ECSA 2016: Open Citizen Science – Day 2 (Afternoon)

The afternoon started with a packed session that focused on Citizen science Studies – Engaging with the participatory turn in the co-production of science and society Elevator talks & interactive session organised by Dana Mahr (University of Geneva); Anett Richter (Helmholtz Centre for Environmental Research – UFZ); Claudia Göbel (Museum für Naturkunde Berlin | ECSA); Alan Irwin (Copenhagen Business School); Katrin Vohland (Museum für Naturkunde Berlin | GEWISS); Sascha Friesike (Alexander von Humboldt University Berlin) (the morning notes are here)

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Dana – astonishment as a starting point: the six organisers – astonished by the scale of interest of public participation in science, which is different from Public Understanding of Science (PUS) in the 1980s or science for the people in the 1970s. There are multiple interpretation – from methods to contract between science and society 2.0. It is adapted to many areas of knowing – though it is happening across the Western world, from physics to patient interests. There are modes of participation and reflecting on epistemology, social history, either as actors or as critical sociologists, and studies of science. Why do we reflect on citizen science – do we have citizen science studies? They received 50 proposals. Finally they decided to have short presentations: the many papers in the session were broken to two sets of lightning talks – 5 minutes talk: who you are what you are working on, and what your interests. We need to organise people very well. The account here, therefore is only of one half of the session (so even in one session you can’t have the full experience!)

Citizen Humanities: Configuring Interpretation and Perception for Participation (Dick Kasperowski, University of Gothenburg, Sweden) Part of a project taking science to the crowd – understanding how the participants are being constructed. Several citizen humanities – like Zooniverse and elsewhere, usually link to interpretation, assuming that it is constructed through a long training and contextual knowledge. The participants are seen as annotators, transcribers – low-level of skills, they are being limited to automation. Project avoid inclusion. Focusing on perceptional quality of participants. Maybe turning participants and humanities into quantification.

Are the rhetorics of citizen science prohibiting detailed accounts of its own practice? (Christian Nold UCL, UK). Worked in an EU project and try to follow the devices of citizen science, and we don’t look at the technologies of citizen science. As a designer & artist look at the sensing devices in different way. Air quality, noise monitoring – the project are part of bigger agendas – actually link to IoT and there is something interesting that is doing much more things that it what is measured and why. When we take them to specific context (e.g. Heathrow) the gain specific agency ,they are redesigned constantly. There are implication to citizen science: if it is a design practice, we will end up with different outcomes, and valuation – being reflective practitioner about the whole thing: what does it mean to care for an app. There are ontological aspects – how they are built into the devices: new type of environmentalism.

The (Citizen-)Scientification of Society and the Pleasures of Research. Citizen Science as Science Communication (Sascha Dickel TU München, Germany). Sociological STS research – leader of a project on citizen science. He suggest the following hypotheses – citizen science is part of the scientification of society. Science as institution, culture, expand to many areas. This is education, mass media. Second hypothesis: citizen science is scientification by participation. Assume that the public take part in scientific research – there are incentives for professional people, but there are different motivations. Discourse frame the incentive to participation. Citizen science discourse is framed as meaningful leisure. Linking it to concept of deeper meaning – civic participation and fun. Citizen science expand research to private sphere and reinforcing science as an institution. But is it good or bad to progress with scientification of society? Why not do that? This was a point of discussion that raised interest in the audience.

