Designing for Collaboration, Participation and Futures Inspired by Art | AI House Davos 2026
Mars Pennington on Interdisciplinary Collaboration
Mars Pennington advocates for interdisciplinary collaboration in AI development, emphasizing the need to integrate perspectives from engineering, humanities, law, and social sciences. She suggests that this approach allows for a broader understanding of the challenges and opportunities presented by AI, leading to more equitable and responsible outcomes. Design, in this context, serves as a catalyst for bringing these diverse perspectives together to create tangible solutions.
Sharon Prince on Ethical AI
Sharon Prince argues that ethical AI must extend beyond software to encompass the ethical sourcing of hardware components, particularly in data centers. She highlights the need for transparency in labor practices and material sourcing to ensure that AI development does not contribute to exploitation. By addressing these ethical concerns, Prince believes AI can contribute to a more just and sustainable future.
Tero Fuji on University's Role
Tero Fuji emphasizes the crucial role of universities in addressing AI's challenges, particularly in ensuring that the technology serves diverse populations and cultures. He highlights the need to harness smaller, localized AI systems within larger frameworks, considering linguistic and cultural nuances. This approach aims to prevent a homogenized, one-size-fits-all AI that could marginalize certain communities.
Mars Pennington on Design's Role
Mars Pennington suggests that design is crucial for bringing AI to life and making it tangible, enabling people to engage with and critique it effectively. She argues that design facilitates the creation of prototypes and visuals that allow for concrete discussions and faster progress in AI development. By making AI more accessible and understandable, design can foster broader participation and innovation.
Tero Fuji on Open Universities
Tero Fuji argues that universities must become more open to society, fostering collaboration between students, professors, and professionals. He envisions a dynamic exchange where individuals from various sectors contribute to research and development, breaking down traditional barriers between academia and the outside world. This openness, according to Fuji, is essential for addressing the complex challenges posed by AI and ensuring its responsible development.
Prima Vera on AI Training
Prima Vera De Filippi emphasizes the critical role of the current generation in training AI systems, as these systems will subsequently train future generations. She stresses the importance of embedding ethical values into AI design to ensure that these values are replicated and reinforced in subsequent learning processes. This perspective underscores the long-term impact of current design choices on the future of education and societal norms.
Prima Vera on Regulatory Limits
Prima Vera De Filippi discusses the limits of regulatory approaches without design intervention in AI. She argues that emerging technologies like AI enable new usages that are not yet encompassed by existing laws. Design, in this context, plays a crucial role in exploring the space of possibilities and proposing ways to embed legal and policy objectives directly into the technology, reducing the need for ex-ante regulation.
Sharon Prince: Ethical Sourcing Imperative
Sharon Prince asserts that ethical AI must begin with ethically sourced hardware, including data centers. She argues that the massive energy consumption and infrastructure of AI development necessitate transparency in labor practices and material sourcing. By addressing these ethical concerns, Prince believes AI can contribute to a more just and sustainable future, ensuring that technological advancements do not perpetuate exploitation.
Tero Fuji on Art and Design
Tero Fuji suggests that art and design can serve as powerful tools for shaping the future of AI by creating tangible representations that facilitate discussion. He argues that design can help structure AI services in a way that reflects diverse perspectives and values, enabling more inclusive and ethical outcomes. By making AI more accessible and understandable, design can foster broader participation and innovation.
