Responses to Ethical Issues

Previous Court Rulings

In previous rulings, courts such as the have determined that AI cannot hold copyright. A review from the US Copyright Office ruled that a piece, titled “A Recent Entrance to Paradise”, generated by an algorithm called “Creativity Machine”, could not be registered as a copyrighted work. The review discussed what the phrase “original work of authorship” means and concluded that the piece lacked “human authorship”, which is needed for protection under copyright. In terms of AI-generated art, this can mean that the art produced by these algorithms belong to the public domain.^[45][46]

This is especially concerning for artists who are worried about algorithms that can copy the style of a human artist. This issue is in line with the growing concern of automated jobs. Some artists have used AI-image generators to produce images of Mickey Mouse and other copyrighted characters in order to bring the issue of legality and copyright into the forefront of the conversation around AI art.^[47]

Ongoing Court Cases regarding Copyright Infringement

In the week of Jan 15, Getty Images filed a claim against Stability AI, creator of the algorithm Stable Diffusion. In its statement, Getty Images says that Stability AI infringed intellectual property rights, including by using content owned or represented by the former without seeking the appropriate license to use such content. The former also states that the content included, but is not limited to, millions of images and the associated metadata.^[48]

Resistance to Data Scrapping

In response to concerns that algorithms may be using creative content without the consent or knowledge of the artists, a group of artists named Spawning created a website named, “Have I Been Trained?” On this website, artists can search the LAION-5B data set by text or by uploading an image to see if their content is being used.^[49]

Added by peer on 1/26: 2: There are several different companies that specialize in AI generated art and the most popular of these is an app called Lensa. Lensa has taken social media by storm, creating custom portraits based on ten images that the user inputs. Lensa used an AI technique called Stable Diffusion to generate the portraits, but there has been controvery as several artists claim that their work has been stolen from the algorithm. ^[50]

Added: Art professors have begun to worry about the prevalence of art-generating algorithms, particularly pertaining to its simplicity of use.^[51] Users can create abstract and sophisticated images, which has teachers worried their students won't develop necessary skills for work in art.

Artists have brought a lawsuit against three major AI Art companies, claiming the companies illegally used the artwork and illustrations of artists to train their algorithms. ^[52]

A Canadian illustrator has discovered that an AI Art algorithm used his art without his consent. ^[53]

Discussion from Peer

The article is around 1220 words, which definitely hits the word requirement for the draft portion of this assignment. The article is about Artificial intelligence (AI) generated art. The opening paragraph of this article is strong. Comprising of 4 paragraphs, each paragraph is densely filled with information that not only teaches readers about what AI-generated art is but also how it works. For example, the author explains the different methods for how images are produced through an algorithmic process that uses an autoregressive or diffusion prior to text-based prompts. For image prompts, the author explains the process of how the algorithm can use a diffusion decoder. In addition to introducing the topic and explaining how information technology works on the surface level, the author also briefly talks about the different apps on the market that use these technologies and the affordances that go with each application. Overall, the opening paragraph is very strong when it comes to summarizing the issue without going too in-depth about it. The body of the article is also separated into multiple sub-sections that go with each section. For example, the subsections “Copyright Infringement”, “Data Scrapping”, “Harassment and Discrimination”, and the “Kim Jung-gi Case” all go with the section called “Ethical Dilemmas.” The subsections “Previous Court Rulings”, “Ongoing Court Cases regarding Copyright Infringement”, and “Resistance to Data Scrapping” all go with the section called “Responses to Ethical Issues.” Lastly, the author has over 30 references to reliable sources. I think structure-wise, the author did a really good job in staying true to the theme of “ethical issues” surrounding their chosen information technology. They did not ramble or go off track and got straight to the point of the ethical dilemmas and the responses to those ethical dilemmas.

The issue at stake is very clear to me. AI-generated art has been booming in popularity lately and has been very prevalent across many social media platforms. The ethical issues surrounding AI-generated art can be very serious and the article does a good job of bringing the issues to light and highlighting why people should care about it. Copyright infringement is a common issue among human creators, but when AI is involved, it is often difficult to really know when the AI will step into the zones of copyrighted work. As stated in the article, a previous court hearing ruled that an AI-generated piece of artwork “lacked ‘human authorship’, which is needed for protection under copyright.” This issue is especially concerning because we truly never when the AI will accidentally draw from the works of existing art pieces. The issue of automated jobs and how AI-generated art can overtake real artists are also at stake. The article also able to help me understand the issue of privacy surrounding artificial intelligence. AI can sometimes draw personal information online without consent, such as medical and police records. This creates a huge privacy concern for literally anyone who uses the internet.