Participatory turn’s legacy and the European ‘Responsible Research and Innovation’ emerging framework (Hadrian Macq University of Liege, Belgium). Hadrian is enthusiastic about citizen science, but as a PhD student who need to be reflective, he explores the normative aspects of citizen science in Horizon 2020 – the specific aspects that it is developing: public understand of science, public engagement and responsible research and innovation. They were criticised in the literature and there is a risk of closing down research. His research plans are to explore the political and economic context of citizen science at the EC. Research and innovation are reoriented towards economic growth to tackle societal problems. There is concern about engagement fatigue and assumption that research and innovation is driven by industry and academia, and sometime citizen science can be seen instrumentally by the commission.

wp-1463751452653.jpgCreating Communicative Spaces that nurture inquiry, reflection, and dialogue in citizen science (Cindy Regalado Univ. College London, UK); Zooming to the local level – looking both as community organiser in Public Lab: grassroots organisation, with following principles: engaging people as researchers; pull complexity off the shelf; built in openness into science as a social process – e.g. through kite mapping; collaborative workflows – either on the website with research notes, maintaining a data archive and face to face; protecting openness with viral licensing and celebrating local innovation. As a researcher, want to point 3 things: notice Arnstein about the real power to change the process, decontextualisation of success stories – as some of the discussion in the book The Participatory City shows.

Who are the citizens in citizen science? Public participation in distributed computing (Bruno Strasser University of Geneva, Switzerland) Bruno explores the citizens and citizen science. There are a whole range of practices that are called citizen science – but it changing the exclusion of amateurs participation in production of scientific knowledge after an era of lack of participation. They will look at India, China, Europe, and US. They will look at medical, DIY science, crowdsourcing. They will look at the discourse and the ideas about parts of science – they will also look at current and past phenomena and current ones – aiming to have biographies for 1m people who participate in citizen science. What is the political and social economy of citizen science? What is the kind of knowledge that is being produced?

Openness in biohacking: expertise and citizen science (Rosen Bogdanov Universitat Oberta de Catalunya, Spain). Researching biohacking and practices of openness in biohacking groups. There are issues of scientific expertise and there is less talk about that in citizen science. There are different types of expertise – interactional expertise, universal expertise – available everywhere. There are issues of keeping the relationships between types of expertise neatly separate. There is lack of scientific citizens. There are different practices of inclusion and exclusion within the community of biohackers.

Dingdingdong. Interferences with the Natural History of a Disease (Katrin Solhdju Vrije Universiteit Brussel, Belgium).  Historian/philosopher of science with interest in medial – part of Dingdingdong disease about Huntington disease. They address current imagination of the disease and defining as only tragic and prescribe the self-fulfilling prophecy of how it is experienced. They are trying to consider a better environment for the people who are involved – history of the disease, speculative narration, dance and choreography and more.

Observing the observer: Citizen Social Science and the Participatory Turn (Alexandra Albert University of Manchester, UK). trying to understand citizen social science, in social citizen science is more than usual participation and they are observe and analyse their information – beyond the usual practices of social science. Looking specifically at the mass observation archive, trying to understand the ethnographic methods – anthropology at home, which include observation and reporting. The mass observation archive brings questions about expertise, and what they view it at, and what the observers though that they can be involved as researchers. This is done within sociology. Hope to lead to interesting observation on the potential of citizen social science. She will follow several case studies, which are about critiquing the method.

What can Citizen Science learn from participatory research? (Tobias Krüger, Humboldt-Universität zu Berlin, Germany). From a cross faculty institute that look at human-environment relations. looking at participatory research – we can learn a lot from integrating literature. Build decision support tools for water quality, and done the model in a participatory way. Citizen science has the potential of setting what science will be done, and control over knowledge production. There are politics of citizen science engagement – who fund, who can hijack projects, and that lead to who’s knowledge count in the end.

