OUR GOAL:


INTERDISCIPLINARY, 
HUMANITIES-LED, ETHICAL RESEARCH PRACTICES 

In 2019, the Ada Lovelace Institute requested proposals for a strategic networking project funded by the UK Research and Innovation’s Arts and Humanities Research Council (AHRC). They wanted a way to bring together citizens, policymakers, and academics involved in data and AI ethics research. Ada and the AHRC hoped connecting disparate thinkers would advance understanding, definition, practice, and policy in the field of data and AI ethics. 

 

Data and AI ethics research remains predominantly privately supported and operationalized. As a result, ethical principles outpace public involvement and ethics is often an afterthought. JUST AI believes addressing ethical problems requires creative and collaborative thinking that transforms ethical principles into practice. 

 

Therefore, we proposed a method of interdisciplinary public engagement that would bring a variety of people together using humanities-led approaches to encourage data and AI ethics research around social justice. What was expected to take the form of a series of workshops instead grew into multiple modes of experimentation, iteration, and reflection on the idea of a network and how a variety of practices build capacity on issues of extreme social significance.

Watch our presentation on Ethics in Practice

OUR FRAMEWORK:

NETWORKS 

 

 

Our organisation recognizes networking as both a verb and a noun. To network creates and transforms relationships, while a network is an intellectual community or project. In considering and applying both definitions, JUST AI’s conceptual framework produces new possibilities for understanding the social and ethical value of data-driven systems through practice-based research.

 Network (n): a set of connections   between people and their ideas 

The JUST AI network connects thinkers and doers across disciplines which generatively links artistic commentary and academic research in data and AI ethics. As the existing data and AI ethics field continues to develop, the JUST AI network identifies and supports ideas produced in multiple contexts to capture the dynamism of ethical efforts and ensure their collective benefit. Connecting individuals based in the humanities loosens the hold techno-systems have in data and AI development and reveals alternatives. The arts in particular provide ways to imagine other worlds that inspire intervention in existing ones. JUST AI believes the power of the humanities is to recognize and create new practices in scholarship that expand its possibilities.

 Network (v): to identify emerging topics and  intervene through interdisciplinary encounters 

 and collaboration 

JUST AI networks by mapping data and AI ethics research to foreground the perspectives and subjects necessary to address social justice issues. When emerging issues have been identified, JUST AI intervenes by convening conversations that connect disparate disciplines including art, design, and writing” and commissioning creative work that prompts discussion. These tactics make space for under-recognized voices in data and AI ethics research which builds the capacity for new narratives and public engagement within it.  

 

OUR METHODOLOGY:

MAP AND CONVENE TO IDENTIFY AND INTERVENE 

The JUST AI network is both a community of practitioners working in data and AI ethics and a way of working that advances the field. JUST AI performs networks through a combination of methods. We describe networks through analysis and visualisation, which makes for stronger ‘networking’ of people and ideas.

Mapping: Bibliometric analysis &  visualisation to identify emerging issues 

JUST AI conducted a bibliometric analysis of the UK’s data and AI ethics landscape in 2021. In collecting what information had been published, who had authored it, and the words they used, we were able to discern which people were discussing what topics and how. Collecting and clustering writings revealed that data and AI ethics is an area of wide intellectual pursuit but indicated that the study and practice of data and AI ethics in the UK prioritised approaches from white, western, and male perspectives. When discussed in narrow isolation, the solutions for  data-driven AI consequences can become limited. Our findings supported the need for interdisciplinary and humanities-led practices to transform the field we had mapped.

 

We visualised the networks we analysed to more clearly see the relationships, demographics, and disciplines of practitioners and reveal which perspectives were prominent and which deserved more attention. Our visualisations also helped to identify topics that exist but are not yet valorized in data and AI ethics. We were interested in how the emerging concept of data justice related to work that drew on an emerging canon of ‘ethical AI’. We ran our analysis using that phrase and found only a handful of scholars linking the emerging and existing networks drawing on ‘ethics’ and ‘justice’. This visualisation inspired us to come up with ways of facilitating conversation and collaboration between the individuals committed to justice in data and AI ethics as a way to incorporate difference and reimagine futures.

