DATAVYSTS – Social Innovation and AI for Good

Connecting Social Innovation with AI: About DATAVYSTS

DATAVYSTS is a Marie Sklodowska-Curie Actions (MSCA) doctoral network (MSCA-DN) connecting social innovation with data science and AI to serve the common good. Funded by Horizon Europe and UK Research and Innovation (UKRI), the network brings together 13 doctoral research fellows alongside academics and real-world partners from across Europe and beyond. United by a shared conviction that data science and artificial intelligence (AI) should work harder for people, not just for profit, they are technically fluent and socially grounded, critical, creative, community-rooted and globally ambitious.

MSCA are part of the research and innovation programme of the EU Horizon Europe and fund excellent research and innovation equipping researchers at all stages of their career with new knowledge and skills, through mobility across borders and exposure to different sectors and disciplines. MSCA also fund the development of excellent doctoral and postdoctoral training programmes and collaborative research projects worldwide. By doing so, they achieve a structuring impact on higher education institutions, research centres and non-academic organisations. Further information of MSCA can be found on their official website.

UKRI is a non-departmental public body sponsored by the Department for Business, Innovation, Science and Trade in the UK. It supports the development of skills and careers across research and innovation. It provides targeted talent investments such as fellowships and doctoral training awards. It also helps foster a healthy research and innovation environment which attracts, retains and develops talented people. Further information of UKRI can be found on its official website.

As the Data and AI for Good field is flourishing, organizations across the world are innovating the use of data science and AI to tackle social issues from climate change, to democratic erosion, global health inequity, and community displacement. The need is real. The energy is real. The current label, however, is not doing the work we need it to do.

‘For good’ is one of the most loaded phrases in the technology sector. It promises purpose, accountability, and shared values. But scratch beneath the surface and you find something more complicated: a field that uses good as a language to mean very different things. 

This is exactly the kind of question the DATAVYSTS were built to answer. Not just what social innovation and AI for Good is in theory, but what it means today in practice, not just building tools, but asking the harder questions about who those tools serve and on whose terms. 

An International and Interdisciplinary Network

The network of doctoral fellows and experienced researchers as supervisors constitutes an interdisciplinary and international network spanning multiple projects embedded in the dissertation themes and cascaded learning, in key fields of data science, AI, and social innovation. Our fellows come from diverse countries as Algeria, Belgium, Brasil, Colombia, Hungary, Kenya, Germany, Mexico, Poland, Serbia, South Africa, and United States of America. 

Across five host universities in Belgium, Germany, Italy, Slovenia, and United Kingdom research projects are being conducted. The lead partners are: 

Four Commitments Setting the Project Manifesto 

The DATAVYSTS manifesto sets out four commitments that define the purpose of the projects and guide the actions towards purposeful goals.

Source: Datavysts.eu

DATAVYSTS approaches these commitments from a highly ambitious perspective:

It needs a brave new generation of hybrid thinkers and doers who can reboot AI and data science from the ground up, who understand the bidirectional involvement with social innovation and that real change happens when we build with purpose. That is what the DATAVYSTS are here to do.

#Meet the DATAVYSTS

As both doctoral fellows and supervisors have embarked on a journey to make an impact in social innoation, data science and AI research and practice, we asked some of our fellows and supervisors to share from their direct experiences into the almost ending first year of the project, gaining a real sense of what is lived in the DATAVYSTS journey.

Here’s what the fellows are sharing with us:

Annette Botha, Doctoral Candidate at Ghent University is researching social innovations that promote active ageing. “My PhD research focuses on identifying, evaluating, and amplifying the impact of social innovations that promote active ageing,” she explains. Her work looks at initiatives built around social participation, connectedness, and well-being, using participatory approaches and data-driven methods to understand “what makes these initiatives successful and how their impact can be strengthened and scaled.”

Elisa Ertl, Doctoral Candidate at Politecnico di Milano is synthesizing academic literature, grey literature, and expert insight on embedding Data Science and AI in social innovation practice. Her goal is to understand “what works for whom and in what contexts,” and beyond that, to “uncover why certain conditions produce the change, or why they don’t.”