Day summary

Summarising the day is challenging – 8 different sessions with different topics. Some of the reporting back include – John Tweddle – there are clear wp-1463753197409.jpgconservation impacts of citizen science: showing different approaches – from community led to university led to global databases. There are different ways, lots of different outcomes. Complex pathways. Observations – is citizen science support outcomes? evaluating is difficult but can be powerful demonstration. . Balancing highlighting the community led and working with local communities . Trying to balance autonomy with the need to have large datasets. Max Craglia – about technology: a lot of applications across many aspects – many were funded by EU data. All the data and software were open. Moving towards open source and data – starting to have critical studies of citizen science. Exploring the light pollution – there are issues that were above – issues were noted above about light studies. Session 8 – Alena Bartonova – wp-1463753211888.jpgthe topics that were looking at air quality, noise, quality of public spaces. and engagement, looking at the social aspect. Thinking about empowerment. In air pollution there are many tools and information that is available, but in each project they are forgotten and there isn’t continuity of use and application. There are technologies and users but there are problems in doing it together – lack of co-design. Lucy Robinson – The session on innovative science looked at mosquitoes, molecular bio, crowdsourcing research question of mental health. Issues of evaluation came up. Failure is equally important as success. Session on participatory social innovation – looked at the connection of digital social innovation and citizen science. Identifying difference – need to solve new societal challenges. Shared lessons and challenges: structure engagement, levels of participation, motivation. Need to think of actionable policy recommendation. Never just a question of providing participation and motivation, but also dealing with conflicting practices and values. Alan Irwin – looking at the participatory turn: there were many papers on critical studies of citizen science. Connecting up research community with practitioners – there are many reflective practitioners. Lots of cross over. Need to maintain space for the groups to get together. Balance of discussion on the nature of citizen science and scientification of society – which led to a lively discussion. What are the politics, what the modes of citizenship? Not all citizen science is good automatically and maintain these critical question. Education – specifically about schools and starting a new working group at ECSA, look at the specific needs.

ECSA GA: ECSA grow significantly since January with a lot of individual members after the conference. There is a new website, which you can get a preview, and it will be launched soon – we see the map of citizen science actors in Europe. Katrin suggested the strategy and plan for 2016/2017. The aim is to strengthen the ECSA community, and do that through the use of new websites and activities – maps that increase visibility, and empower local hubs and expertise. Starting to develop policy papers and having transparent governance structure, but now working on internal procedures. Aiming to make ECSA more integrative. The working groups are evolving – aim to appoint an internal community manager, improve external communication, make ECSA more independent from the Museum. The COST action on citizen science will assist in promoting citizen science activities across Europe. ECSA participate in DITOs and LandSense which will help in establishing ECSA well. The working groups are developing, but we need to identify more people who will progress on the best practice area – we start collating best practice guides. ECSA got guidelines for participating in European calls. New policy position papers: citizen science as part of EU policy delivery – looking at EU directive. The white paper on citizen science for Europe and EU wide citizen science programmes.

Following the AGM, we had a series of lightning talks as an opening to the think camp – the talks mixed participants in the Berlin science hacking community and people who came to the conference – and finally we experienced the Citizen Science Disco. I’ve welcomed this session with the demonstration, through the work of Leni Diner-Dotan on the Citizen Cyberscience nightmare wall that new and radical participation is possible in citizen science conferences.

Lucy Peterson explains the idea of hacking and science hackathons

Following this, Johann Bauerfeind describe the experience of the Berlin iGEM team

Byrke Lou, an artist who works on issues of science and the environment was next:

Cindy Regalado then describe the work of public lab

Kat Austen closed the lightning talks with chemistry hacking

The last part included a short intro to the ThinkCamp

ECSA2016: Open Citizen Science – Day 2 (Morning)

wp-1463763323886.jpgAfter the opening day (see morning and afternoon posts) and the reception under the dinosaur at the museum, the second day started with an introduction and review of day 1 by Marisa Ponti (University of Gothenburg, Sweden): We want to reconnect to the first day. Particularly happy to hear the connection at the European Commission (EC) level about the link of citizen science and open science. Indicators for success, and digital and other aspects of inequality were address. Today we have 3 keynotes, and that is followed by two four parallel sessions.

The keynotes were facilitated by Susanne Hecker (UFZ | iDiv, Germany) – we have several celebrations – including the birthday of the conference chair, and the success of conference with many participants.

