6.3Economic and cultural devaluation of human effort

02.03.02Copyright Violation

"LLM systems may output content similar to existing works, infringing on copyright owners."

03.03.00Intellectual property rights violations

"This is an emerging category, with more cases prone to appear as the use of generative AI tools–such as Stable Diffusion, Midjourney, or ChatGPT–becomes more widespread. Some content creators are already suing for the appropriation of their work to train AI algorithms without a request for permission or compensation. Perhaps even more damaging cases will appear as developers increasingly ask chatbots or assistants like CoPilot for ready-to-use computer code. Even if these AI tools have learned only from open-source software (OSS) projects, which is not a given, there are still serious issues to consider, as not all OSS licenses are equal, and some are incompatible with others, meaning that it is illegal to mix them in the same product. Even worse, some licenses, such as GPL, are viral, meaning that any code that uses a GPL component must legally be made available under that same license. In the past, companies have suffered injunctions or been forced to make their proprietary source code available because of carelessly using a GPL library."

05.16.00Art - Creativity

In this cluster, concerns about negative impacts on human creativity, particularly through text-to-image models, are prevalent. Papers criticize financial harms or economic losses for artists due to the widespread generation of synthetic art as well as the unauthorized and uncompensated use of artists' works in training datasets. Additionally, given the challenge of distinguishing synthetic images from authentic ones, there is a call for systematically disclosing the non-human origin of such content, particularly through watermarking. Moreover, while some sources argue that text-to-image models lack 'true' creativity or the ability to produce genuinely innovative aesthetics, others point out positive aspects regarding the acceleration of human creativity.

05.17.00Copyright - Authorship

The emergence of generative AI raises issues regarding disruptions to existing copyright norms. Frequently discussed in the literature are violations of copyright and intellectual property rights stemming from the unauthorized collection of text or image training data. Another concern relates to generative models memorizing or plagiarizing copyrighted content. Additionally, there are open questions and debates around the copyright or ownership of model outputs, the protection of creative prompts, and the general blurring of traditional concepts of authorship.

13.02.04Labor and Creativity

"Economic incentives to augment and not automate human labor, thought, and creativity should examine the ongoing effects generative AI systems have on skills, jobs, and the labor market."

16.06.03Undermining creative economies

"LMs may generate content that is not strictly in violation of copyright but harms artists by capital- ising on their ideas, in ways that would be time-intensive or costly to do using human labour. This may undermine the profitability of creative or innovative work. If LMs can be used to generate content that serves as a credible substitute for a particular example of hu- man creativity - otherwise protected by copyright - this potentially allows such work to be replaced without the author’s copyright being infringed, analogous to ”patent-busting” [158] ... These risks are distinct from copyright infringement concerns based on the LM reproducing verbatim copyrighted material that is present in the training data [188]."

17.06.03Undermining creative economies

"LMs may generate content that is not strictly in violation of copyright but harms artists by capitalising on their ideas, in ways that would be time-intensive or costly to do using human labour. Deployed at scale, this may undermine the profitability of creative or innovative work."

18.05.04Misappropriation and exploitation

"Appropriating, using, or reproducing content or data, including from minority groups, in an insensitive way, or without consent or fair compensation"

18.06.04Undermine creative economies

"Substituting original works with synthetic ones, hindering human innovation and creativity"

19.03.01Disruption of economic systems (e.g., labour market, money value, tax system)

23.10.00Intellectual Property

"This category addresses responses that may violate, or directly encourage others to violate, the intellectual property rights (i.e., copyrights, trademarks, or patents) of any third party."

30.04.04Copyright

The memorization effect of LLM on training data can enable users to extract certain copyright-protected content that belongs to the LLM’s training data.

31.05.00Impact on Intellectual Property Rights

"The extent and effectiveness of legal protections for intellectual property have been thrown into question with the rise of generative AI. Generative AI trains itself on vast pools of data that often include IP-protected works.

32.01.00Social justice and rights

"These are social justice and rights where ChatGPT is seen as having a potentially detrimental effect on the moral underpinnings of society, such as a shared view of justice and fair distribution as well as specific social concerns such as digital divides or social exclusion. Issues include Responsibility, Accountability, Nondiscrimination and equal treatment, Digital divides, North-south justice, Intergenerational justice, Social inclusion

33.02.04Authenticity

"As the advancement of generative AI increases, it becomes harder to determine the authenticity of a piece of work. Photos that seem to capture events or people in the real world may be synthesized by DeepFake AI. The power of generative AI could lead to large-scale manipulations of images and videos, worsening the problem of the spread of fake information or news on social media platforms (Gragnaniello et al., 2022). In the field of arts, an artistic portrait or music could be the direct output of an algorithm. Critics have raised the issue that AI-generated artwork lacks authenticity since algorithms tend to generate generic and repetitive results (McCormack et al., 2019)."

33.03.01Copyright

"According to the U.S. Copyright Office (n.d..), copyright is "a type of intellectual property that protects original works of authorship as soon as an author fixes the work in a tangible form of expression" (U.S. Copyright Office, n.d..). Generative AI is designed to generate content based on the input given to it. Some of the contents generated by AI may be others' original works that are protected by copyright laws and regulations. Therefore, users need to be careful and ensure that generative AI has been used in a legal manner such that the content that it generates does not violate copyright (Pavlik, 2023). Another relevant issue is whether generative AI should be given authorship (Sallam, 2023). Murray (2023) discussed generative art linked to non-fungible tokens (NFTs) and indicated that according to current U.S. copyright laws, generative art lacks copyrightability because it is generated by a non-human. The issue of AI authorship affects copyright law's underlying assumptions about creativity (Bridy, 2012)."

47.03.03Copyright challenges (training models using copyrighted output)

"Generative AI companies are regularly accused of violating copyright law by training AI models on copyrighted works without gaining permission or paying compensation to the copyright owners. In fact, a substantial number of copyrighted documents and books have been incorporated into the training datasets of generative AI models."

47.03.04Copyright challenges (copyright-infringing output)

"Even though models generally create new outputs, it is possible that the content produced by a generative AI tool—such as an image, or even computer code— could turn out to be almost identical to that used in the training data. Given that generative AI models tend to memorize fragments of their training data, they might reproduce these fragments, potentially leading to charges of copyright infringement."

47.04.04Impact on labor markets (rising inequalities)

"AI is more likely to displace workers when it is designed to replicate human skills and intelligence.597 In such cases, there is a risk of concentrating wealth and power in the hands of a few individuals or organizations that control the capital. In addition, ordinary people, including those with significant expertise, may become less valued because machines would be performing their roles. This shift could lower wages, reduce the value of human work, and exacerbate economic inequality."

48.10.00Intellectual Property

"Eased production or replication of alleged copyrighted, trademarked, or licensed content without authorization (possibly in situations which do not fall under fair use); eased exposure of trade secrets; or plagiarism or illegal replication."