Anna Pasko, Doctoral Candidate at Glasgow Caledonian University researches the role of AI in enhancing social innovation in health and care for ageing societies. Her background bridges public policy, communications, and research, shaped by experience across Ukraine, Hungary, and Austria and work with organisations including UNICEF. “Data gains power when it is not only processed but also contextualized,” she says, “reflecting human experiences and helping to make decisions that make people’s lives better.”

Owen Soontjens, Doctoral Candidate at Ghent University is researching how to make muscle-strengthening activity more accessible and relevant for older adults. Having already explored what older adults know about and how they perceive this activity, he’s now mapping social innovations that promote it, aiming to “bridge the gap between these innovations and older adults, normalize muscle-strengthening activity within this population, improve accessibility, and increase participation.”

Andrés Felipe Zárrate, Doctoral Candidate at TU Dortmund University found excitement in the opportunity to connect to a multidisciplinary network. This helped making sense of how public sector actors, AI, and social innovation connect. “I would say a challenging process is bridging the key themes of my research into theory and practice,” he says. Working through international policy papers on public AI governance and grappling with what social innovation means in both research and practice, he recognizes a collaborative bridging should no longer be confined to the future but already unfold in the present to face challenges.

Kacy Lovelace, Doctoral Candidate at Glasgow Caledonian University discovered a practitioner-led mapping of the Data and AI for Good field close to her own. “For a brief moment, I wondered whether my study was redundant before it was finished.” A closer comparison showed the existing mapping missed the epistemic question her study centres on. “Rather than making my study redundant, the data.org mapping became evidence for why it was necessary. Sometimes the most useful discoveries are the ones that initially feel like threats.”

Vuk Dinic, Doctoral Candidate at Jožef Stefan Institute Slovenia pushes back on how AI tends to be framed. “While AI dominates the conversation today, it’s mostly framed in a business context, which is fine, but not enough,” he says. “We need to start applying the technology we already have to solve real-world problems and help more people.”

Akram Naoufel Tabet, Doctoral Candidate at Jožef Stefan Institute Slovenia focuses on forecasting and language technologies. After training in computer science in Algeria and a Master’s in Data Science and Analytics in the UK, his roles have spanned AI, NLP development, cybersecurity, and e-commerce. “By blending advanced analytics with an understanding of society,” he says, “I hope to create tools that not only predict outcomes but also help communities, policymakers, and organisations make better decisions for the common good.

… And what the supervisors think about DATAVYSTS:

Artur Steiner, Supervisor | Professor of Social Entrepreneurship and Community Development at Glasgow Caledonian University describes it from a foundational perspective: “DATAVYSTS connect specialist researchers, practitioners and policymakers to create impactful new knowledge about AI and how to use it for social good.”

Niamh Smith, Project Manager | Researcher at Glasgow Caledonian University wants the network to shift how social innovators relate to data. “We need to make data less intimidating and more useful to groups of people who are already working tirelessly to improve peoples’ lives and the environment,” she says. By collaborating directly with social innovators to understand their challenges, she believes technology can be tailored to enhance their impact and used ethically. “I want to see the Datavysts network create a significant mindset shift. Data and AI have real potential to help, not hinder, social innovation.”

Federico Bartolomucci, Supervisor | Junior Assistant Professor of Management Engineering at Politecnico di Milano wants social innovation methodologies to shape data science practice itself, making it “accessible, allowing a plurality of stakeholders to take part, breaking the barriers to data exploitation.” He hopes the network shows “that a different way of dealing with AI and data science is possible, and that when it’s done in the proper way, it can bring great societal benefits.”

Mitja Luštrek, Supervisor | Professor and Head of Intelligent Systems at Jožef Stefan Institute sees impact in changing how social innovators make decisions. “What we would like to achieve is that they start looking at raw data available to them in reasonably sophisticated ways, and that they generate their own data, analyse it and pick the way forward based on the evidence emerging from it.” As he puts it, “we need real-world societal issues, real problems, to apply it to, and this is what this opportunity gives us.”

Nikola Ljubešić, Supervisor | Professor and Senior Researcher in the Department of Knowledge Technologies at Jožef Stefan Institute frames the impact as a marriage of paradigms. “We have to develop a collaboration paradigm between social sciences on one side and data science and AI on the other,” he says, pushing back on the idea that social sciences are somehow lesser. The legacy he hopes for is “a new level of understanding of the complexity of societal processes, coupled with the technological capacity to empower this understanding.”