Citizen science – innovation & inspiration for science, Rick Bonney (Cornell Lab of Ornithology (CLO), USA), Rick has been working in the Cornell Lab of Ornithology for 42 years, and he started many citizen science projects in the lab. The end outcome for his work are projects like eBird which receives 18,000 checklists a day – eBird can provide specific location and see what was happening and you can report opportunistic or systematic effort. You can report what you’ve seen – the list is automatically checked, and the filters that decide which list you can see is operated by many volunteer editors. This helps in managing the quality of the data – since 2002 they had 300K users, 250mil observations – 98.5% world’s species.  Because the checklist is smart, it is telling us if we recorded everything that you’ve seen or not, this provided the data for statisticians that can do the STEM model for distribution of species. They can see the routes of travel and discover routes of migration – e.g. over the ocean – which was not known to ornithologists before the data was available. Lots of papers are coming out, including about climate change impact. There is also analysis to support the location of creating wetlands to support migratory birds. The data is open and allow people to use it for many purposes. There are also survey of people who use the data – from law and policy, habitat protection and site and habitat management.

There is evidence for effective conservation. The eBird data is used for the state of bird population and ways of exploring the data – it is being used for education with a range of lesson plans. There is also an effort to increase cultural diversity of participants. CLO was one of the first organisations that include citizen science in its mission. This links to the history of the lab that was always working with volunteers observers, since it was founded by Arthur Allen.

Here it gets personal: Rick’s dad encourage him to be interested in birds and the environment, and he done analysis of Christmas Bird Count – he done diary of birds, and he managed to discover things that other people didn’t know. He joined the lab in 1972, and that led to analysis of Christmas Bird Count. After graduation he worked as Volkswagen mechanic and other jobs, and started working on the Living Bird magazine and found many things about the nest watch study. They started noticing impacts on citizen science. They developed different programme – e.g. FeederWatch that allow people to learn about the birds in addition to the data collection. So they have developed programmes – from Nest Record Card in 1965 to eBird in 2002. Citizen Science allow to track infectious disease, understand forest fragmentation impact that led to guides to forest manager. There were many other people doing work with citizen science – the number of peer review publications are appearing. Theobald et al. 2015 show that citizen science is contributing to many areas – many people, high financial value, and many peer review paper. The important aspects are: design and evaluate effectively, ‘own’ citizen science, diversity and inclusion and collaborate. there are different guides for citizen science and tool-kits.wp-1463763362078.jpg There are different terms that are being used – civic science, volunteer monitoring, traditional knowledge – but the concept is being recognised and it get traction – we need to own and embrace the term. Without a common term, it is impossible to quantify the impacts. The third point is diversity & inclusion – many community know things that we don’t know. The is an importance in collaboration – Finn Danielsen 2013 show that many indicators for international treaties can be done through citizen science. Rick hope to develop an eFish project next.

10 Principles of Citizen Science (Lucy Robinson – The Natural History Museum London, UK). The term Citizen Science was not used in the UK in the past but gain acceptance – she described the Natural History Museum, and through the Open Air Laboratories (OPAL) programme they secured commitments from management and it is central to their work. They have different project through different means – about 10 projects.

