How can we create anti-colonial approaches to AI?
How can ‘slow’ principles help us arrive at better ways of designing, deploying and engaging with the technology across different fields?
What can a Slow AI become?
We are excited to share with you the launch of “Slow AI,” a collaboration between the Visual Methodologies Collective at Amsterdam University of Applied Sciences and the Algorithmic Cultures Research Group at Gerrit Rietveld Academie, Amsterdam. Originating from Mariana Fernandez Mora’s ongoing research into decoloniality in AI, this project will focus on laying the ground for developing strategies to address colonial and extractive histories embedded in current AI systems by introducing the concept of slowness to a fast technology. The project will do this through a series of working sessions and material-based research workshops in collaboration with the ARIAS Artificial Worlds group which will culminate in a publication presented together with a symposium.
As Artificial Intelligence becomes increasingly prevalent in every aspect of our lives, it is crucial to address the way it amplifies existing colonial, extractive, and biased structures embedded in it. Issues such as the homogeneity of AI creators, biases, and the environmental impact of the technology are some examples of the urgent need for innovative approaches that counter act them. In response, the Slow AI project introduces the concept of ‘slowness’ to this fast technology, understanding it beyond a temporal metric and rather as a change in modes of engagement that resist notions of speed, efficiency, and optimisation rooted in its colonial and extractive history. It aims to challenge the prevailing trends of extraction, rapid consumption, immediate gratification, and the relentless pursuit of efficiency that have characterised the digital era, particularly within AI.
This research is informed by scholars like Virginia Eubanks, Kate Crawford, Safiya Noble, Ruha Benjamin, and James Bridle looking to emphasise the importance of addressing underlying power dynamics and systemic issues in AI from a multi-disciplinary perspective.
Team:
Mariana Fernández Mora (HvA)
Sabine Niederer (HvA)
Flavia Dzodan (Rietveld Academie)
Maarten Groen (HvA)
Zachary Formwalt (Rietveld Academie)
Andy Dockett (HvA)
Janine armin (HvA)
In collaboration with ARIAS Amsterdam and generously funded by the Centre of Expertise Creative Innovation, Slow AI aims to contribute to a more equitable and sustainable technological landscape.
For updates on the research and public events, subscribe to the ARIAS Artificial Worlds newsletter here.
This paper introduces and contextualises Climate Futures, an experiment in which AI was repurposed as a ‘co-author’ of climate stories and a co-designer of climate-related images that facilitate reflections on present and future(s) of living with climate change. It converses with histories of writing and computation, including surrealistic ‘algorithmic writing’, recombinatory poems and ‘electronic literature’.
At the core lies a reflection about how machine learning’s associative, predictive and regenerative capacities can be employed in playful, critical and contemplative goals. Our goal is not automating writing (as in product-oriented applications of AI). Instead, as poet Charles Hartman argues, ‘the question isn’t exactly whether a poet or a computer writes the poem, but what kinds of collaboration might be interesting’ (1996, p. 5).
STS scholars critique labs as future-making sites and machine learning modelling practices and, for example, describe them also as fictions. Building on these critiques and in line with ‘critical technical practice’ (Agre, 1997), we embed our critique of ‘making the future’ in how we employ machine learning to design a tool for looking ahead and telling stories on life with climate change. This has involved engaging with climate narratives and machine learning from the critical and practical perspectives of artistic research. We trained machine learning algorithms (i.e. GPT-2 and AttnGAN) using climate fiction novels (as a dataset of cultural imaginaries of the future). We prompted them to produce new climate fiction stories and images, which we edited to create a tarot-like deck and a story-book, thus also playfully engaging with machine learning’s predictive associations.
The tarot deck is designed to facilitate conversations about climate change. How to imagine the future beyond scenarios of resilience and the dystopian? How to aid our transition into different ways of caring for the planet and each other?
What makes you feel that you belong in the city?
When addressing diversity in urban planning and urban policy there is a tendency to look at social issues in isolated ways. But identities are complex, intricate and interwoven. If someone is for instance both gay and disabled, their urban experience might be a lot different from people who are queer and able-bodied, or heterosexual and disabled. To understand these intersections this research folds into it Data Feminism; practices of intersectional feminist theory and critique.
First, participatory methods rethink citizen engagement as a process, redefining who is invited to the conversation and suggesting alternative and more sensitive ways of engaging under represented communities. Second, the way that data is used to tell stories about people’s urban experiences is redesigned. It is also crucial that the binary pink-and-blue gender diagrams are replaced, and a more nuanced data visualisation language is introduced that captures the intersectional complexity of social issues.
To do so, this research experiments with making maps and visualisations that break hierarchies, challenge binaries and exposes power dynamics that shape feelings of belonging in cities.
This research is apart of the Urban Belonging project initiated in 2021 by a collective of planners and scholars in Copenhagen with the ambition of mapping lived experiences of under-represented communities in the city. Collaboration partners include Techno-Anthropology Lab, Service Design Lab at Aalborg University, Center for Digital Welfare at IT University of Copenhagen, and Gehl Architects.
A look at the rich history of local media-making in and around the Bijlmer neighbourhood in Amsterdam-Zuidoost.
Amsterdam-Zuidoost has a long tradition of media-making as a way to be heard, represent themselves, have influence, and create a feeling of home. From the pirate radio stations of the 1970’s all the way to the podcasts and digital radio stations of today, the practice of making and listening to radio strengthens a community identity and contributes to a sense of belonging. Thinking through the broader issue of auditory culture in Amsterdam-Zuidoost, participatory exercises and workshops within the community take a closer look at the listening needs of the local community.
What is being listened to, and why? And does radio still have a place in the listening behaviour of the young people?
Explore the outcomes of these exercises and workshops at the Research Station itself this spring, where its various drawers contain research materials for each line of inquiry.
Other partners:
ImagineIC