Lastly, as for objective reporting, I think the author does a good job of not stating any personal opinions and staying true to just facts pulled from reliable sources. The article does mainly talk about the negative implications of AI-generated art. While the issue itself is definitely a serious topic of discussion, I think the author can add a section at the beginning where they talk about how AI-generated art can be good, and then start talking about the negative consequences. I think they can still mainly focus on the negative implications, but I think briefly mentioning the positives won’t hurt. Also, they can mention the recent popularity boom and how TikTok even has built-in filters for people to do self-portraits. But going back to objective reporting, I believe that the author does have a neutral point of view all throughout the article and does not state any personal opinions. All of their arguments are based on facts pulled from a variety of sources. When talking about lawsuits, the author mentions both sides of the argument.

1. ↑ Hencz, Adam. “AI Art and How Machines Have Expanded Human Creativity.” Artland Magazine, 8 Apr. 2022, magazine.artland.com/ai-art/.
2. ↑ Feldman, Ella. “Are A.I. Image Generators Violating Copyright Laws?” Smithsonian Magazine, 24 Jan. 2023, www.smithsonianmag.com/smart-news/are-ai-image-generators-stealing-from-artists-180981488/.
3. ↑ Clarke, Laurie. “When AI Can Make Art – What Does It Mean for Creativity?” The Guardian, 12 Nov. 2022, www.theguardian.com/technology/2022/nov/12/when-ai-can-make-art-what-does-it-mean-for-creativity-dall-e-midjourney.
4. ↑ Feldman, Ella. “Are A.I. Image Generators Violating Copyright Laws?” Smithsonian Magazine, 24 Jan. 2023, www.smithsonianmag.com/smart-news/are-ai-image-generators-stealing-from-artists-180981488/.
5. ↑ Kelly, Kevin. “Picture Limitless Creativity at Your Fingertips.” Wired, 17 Nov. 2022, www.wired.com/story/picture-limitless-creativity-ai-image-generators/.
6. ↑ Ramesh, Aditya, et al. “Hierarchical Text-Conditional Image Generation with CLIP Latents.” Computer Vision and Pattern Recognition, 13 Apr. 2022. ArXiv. Cornell University.
7. ↑ Ramesh, Aditya, et al. “Hierarchical Text-Conditional Image Generation with CLIP Latents.” Computer Vision and Pattern Recognition, 13 Apr. 2022. ArXiv. Cornell University.
8. ↑ Kelly, Kevin. “Picture Limitless Creativity at Your Fingertips.” Wired, 17 Nov. 2022, www.wired.com/story/picture-limitless-creativity-ai-image-generators/.
9. ↑ Singh, Aditya. “How Does DALL·E 2 Work?” Augmented Startups, 31 May 2022, medium.com/augmented-startups/how-does-dall-e-2-work-e6d492a2667f.
10. ↑ Hencz, Adam. “AI Art and How Machines Have Expanded Human Creativity.” Artland Magazine, 8 Apr. 2022, magazine.artland.com/ai-art/.
11. ↑ “Terms of Service.” www.wombo.ai, 1 Aug. 2021, www.wombo.ai/terms. Accessed 27 Jan. 2023.
12. ↑ Kelly, Kevin. “Picture Limitless Creativity at Your Fingertips.” Wired, 17 Nov. 2022, www.wired.com/story/picture-limitless-creativity-ai-image-generators/.
13. ↑ OpenAI. “DALL·E 2.” OpenAI, 2022, openai.com/dall-e-2/.
14. ↑ Rea, Naomi. “How Did A.I. Art Evolve? Here’s a 5,000-Year Timeline of Artists Employing Artificial Intelligence, from the Ancient Inca to Modern-Day GANs.” Artnet News, 16 Dec. 2021, news.artnet.com/art-world/artificial-intelligence-art-history-2045520.
15. ↑ Kundu, Rohit. “AI-Generated Art: From Text to Images & beyond [Examples].” Www.v7labs.com, 2 Feb. 2023, www.v7labs.com/blog/ai-generated-art#:~:text=AI%2Dgenerated%20art%20also%20began. Accessed 9 Feb. 2023.