wp-1463763376254.jpgThe ECSA working group on best practice have developed the 10 principles which was an internal deliberative process. We were able to create them, and share them. Why are they needed? the term citizen science became a buzz word, and it create many opportunities, but also require challenges to agree on common concept and not use ‘we should’ – we don’t want standards – we want it as a flexible concepts which can be applied in diverse situations and disciplines – but we do want to have good practice. The principles are for inspiration, support, principle of good practice. She then gone through the 10 principles: The first principle is actively involve citizens, and there are many photos of people involve locally and the principle usually met. Second, we want to have real science, as Rick demonstrated – many peer reviews publications, but this is not the only output: from identifying pollution and acting on it, or other similar things. Third, thinking about who benefits – need to be mutually beneficial. Many benefits are varies and different between actors – we need to evaluate these impacts – but this is squeezed many times. wp-1463763396794.jpgThe #WhyICitSci during the Citizen Science Association conference in 2015 demonstrated the benefits for practitioners. Four, there are smaller scale projects that allow people to engage in multiple stages of the process if they wish to. Fifth, we need to ensure feedback – it’s motivate people, feedback can be newsletter, maps, emails but personalised feedback is important – and can we be more creative. For example in LA they carry out meetups. Sixth, it is about understanding it as a research approach, and the data quality issue of citizen science is addressed – are we do in it enough to address the concerns. Need to remember that it is a research method. We don’t need perfect – high-quality data. We also need it fit for purpose. Seventh, need to make data and metadata open – in practice, this doesn’t happen for many reasons. Eights – we need to acknowledge the citizen science in project results and publications – in one case a project listed 37,000 co-authors (with only 10 professional scientists). Ninth, evaluating citizen science for their outcomes – this is something that can be squeezed out – evaluation require careful thinking what was the purpose of the project. Need to think in advanced about what success mean. Finally, considering ethical and legal considerations of the activity. The principles are translated to many languages – in 17 languages and 3 more in preparation. There are now news guides for citizen science. We are now an international committee – we have 300 people in the room who are presenting thousands of citizen science projects. What should be the eleventh principle?

My talk, Participatory Citizen Science, is available in a separate blog post. 

Some of the reaction on twitter:

Of the four parallel sessions that were on offer, I followed:

Worldwide citizen science initiatives on light pollution –  organised by Franz Hölker & Sibylle Schroer (IGB Berlin, Germany )- usually, life for millions of years was dark, but humans started to illuminate the night, and many species are not ready for it. There are good reasons for the lighting of the night but aalso problems. The area of research into light pollution is an interdisciplinary area, and we need to explore it from different perspectives.

How reliable is data produced by citizen scientists? (Chris Kyba – GFZ Potsdam, Germany). Chris discussed reliability – scientists are specific about calibration and acceptance of tools – e.g. Sky Quality Meter is called ‘Kindergarten toy’. Citizen science is ‘gimmick’ to get proposals funded – but that is not true any more. The disappearance of stars in the sky you can tell how much light there is. We are daytime active animals – satellite are no sensitive to blue light from LEDs, so satellites can’t capture all lights. The Globe at Night is being used around the world, and there is a paper Kyba et al. (Sci Rep 2013) – there is good correlation, but data is broad. The app guide you to look at specific area of the Sky – there is relationship between number of observations and the agreement with the data – more observations make people more confident. Data is quantitative and there is a method to check for accuracy. There are environmental variability (humidity, dust) there is also shot-to-shot variation and person-to-person variation. Trying to solve it through community experiments, and flashmob for science, and do repeated observation one after the other. With MyGeoss, they created a portal to give it to scientists and allow people to understand trend analysis from different projects.

Cities at Night: ISS pictures to trace the environmental impact the light pollution
Alejandro Sanches Universidad Complutense de Madrid, Spain. There are impacts of light pollution. There is an ESA mission specific to without calibration – these are the ISS pictures by astronauts. There are tools like DMSP/OLS, VIIRS/DNS but they don’t have proper reolution as the ISS/D3S/RGS is in better resolution and ability – (Aube 2013 Plos one 8(7) e67798). There are simulations of change for Montreal for the changes in lighting – so can see impacts from increase from 160% to 44% according to different illumination techniques. There are also maps of specific places – e.g. Milan, Berlin (noticing the two parts)

From an interdisciplinary science community to citizen science (Sibylle Schroer IGB Berlin, Germany). She looked  at Carbon Sinks – ocean, forests and crop-land – there are impacts from cows and animals. There are significant impacts from agriculture – but what about lakes, light and GHG? Inland waters are active in global C cycle – one fifth of emissions are coming from inland water. There are anthropogenic drivers that increase temperature, carbon input, nutrients – but what about night-light? They done lab experiment and the artificial light at night influence Diatoms – shift in metabolism. This allow to calculate the impact of the 2.4% land area in Germany that covered by water – outside the lab what is going on. So the only way to do it is through citizen science, and evaluate the impact of artificial light – impact of village of agriculture activities – very complex package. Creating sampling package and options of recording by app or questionnaire, and then send it off.

