Navigating the Ethical Horizon: Insights from our AI Ethics Model UN Debate on AI Art Generation
In the ever-evolving landscape of artificial intelligence, where innovation meets ethical considerations, our research group recently hosted a thought-provoking event series—the AI Ethics Debates. This unique debate series brought together students from our research community to deliberate on the various ethical dimensions of artificial intelligence, mirroring the diplomatic spirit of a Model UN conference. Against the backdrop of emerging technologies and their impact on society, the debate provided a platform for these aspiring researchers to channel their insights, concerns, and recommendations. In this post we highlight the responses of participating teams.
Scenario: AI Art Generation
A media production company has recently developed the opening credit of a series completely with AI. Some artists working at the company are going to protest and sue the company. The company is arguing that using AI models will eventually help the company. They are arguing that developing such models able to generate the requested art form will not be fair to the artists who have created the content the models use as training data. Their jobs are at risk while the model is using their art for training purposes.
Group responses
The Arts Team
Batool AlMousawi, Radin Hamidi Rad, Aude Marie Marcoux
The collective response regarding the AI ethics scenario involving Generative AI (GenAI) in a media production company reveals a diverse set of concerns and perspectives. The discussion begins with worries about the security of GenAI models and potential data leaks, especially regarding voice models. The claims from the Corporate team about GenAI fostering creativity are met with skepticism, raising questions about the actual generativity of a model that replicates existing artists' works. Concerns are expressed regarding the impact on artists' jobs, the questionable democratization of art, and the ethical implications of using global artwork without proper attribution or compensation.
The emphasis on the delicate balance between innovation and professional ethics is apparent, arguing against the creation of derivative versions of artists' work through GenAI. The fear of job loss, combined with concerns about copyright infringement and the ethical sourcing of data, reflects broader apprehensions about the potential exploitation of creative output. Attention is drawn to the risk of misinformation and disinformation associated with AI tools, particularly in journalism, stressing the importance of upholding journalistic values and ethics.
Representing the perspective of an artist, rebuttal arguments are provided. Addressing the claim that job losses in the arts can be offset by the emergence of new AI-related jobs, it is argued that the skills and creativity of artists do not necessarily transfer to technical roles. The accessibility of GenAI is challenged, noting that it requires specific resources and digital literacy, potentially making art more inaccessible. Additionally, the comparison of GenAI to a tool like a paintbrush or camera is rejected, highlighting the ethical issues related to unauthorized use of artists' work and the lack of compensation.
In summary, the group response articulates a comprehensive set of concerns, encompassing job security, ethical considerations, copyright issues, and the potential negative impact of AI on the artistic industry. The responses collectively underscore the need for careful consideration and ethical guidelines in the development and deployment of AI models in creative fields.
The Corporate Team
Solomon Amenyo, Samy Assouane, Omid Shokrollahi
The use of generative artificial intelligence (AI) in the production of art presents a potentially game changing opportunity for increased artistic originality and effectiveness within the context of media production. It’s possible that some artists will view this as a threat to their ability to make a living, but there are actually a lot of good things that can come from AI-driven art development. The purpose of these AI models is not to serve as a replacement for human creativity but rather as a source of fresh ideas that can be built upon. They make techniques, styles, and possibilities that were previously inaccessible or required a significant amount of time available to artists. This collaborative effort between human creators and AI, which is advantageous to both parties, fosters collaboration in which the latter complements rather than unseats human innovation. By lowering entry barriers and making the creative process more accessible, generative AI is democratizing the production of original content.
When AI is utilized to generate artwork, the production operations that are involved can be considerably simplified. When artists automate repetitive or technical tasks, it frees up the mental capacity for more creative and conceptual considerations to be given. Not only does this result in a higher output, but it also makes more room for innovative exploration and experimentation. The idea that using artists’ work as training data for AI models will boost the artists’ prominence is overlooked in the argument that this will jeopardize the artists’ ability to make a living from their work. The use of AI in the creative process can lead to exciting new career paths and the development of valuable industry-specific skills. Artists can take on a new role as facilitators, coaching and directing AI models to realize specific artistic concepts, increasing their importance in today’s dynamic media creation environment.
It is not acceptable to disregard intellectual property rights simply because AI is the creative force behind works of art. It is possible to put in place the appropriate infrastructure to guarantee that the original creators will be credited and compensated. Additionally, this would alleviate the ethical problems with the utilization of material protected by copyright in the training datasets. AI does not “exploit” in the same way that humans do. It processes data and generates outcomes. How we as a society decide to employ and control this technology is the actual point of debate. With the correct regulations in place, AI art generation can continue to advance while also protecting artists’ rights. In order to solve the problem of how to compensate artists, we decided to implement a tipping system. This technique is intended to provide financial rewards for the original artists, thereby addressing the issue of compensation that was raised. Because of this retrieval mechanism, when we produce new works of art, we also produce new opportunities for artists to be acknowledged and paid for their efforts. Artistic retrieval systems use complex algorithms to examine, evaluate, and detect parallels between newly created works of art and the themes explored in earlier works of art. This system utilizes a wide range of methods, such as image recognition, semantic analysis, and pattern identification, to identify similarities between newly created works and the large archive of historical artwork. This helps to ensure that the artists’work is not forgotten as the digital age advances.