Katrin Bauer, Supervisor | Senior Researcher (Assistant Professor) at TU Dortmund University’s Social Research Center frames it as an overdue convergence. “We cannot look at social innovation and artificial intelligence as belonging to two totally distinct buckets, as two unrelated matters anymore,” she says. Investigating the relationship between the two, in either direction, is “what is in the DNA of DATAVYSTS, as basic as it sounds.”

Sebastien Chastin, Project Coordinator | Professor of Health Behaviour Dynamics: People, Places, Systems at Glasgow Caledonian University: For him, the motivation was structural. “The gap, the need for transdisciplinarity, and the possibility to inspire and train a new generation of researchers and leaders that would bring a new narrative to both AI/Data science and Social Innovation.” He wants the network’s legacy to be that new generation of leaders, people who can “define and demonstrate how we develop and use new technology in a wiser way.”

International Participation and Training

The Datavysts take part of monthly trainings online, where guest lecturers and our researchers teach state of the art research, practice and methods. This creates a network wide learning environment to collaborate on work and ideas across the network, making it a unique great learning space.

Our fellows have engaged in enriching international conferences and training that have broadened their perspectives, ideas, and contributed to disseminating their current research in the academic and organizational fields.  

Here, they let us know some of their experiences in their own words:

One of the most valuable experiences during my PhD has been participating in the Quality of Life Summer School: Digital Innovations for Happier, Healthier Ageing at the University of Geneva. Working in an international multidisciplinary team, we developed FlowForward, a digital solution to support people living with urinary incontinence, which was awarded first prize. The experience strengthened both my research approach and professional network  highlighting the value of international and interdisciplinary collaboration in addressing complex societal challenges. – Annette Botha, Doctoral Candidate at Ghent University.

Beyond presenting, it was inspiring to attend talks, exchange ideas, and connect with researchers from around the world. Grateful for all the insightful discussions, new connections, and memorable moments throughout the conference. – Akram Naoufel Tabet, Doctoral Candidate at Jožef Stefan Institute Slovenia.

The most exciting part of my research so far has been speaking directly with older adults about muscle-strengthening activity and engaging in meaningful conversations. I have travelled across Belgium to meet with older adult groups in person. Although there is quite the confusion and several misconceptions surrounding muscle strengthening, their interest and curiosity have been wonderful to witness. Some participants may initially be hesitant, but I have found that sharing evidence-based information and practical, real-life examples can significantly change how they view muscle-strengthening activity. – Owen Soontjens, Doctoral Candidate at Ghent University.

The Data CARE Festival at Utrecht University was one of the most genuinely distinctive academic events I have attended. I came away with connections and perspectives I would not have encountered in a more traditional conference setting. My research asks critical questions about what Data and AI for Good organisations actually believe, which sits productively in tension with optimistic narratives about the field’s potential. The conversations that emerged from that tension were exactly the kind of exchange the MSCA programme is designed to facilitate. – Kacy Lovelace, Doctoral Candidate at Glasgow Caledonian University.

I wanted to be a Datavysts fellow because I am driven by the desire to make academic research results more directly relevant and accessible to practitioners and communities. Coming from working on a tech enabled social innovation in the real world, as well as from tackling social inequalities in practice – I know firsthand that we must do a better job at bridging research and practice, as well as research and policy. Datavysts, and the MSCA fellowship more broadly, really allow me to conduct research, but also to complete a PhD, in a manner that is meaningful to me. – Elisa Ertl, Doctoral Candidate at Politecnico di Milano

I truly value the Datavysts as an international and multi-disciplinary network. From the monthly trainings in new fields of research methods, data science, and social innovation, to connecting with other fellow doctorate candidates, researchers, and people working in practice has been a learning experience. New friendships and collaborations have opened me to push towards social innovative research and has been a great setting to better understand from inter-disciplinary projects and a more hands-on and practical approach to research. – Andrés Felipe Zárrate, Doctoral Candidate at TU Dortmund University

The project is just in its early stages and there is a lot more to come. Our fellows and supervisors will have much more experiences to tell later on. To stay tuned, check in and follow, more information can be found on different DATVYSTS platforms, channels and social media:

LinkedIn: https://www.linkedin.com/company/datavysts-eu/
Monthly newsletter: https://datavysts.eu/join-the-reboot/
Blog: https://datavysts.eu/blog/