wp-1463763538483.jpgCrime Scene German Inland Waters: On the Track of CO2 K(atja Felsmann IGB Berlin, Germany). River areas are important as explained in the previous talk. There was a specific COST Action LoNNe which run 2012 – 2016.She was involved in research that took information from 635 sites – 192 streams, 609 questionnaire about night-time. Satellite data is only about light that go upward, not the blue spectrum. There are very good observations – with qualitative comments that help to understand the impact of light situation. At the COST Action ES1204 include people from many areas – there is a small community from in stars4all they try to reach out to many more people – citizen sensing and gamification – there are many initiatives and the question is about creating self-sustained networks and challenges of communication.

wp-1463763433804.jpgWorld Café:  1 round of discussion instead of moving between tables. There are three hosts: potential and limits of CS for research; skills needed to create self-sustainable platform. – EU project STARS4All is relevant here.

The idea is to sustained the network over time. Maybe similar lessons from Moon watch project in the 1950s. In the water project, participants  that they will give them information about the water quality, they didn’t realise that it is about what the researcher learn. Another reason for success is a very good communication – the reason for continuing funding is not the good science, but because of the science – log with owl. Misconception of getting the data – is local impact. Motivation – in Alzheimer research UK they had a very successful game, but need to understand motivation of doing a game for the game, or is it about the motivation to help science. There are ways to encourage people to do more through competition but should be careful about the unintended competition. Interest in the results and personal aspects – need to identity. In Galaxy Zoo – this can be even volunteers that help other volunteers. There is scalability challenge of dealing with more and more volunteers. The most important words : motivations , cooperation.

In terms of quality – is to improve it from the start through training. Selecting people according to skills – send people as control to try to see if you get bias. There are issues of funding to get project going over time. Having a lecture, and then do the activity.

 

Participatory [Citizen] Science

Citizen Science as Participatory Science‘ is one of the most popular posts that I have published here. The post is the core section of a chapter that was published in 2013 (the post itself was written in 2011). For the first European Citizen Science Association conference I was asked to give a keynote on the second day of the conference, which I have titled ‘Participatory Citizen Science‘, to match the overall theme of the conference, which is  ‘Citizen Science – Innovation in Open Science, Society and Policy’. The abstract of the talk:

In the inaugural ECSA conference, we are exploring the intersection of innovation, open science, policy and society and the ways in which we can established new collaborations for a common good. The terms participation and inclusion are especially important if we want to fulfil the high expectations from citizen science, as a harbinger of open science. In the talk, the conditions for participatory citizen science will be explored – the potential audience of different areas and activities of citizen science, and the theoretical frameworks, methodologies and techniques that can be used to make citizen science more participatory. The challenges of participation include designing projects and activities that fit with participants’ daily life and practices, their interests, skills, as well as the resources that they have, self-believes and more. Using lessons from EU FP7 projects such as EveryAware, Citizen Cyberlab, and UK EPSRC projects Extreme Citizen Science, and Street Mobility, the boundaries of participatory citizen science will be charted.

As always, there is a gap between the abstract and the talk itself – as I started exploring the issues of participatory citizen science, some questions about the nature of participation came up, and I was trying to discuss them. Here are the slides:

After opening with acknowledgement to the people who work with us (and funded us), the talk turn the core issue – the term participation.

https://www.google.co.uk/search?q=sherry+and+george+arnstein
Sherry Arnstein with Harry S Truman (image by George Arnstein)

Type ‘participation’ into Google Scholar, and the top paper, with over 11,000 citations, is Sherry Rubin Arnstein’s ‘A ladder of citizen participation’. In her ladder, Sherry offered 8 levels of participation – from manipulation to citizen control. Her focus was on political power and the ability of the people who are impacted by the decisions to participate and influence them. Knowingly simplified, the ladder focus on political power relationships, and it might be this simple presentation and structure that explains its lasting influence.