16. ↑ Nake, Frieder. “No Title,” Tate, 2013, www.tate.org.uk/art/artworks/nake-matrix-multiplications-128667/2. Series: “matrix multiplications.”
17. ↑ Kundu, Rohit. “AI-Generated Art: From Text to Images & beyond [Examples].” Www.v7labs.com, 2 Feb. 2023, www.v7labs.com/blog/ai-generated-art#:~:text=AI%2Dgenerated%20art%20also%20began. Accessed 9 Feb. 2023.
18. ↑ Rea, Naomi. “How Did A.I. Art Evolve? Here’s a 5,000-Year Timeline of Artists Employing Artificial Intelligence, from the Ancient Inca to Modern-Day GANs.” Artnet News, 16 Dec. 2021, news.artnet.com/art-world/artificial-intelligence-art-history-2045520.
19. ↑ Kundu, Rohit. “AI-Generated Art: From Text to Images & beyond [Examples].” Www.v7labs.com, 2 Feb. 2023, www.v7labs.com/blog/ai-generated-art#:~:text=AI%2Dgenerated%20art%20also%20began. Accessed 9 Feb. 2023.
20. ↑ Gonsalves, Robert A. “GANshare: Creating and Curating Art with AI for Fun and Profit.” Medium, 23 Oct. 2021, towardsdatascience.com/ganshare-creating-and-curating-art-with-ai-for-fun-and-profit-1b3b4dcd7376. Accessed 9 Feb. 2023.
21. ↑ “GAN Art Generated by AI.” Www.wichita.edu, Wichita State University, www.wichita.edu/academics/engineering/aerospace/gafl/gan_generated_art.php. Accessed 9 Feb. 2023.
22. ↑ Rea, Naomi. “How Did A.I. Art Evolve? Here’s a 5,000-Year Timeline of Artists Employing Artificial Intelligence, from the Ancient Inca to Modern-Day GANs.” Artnet News, 16 Dec. 2021, news.artnet.com/art-world/artificial-intelligence-art-history-2045520.
23. ↑ Rea, Naomi. “How Did A.I. Art Evolve? Here’s a 5,000-Year Timeline of Artists Employing Artificial Intelligence, from the Ancient Inca to Modern-Day GANs.” Artnet News, 16 Dec. 2021, news.artnet.com/art-world/artificial-intelligence-art-history-2045520.
24. ↑ Elgammal, Ahmed. “AI Is Blurring the Definition of Artist.” American Scientist, 14 June 2019, www.americanscientist.org/article/ai-is-blurring-the-definition-of-artist.
25. ↑ “François Pachet - Director of Spotify Creator Technology Research Lab.” Francoispachet.fr, www.francoispachet.fr/. Accessed 9 Feb. 2023.
26. ↑ SKYGGE. “Hello World Album the First Album Composed with an Artificial Intelligence.” SKYGGE, www.helloworldalbum.net/.
27. ↑ Ings, Simon. “An AI Has Created Music Based on Bach – but Will an Audience Notice? | New Scientist.” Webcache.googleusercontent.com, 27 Feb. 2019, webcache.googleusercontent.com/search?q=cache:www.newscientist.com/article/mg24132190-800-an-ai-has-created-music-based-on-bach-but-will-an-audience-notice/. Accessed 9 Feb. 2023.
28. ↑ Kelly, Kevin. “Picture Limitless Creativity at Your Fingertips.” Wired, 17 Nov. 2022, www.wired.com/story/picture-limitless-creativity-ai-image-generators/.
29. ↑ Kundu, Rohit. “AI-Generated Art: From Text to Images & beyond [Examples].” Www.v7labs.com, 2 Feb. 2023, www.v7labs.com/blog/ai-generated-art#:~:text=AI%2Dgenerated%20art%20also%20began. Accessed 9 Feb. 2023.
30. ↑ Kelly, Kevin. “Picture Limitless Creativity at Your Fingertips.” Wired, 17 Nov. 2022, www.wired.com/story/picture-limitless-creativity-ai-image-generators/.
31. ↑ Kundu, Rohit. “AI-Generated Art: From Text to Images & beyond [Examples].” Www.v7labs.com, 2 Feb. 2023, www.v7labs.com/blog/ai-generated-art#:~:text=AI%2Dgenerated%20art%20also%20began. Accessed 9 Feb. 2023.
32. ↑ Clarke, Laurie. “When AI Can Make Art – What Does It Mean for Creativity?” The Guardian, 12 Nov. 2022, www.theguardian.com/technology/2022/nov/12/when-ai-can-make-art-what-does-it-mean-for-creativity-dall-e-midjourney.
