Shannon titled her talk “The Challenges of Continuous Adaptation: Citizen Science for a Changing World. Shannon is leading the Open Environmental Data Project. Her thinking is done with collaboration with a lot of colleagues over the years – and recognising them. What can we contribute to citizen science in a changing world? The Mississippi and Louisiana are known for their rich biodiversity, but also for being the largest concentration of the petrochemical industry, and her forming experiences are located in this landscape. She defines herself in the area between activism and policy and infrastructure influence and study. She is interested and focuses on how to create an organisational and project shift and understand how things change. Her trajectory started from understanding the problems that people face and the way they are addressing them. The experience started from working with the bucket brigade – this is socially situated data. The 2010 BP oil spill with a limit on data collection and the creation of the Public Lab – making aerial images to capture images with balloon mapping. Public Lab developed into a community of people that support different environmental monitoring. The hardware part of the activities, they started the Gathering for Open Science Hardware (GOSH) and thinking about open science hardware. This is an important part of science – open hardware. Her questions shifted towards one that values community input.
The open environmental data project focuses on thinking about the aspects of policy and processes and not only technical tools. There are big questions about a changing world – climate crisis, technology, biodiversity. Shanon reviewed the big changes between 2010 and 2023: internet, infrastructure, the commons, the influence and social media, AI, extreme politics and policy.
The internet in 2010 was still evolving and social media wasn’t standardised to the current degree, and there were opportunities to create resources, and then connect local action with data. Back then, it was a democratic space whereas it is now controlled by empires taking over huge parts of the internet (Amazon, Apple, Google, Meta). This complicates the environment.
Infrastructure – this can be physical and technical parts but also the people culture and institution. We spent less time understanding resource sharing and supporting community monitoring but there isn’t much attention to how projects work together and share information. Even the ability to get the funding is something that blocks communities from getting the data.
The commons – community-based management of common-pool resources (Ostrom) but many of the commons are polluted – so think about knowledge as a common. In a changing world how we can move to work on common environmental causes. Principles of organisations that allow for the management and new ways of dealing with exploitations and dis.
The influence is through social media and we don’t have the luxury of time to do citizen science that is not influential and impact. We need to think about how we support people to communicate and storytellers to change and engage with environmental issues. The Internet is now requires negotiating with platforms and the way they are doing
Artificial Intelligence (AI) is going to experience a fundamental shift, AI is amplifying the crowd in a new way, There are new ways of using AI in eBird, iNaturalist and other things. How AI will transform science and citizen science – is it about productivity or about democratising science and how focus on productivity will impact democratisation? How does AI affect inclusion and local priorities and values?
The extreme politics – move from belief in science for progress, there is now a significant population that is not accepting science. There is hostility toward science and problems with the political susceptibility of science policy. Impacts of changes in politics such as Brexit the UK, and the populist government in Argentina as examples in the attention to scientists. Citizen science needs to be prepared to operate in these extreme
Is citizen science expansive enough of the all-hands approach we need to address future challenges? There are examples of projects that are not seeing themselves in citizen science. Projects that use the commons approaches – such as the Internet of water coalition which is making water data sharable. Collaboration can create partnerships early, often and in unexpected places – the OpenTeam are a group that is doing it in agriculture management and helping support systems for farmers and agriculturalists. Including open practices that open up on dialogue frameworks – Zooniverse as an example. There are many examples in citizen science of open. Infrastructure first is an ew was of data to design and policy – the behind compliance network is working on designing environmental data. Diversity of voices that are being done in different groups – an example is Digital democracy that creates support for environmental defenders. We can also have local solutions which are thinking about grounded, local innovation – the CHARRS projects as an example. Epistemic innovation (Ottinger) o so thinking about epistemic justice and actions in the world. Trust and relationship building is important in citizen science (ELOKA projects in the Arctic) there is a need to create trust with the local communities. There is also a need to include learning and sharing experiences and there are places for new scenarios for learning such as the ARRIBADA initiative with tools that help in STEM activity.
With all the changes, what can we do to meet the moment: a framework of continuous adaptation. We need an evolutionary approach to continuous adaptation – the ability to adapt we need to mimic diversity, select the one that works, and amplify – so we can get better in selection and amplification. We adapt by being dynamically involved. The future is found at the fringe because it is comfortable in encounters that challenge thinking. The Open Science of tools led to think into the effort on the 2023 years of open science. Issues of data sovereignty in indigenous groups can impact communities. Finding cases for challenges are – they can challenge your present. It can challenge your identity. Dismissal ignores the encounter and sidelining and needs to work extra-had to overcome dismissal. Influence – if we want to do citizen science to influence society and policy influence need to take into account how to disseminate information widely and people who need to learn about what we are doing.
What do we need to continuously adapt – understand the new normal of discontinuity, find the unfamiliar and listen, learn and engage. Question what you want to transform with your citizen science. The future is in the curation of data and not only in creation. We need to learn to better curate. We do need to scale simple solutions and look where analogue designs that work better than technology. Common knowledge and data are important for addressing these challenges. A
A proper version of this talk will appear at Sdosemagen.medium.com
Q&A
Power conflicts and controversies – each situation is unique, and need to think about how to build bridges and dialogues and work with people who disagree,
Citizen science and generative AI – work is coming from small organisations and people who left corporations to ask how these technologies impact society. What does democratise science look like when it is about AI? Reaching these people and areas that work already on these issues should be involved.
Is it realistic to have open environmental data in a competitive, capitalist world? There is an effort to open data and open source, there is seeing SME and an economic component and competition is such that sharing the data that is used from the open public data is problematic? From activist data -we need to share it and we can’t address challenges with an all-hands approach. But if we think of a more common approach in terms of governance there can be a structure that can be put in place. There are cracks from just legal and licensing perspectives but we need to think about other mechanisms. Communities are asking about sharing data.
Funded by the European Union through the European Union’s Horizon Europe Framework Programmes for Research and Innovation under grant agreement No. 101058509 (ECS project). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.
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