Since its emergence, other researchers developed versions of participation ladders – for example Wiedmann and Femers (1993), here from a talk I gave in 2011:

These ladders come with baggage: a strong value judgement that the top is good, and the bottom is minimal (in the version above) or worse (in Arnstein’s version). The WeGovNow! Project is part of the range of ongoing activities of using digital tools to increase participation and move between rungs in these concept of participation, with an inherent assumption about the importance of high engagement.

Levels of Citizen Science 2011
Levels of Citizen Science 2011

At the beginning of 2011, I found myself creating a ladder of my own. Influenced by the ladders that I learned from, the ‘levels of citizen science’ make an implicit value judgement in which ‘extreme’ at the top is better than crowdsourcing. However, the more I’ve learned about citizen science, and had time to reflect on what participation mean and who should participate and how, I feel that this strong value judgement is wrong and a simple ladder can’t capture the nature of participation in Citizen Science.

There are two characteristics that demonstrate the complexity of participation particularly well: the levels of education of participants in citizen science activities, and the way participation inequality (AKA 90-9-1 rule) shape the time and effort investment of participants in citizen science activities.

We can look at them in turns, by examining citizen science projects against the general population. We start with levels of education – Across the EU28 countries, we are now approaching 27% of the population with tertiary education (university). There is wide variability, with the UK at 37.6%, France at 30.4%, Germany 23.8%, Italy 15.5%, and Romania 15%. This is part of a global trend – with about 200 million students studying in tertiary education across the world, of which about 2.5 million (about 1.25%) studying to a doctoral level.

However, if we look at citizen science project, we see a different picture: in OpenStreetMap, 78% of participants hold tertiary education, with 8% holding doctoral level degrees. In Galaxy Zoo, 65% of participants with tertiary education and 10% with doctoral level degrees. In Transcribe Bentham (TB), 97% of participants have tertiary education and 24% hold doctoral level degrees. What we see here is much more participation with people with higher degrees – well above their expected rate in the general population.

The second aspect, Participation inequality, have been observed in OpenStreetMap volunteer mapping activities, iSpot – in both the community of those who capture information and those that help classify the species, and even in an offline conservation volunteering activities of the Trust for Conservation Volunteers. In short, it is very persistent aspect of citizen science activities.

For the sake of the analysis, lets think of look at citizen science projects that require high skills from participants and significant engagement (like TB), those that require high skills but not necessarily a demanding participation (as many Zooniverse project do), and then the low skills/high engagement project (e.g. our work with non-literate groups), and finally low skills/low engagement projects. There are clear benefits for participation in each and every block of this classification:

high skills/high engagement: These provide provide a way to include highly valuable effort with the participants acting as virtual research assistants. There is a significant time investment by them, and opportunities for deeper engagement (writing papers, analysis)

high skills/low engagement: The high skills might contribute to data quality, and allow the use of disciplinary jargon, with opportunities for lighter or deeper engagement to match time/effort constraints

low skills/high engagement: Such activities are providing an opportunity for education, awareness raising, increased science capital, and other skills. They require support and facilitation but can show high potential for inclusiveness.

low skills/low engagement: Here we have an opportunity for active engagement with science with limited effort, there is also a potential for family/Cross-generational activities, and outreach to marginalised groups (as OPen Air Laboratories done)

In short – in each type of project, there are important societal benefits for participation, and it’s not only the ‘full inclusion at the deep level’ that we should focus on.

Interestingly, across these projects and levels, people are motivated by science as a joint human activity of creating knowledge that is shared.

So what can we say about participation in citizen science – well, it’s complex. There are cases where the effort is exploited, and we should guard against that, but outside these cases, the rest is much more complex picture.