33. ↑ “Community Guidelines | Deep Dream Generator.” Deepdreamgenerator.com, deepdreamgenerator.com/community-guidelines. Accessed 27 Jan. 2023.
34. ↑ “Terms of Service - WOMBO Dream.” www.w.ai, 6 Apr. 2022, www.w.ai/terms-of-service-wombo-dream.
35. ↑ “Terms of Service.” www.wombo.ai, 1 Aug. 2021, www.wombo.ai/terms. Accessed 27 Jan. 2023.
36. ↑ Clarke, Laurie. “When AI Can Make Art – What Does It Mean for Creativity?” The Guardian, 12 Nov. 2022, www.theguardian.com/technology/2022/nov/12/when-ai-can-make-art-what-does-it-mean-for-creativity-dall-e-midjourney.
37. ↑ Clarke, Laurie. “When AI Can Make Art – What Does It Mean for Creativity?” The Guardian, 12 Nov. 2022, www.theguardian.com/technology/2022/nov/12/when-ai-can-make-art-what-does-it-mean-for-creativity-dall-e-midjourney.
38. ↑ “NVIDIA RESEARCH AI PLAYGROUND TERMS of USE.” Imaginaire.cc, 30 Sept. 2020, imaginaire.cc/gaugan360/term.txt. Accessed 27 Jan. 2023.
39. ↑ Edwards, Benj. “Artist Finds Private Medical Record Photos in Popular AI Training Data Set.” Ars Technica, 21 Sept. 2022, arstechnica.com/information-technology/2022/09/artist-finds-private-medical-record-photos-in-popular-ai-training-data-set/.
40. ↑ Vincent, James. “Getty Images Is Suing the Creators of AI Art Tool Stable Diffusion for Scraping Its Content.” The Verge, 17 Jan. 2023, www.theverge.com/2023/1/17/23558516/ai-art-copyright-stable-diffusion-getty-images-lawsuit.
41. ↑ “NVIDIA RESEARCH AI PLAYGROUND TERMS of USE.” Imaginaire.cc, 30 Sept. 2020, imaginaire.cc/gaugan360/term.txt. Accessed 27 Jan. 2023.
42. ↑ “Community Guidelines | Deep Dream Generator.” Deepdreamgenerator.com, deepdreamgenerator.com/community-guidelines. Accessed 27 Jan. 2023.
43. ↑ “Terms and Conditions | Deep Dream Generator.” Deepdreamgenerator.com, deepdreamgenerator.com/terms. Accessed 27 Jan. 2023.
44. ↑ “OpenAI API.” Beta.openai.com, beta.openai.com/docs/usage-policies/content-policy. Accessed 27 Jan. 2023.
45. ↑ Robertson, Adi. “The US Copyright Office Says an AI Can’t Copyright Its Art.” The Verge, 21 Feb. 2022, www.theverge.com/2022/2/21/22944335/us-copyright-office-reject-ai-generated-art-recent-entrance-to-paradise.
46. ↑ US Copyright Office, Copyright Review Board. Re: Second Request for Reconsideration for Refusal to Register a Recent Entrance to Paradise (Correspondence ID 1-3ZPC6C3; SR # 1-7100387071). 14 Feb. 2022.
47. ↑ Robinson, Blair. “Artists Are Selling AI-Generated Images of Mickey Mouse to Provoke a Test Case.” Data Privacy + Cybersecurity Insider, 5 Jan. 2023, www.dataprivacyandsecurityinsider.com/2023/01/artists-are-selling-ai-generated-images-of-mickey-mouse-to-provoke-a-test-case/. Accessed 27 Jan. 2023.
48. ↑ “Getty Images Statement.” Getty Images Press Site - Newsroom - Getty Images, 17 Jan. 2023, newsroom.gettyimages.com/en/getty-images/getty-images-statement.
49. ↑ Edwards, Benj. “Have AI Image Generators Assimilated Your Art? New Tool Lets You Check.” Ars Technica, 15 Sept. 2022, arstechnica.com/information-technology/2022/09/have-ai-image-generators-assimilated-your-art-new-tool-lets-you-check/.
50. ↑ https://www.nbcnews.com/tech/internet/lensa-ai-artist-controversy-ethics-privacy-rcna60242
51. ↑ https://www.vice.com/en/article/jgpzz3/ai-art-in-schools
52. ↑ https://news.artnet.com/art-world/class-action-lawsuit-ai-generators-deviantart-midjourney-stable-diffusion-2246770?fbclid=IwAR0W31X7_n_h7p5_GtM7O7_k2Dj-a9l5xAmn_YG7qQ895XlwxAZjc771zcc
53. ↑ https://www.cbc.ca/news/canada/sudbury/ai-generated-art-consent-1.6722981