WP2: AI in artistic processes

This work package is about artists who make things with AI: pictures, films, games, books, music and more. Many artists already use AI tools every day. We want to know what these tools do to the work, and what they do to the artist.

This work package looks at AI systems used to make works in the arts and the creative industries: visual art, film, virtual and extended reality, literature, performing arts, games and music. Prompt-based, machine-learning tools are becoming a normal part of many workflows, and the people who use them are increasingly aware of both what they give and what they cost.

This WP focuses on AI systems used in producing works associated with the arts and creative industries, including visual arts, film, VR/XR, literature, performing arts, games, and music. Prompt-based, machine-learning systems are becoming normalised in many workflows, and practitioners and professionals are increasingly aware of their benefits and costs.

Description

When an artist hands part of the work to a machine, something changes. Many AI tools were trained on the same big pile of images and texts, so they tend to give everyone the same kind of answer. That can make art more alike and push unusual voices aside.

So we ask: who decides which stories get told and which pictures get seen? We look closely at the tools, find the biases built into them, and try to keep the artist in charge. The aim is tools that make culture more varied and more open, not less.

Two concerns run through the work package. One is what happens when creative work and creative decisions are handed over to an AI system. The other is the cultural bias built into many commercial tools. Creativity shapes how communities see themselves and imagine what is possible; when AI systems repeat dominant cultural patterns and push alternatives to the margins, they narrow public conversation, reduce cultural diversity and strengthen existing norms at the expense of exploration.

That raises questions about cultural agency: who decides which stories are told, which images are seen, and which ideas shape our shared reality? The work package examines these challenges in the creative process, questions the idea that an AI system can be neutral, and looks at the biases embedded in the tools. The goal is creative tools that lead to more inclusive, diverse and democratic cultural futures, with the artist rather than the machine in control.

Concerns include the effects of “outsourcing” creative work and decision-making to AI systems and the hegemonic cultural biases present in many commercial tools. Creativity shapes how communities see themselves and imagine new possibilities. When AI systems reinforce dominant cultural patterns and marginalised alternative perspectives, they risk narrowing public discourse, diminishing cultural diversity, and strengthening existing norms at the expense of exploration and innovation.

This raises critical questions about cultural agency: Who decides what stories are told, what images are seen, and what ideas shape our shared reality? This WP will explore new challenges in the creative process, challenging the concept of “neutrality” in AI systems and examining embedded biases. The goal is to ensure that creative tools contribute to more inclusive, diverse, and democratic cultural futures, balancing artistic control with machine dominance to preserve human aesthetic and artistic integrity.

Research Questions

How can artists use AI to make new work without everyone’s work ending up the same?
What does AI in art mean for artists and for audiences, and how do we keep art varied and original?
How can artists push what is possible with AI tools while keeping an eye on the biases inside them?
How can art show where today’s AI falls short, and help build better tools that put artists first?

RQ2.1: How can artists bring generative AI into their idea and production work while keeping their own creative judgement and avoiding the sameness the machines tend towards?
RQ2.2: What do AI systems in the creative process mean, culturally and ethically, for artists and audiences, and how can diversity and originality be protected?
RQ2.3: How can artists and producers use generative AI to extend artistic expression while engaging critically with the biases built into the systems?
RQ2.4: How can artistic exploration expose the limits of today’s AI and inspire more inclusive, artist-centred tools that support innovation and human agency?

RQ2.1: How can artists integrate generative AI systems into their ideation and production processes while maintaining creative autonomy and avoiding the risk of machine-driven homogenisation?
RQ2.2: What are cultural and ethical implications for artists and audiences when AI systems integrate into creative processes, and how can these be addressed to ensure diversity and originality?
RQ2.3: How can artists and creative producers employ generative AI tools to push the boundaries of artistic expression while critically engaging with the biases embedded in these systems?
RQ2.4: How can artistic exploration help expose limitations of current AI technologies and inspire the development of more inclusive, artist-centred tools that foster innovation and human agency?

Approaches

CREATE: new artworks and new tools where the artist stays in charge.
EXPLORE: today’s AI tools, to find out what they can do, what they cannot, and where they are unfair.
REFLECT: on what making art with AI teaches us about creating, about audiences and about society.

CREATE: new AI-based artworks and tools built around the artist’s workflow, giving creative control and room for innovation across fields.
EXPLORE: existing AI tools, to identify their potential, their limits and their problems, with attention to ethics, law and cultural bias.
REFLECT: on how the interplay of AI and human creativity gives new insight into the act of creation, its effect on audiences, and the social role of art today.

CREATE: new AI-based artistic productions and tools that prioritise artist-centred workflows, enabling creative control and innovation across diverse fields.
EXPLORE: existing AI tools to identify their potentials, limitations, and challenges, focusing on ethical and legal implications and cultural biases.
REFLECT: on how the interplay between AI and human creativity exposes new insights into the act of creation, its impact on audiences, and the social impact of art on contemporary society.

Sustainability

This work helps with two of the United Nations’ goals for a better world. Fighting the bias in commercial AI tools works against inequality (SDG 10), and building tools that let more people see themselves in culture supports open and fair societies (SDG 16).

The centre’s other commitments on sustainability, openness and reuse are on the open research page.

This work package contributes to two of the UN Sustainable Development Goals. Confronting the cultural biases in commercial generative tools, and developing artist-centred alternatives, works against inequality (SDG 10) and towards cultural expression that more people can recognise as their own (SDG 16).

The centre’s other commitments on sustainability, openness and reuse are on the open research page.