Mapping: Reflection Prototype to identify perspectives and possibilities  

JUST AI challenged the inherent limitations of bibliometric analysis by creating a way to make mapping interactive. Our Reflection Prototype survey and workshops allow anyone to examine their own position in data and AI ethics research and add it to the expanding field. When individuals complete the survey, they receive a visual representation of their experiences in relation to others which is used in conversation to entangle people with similar or distinct interests. The more the Prototype is used, the more connections get revealed, and the deeper understanding becomes. The Reflection Prototype is intentionally designed as a creative prop for groups to engage with a range of expertise and experiences in data and AI ethics. 

 

Comparing answers provides an opening for discussion about the difference in perspective and demonstrates the critical skills the humanities bring to questions around data and AI ethics. The Reflection Prototype is a manifestation of JUST AI’s unique approach to exploring data and AI ethics through public engagement and art. Furthermore, prototypes permit open and experimental thinking which JUST AI believes is crucial to incorporating justice in data and AI ethics research. The Reflection Prototype supports infinite additions to the field so as not to exclude possible perspectives or connections. It also supports interdisciplinary research by finding connections, divergences, and points of encounter. In this way, using our Prototype becomes an ethical practice.

Convening: Intervention through community building and  commissioned work 

After identifying data justice as an emerging area and prototyping to continually find others, JUST AI set up programs and processes that intervene in data and AI ethical issues by convening those who are working to address them found on our maps. JUST AI built a network of people and projects shifting priorities, perspectives, and practices in data and AI ethics through the facilitation and financial support of conversation and creative work.

 

We established the Racial Justice Fellowship program to redress how racial aspects of data and AI ethics were not prominently present in the field we had mapped. JUST AI selected and supported four research projects conducting racial-justice-oriented work in an effort to prioritise ethical investigation into this social issue. The Fellow’s collective work spans areas of public policy, biometric surveillance, data practices, and research on the Dartmouth AI study. In addition to their own work, the Fellows have collaborated in bi-weekly meetings to build and sustain their research practices. Through these lab meetings, the Fellowship has built a space of reflection and support geared toward connecting issues in AI ethics to matters of racial justice. 

Iteratively mapping data and AI ethics research highlighted other areas that are especially challenging or complex. JUST AI specifically identified issues of holistic sustainability and the dynamics of rights, access, and refusal surrounding data-driven AI technologies. In response, we formed the Deep Sustainability and Rights, Access, and Refusal (RAR) working groups to intervene through structured conversation and commissioned work. These groups include JUST AI team members, Ada staff, and external scholars and creative researchers. Each working group designed its own approach to define and conduct cross-disciplinary research, including how to commission publicly-engaging creative work and host discussions among experts. They are intended to experiment with new directions and demonstrate the role creative and humanities-led work has in building capacity for interdisciplinary encounters.

Commissioning creative work (including art, design, and writing) is a way for JUST AI to position humanity as the basis of ethical consideration. In addition to commissions within the Racial Justice Fellowship and working groups, JUST AI has supported fiction writing in our effort to prototype ethical futures. 

OUR RESULT:

A NETWORK THAT MODELS A NEW WAY TO NETWORK 

 

The JUST AI project has consciously created a humanities-led methodology that creates  interdisciplinary encounters and public understanding to advance data and AI ethics research practices. Our work integrates several approaches to networking that experiment with the dynamism of connections and prototype possible directions. We integrate bibliometric processes and participatory reflections to iteratively map and identify emerging issues in the data and AI ethics field. We establish and support the connection of data and AI ethics practitioners by convening a cohort of Fellows and working groups, hosting public events, and commissioning creative work. As a result, we have built a network that encompasses a variety of existing perspectives, disciplines, and theoretical orientations to prioritise multiple positions in data and AI ethics. 

 

Our methodology is meant to be adopted and adapted by those hoping to expand their own work or continue working on data justice. JUST AI experiments with a large range of social science, humanities-based, and creative methods to reconsider networking in order to expand our understanding of data and AI ethics but also to model how to do the same. When we consider a network as a noun that describes a community or set of connections, we use bibliometric and reflective mapping methods to analyse existing relationships and define new ones in a field. When networking is treated as a verb we convene and collaborate to reveal connections that aren’t necessarily possible with descriptive tactics alone. JUST AI reframes network methodology as an incomplete practice of mapping and remapping that always involves a certain level of feedback through prototyping. The constant feedback of iterative processes and convened communities creates the capacity for new perspectives and critical engagement. The infinite and inclusive potential of JUST AI’s methodology turns it into ethical practice. 

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