The talk move on to suggest a model of allowing people to adjust their participation in citizen science through an ‘escalator’ that we are aiming to conceptually develop in DITOs.

Finally, with this understanding of participation, we can understand better the link to open science, open access and the need of participants to potentially analyse the information.

ECSA 2016: Open Science – Policy Innovation & Social Impact (Day 1 afternoon)

See the first post of the day here. After the afternoon break, the second panel was dedicated to started with Innovative approaches to civic engagement, learning & education

Michael J.O. Pocock (Centre for Ecology & Hydrology, UK). Defined himself as an ecologist who is interested in citizen science. He is interested in ecosystem services and finding ways to engage people and communicate the ideas and imporance of nature to people – and that is why he created ‘hypothesis led citizen science’ in the Conker  Tree Science project. The project includes ecosystem services, invasive species and other ecological discussions within the interaction between the participants and the scientists, so it got an element of education. Challenge is evaluating if the educataional benefits that are assumed to be happening do materialise. Michael also shared the experience from the Biological Records Centre, which has been working for 50 years with different groups of volunteers and enthiasts for identifying species. BRC provide support through infrastructure, but the communities are learning and developing themselves. Meaningful interactions in the Conker Tree Project: we can have mass communication, but the mass participation allow deeper engagement. Also there are questions that are coming from the community of the people that were involved, but when the project team asked ‘what research questions should we address next?’ there was no response from the thousands of participants. However, direct emails and contacts raised research questions, but the level of engagement in this part of the project was limited.

The cost benefit report is here

wp-1463667959231.jpgDavid Weigend (Haus der Zukunft, Germany) – at the house of the future, the reality lab is a lab to allow people to create their own future. They want to enable people to share the future. Societal issues that they are exploring today are complex – such as data security – so their approach is to through their process that lead to creativity and exploration. For example, thinking about apps that help people to see what information is being collected about them over one day, so they can think about the implications and discuss them with facilitators. The type of engagement that they are trying to achieve is hard and they can reach about 50 people face to face, but aim to have apps and tool-kits to allow more people to be involved – e.g. through games which helping to understand issues.

Isabelle Arpin (IRSTEA, France). As a sociologist, she research citizen science – in her case the experience of gardeners from Grenoble, which were involved in a project about management based on insects instead of pesticides. The city wanted to convince the gardeners that the approach was appropriate management approach, but gardeners in the city were complaining about the use of insects. The citizen science was means to convince gardeners that the approach was valid. They were trying to show that they’ll experience more butterflies in the gardens. There was a clear evidence of change for the gardeners in their personal and professional life. The gardeners were not highly educated but as they were very engaged in the project, they learned more about insects. It’s not spontaneous to notice things (e.g. attention to insects). Therefore, we need to think of technologies of attention that make people aware of new things in their area.

Marie Céline Loibl (Sparkling Science Austria, Federal Ministry of Science, Research and Economy, Austria). The research of citizen science in Austria – well funded range of projects of involving people in many fields of work, and the scope have engaged many organisations: 450 schools, over 50 universities with interest to work in authentic research situations. It’s about offering people to fund research but only project that can students can be actively involved and do. Most students are involved because of guidance by teachers, not only by the students themselves, volunteering people – but all the projects have difficult phase in the middle of knowing how to go through the project, but when it works it is amazing.

Mike Sharples (The Open University, UK). The Open University is about inclusive research and education, and they have been working to allow people to do open inquiry trough the project nQuire-it where people can create missions and proposed investigations. On the platform it is easy to create a session and then using mobile phones as the measuring device. The app unlock sensors on the phone and see link between air pressure and precipitation. The professional scientists can have a role in nQuire-it – engaging professional and creating sustainable community is a challenge. You need to moderate and facilitate an inquiry to make it both sustainable and successful, and without it it will not be successful Experts can help in understanding calibration, data reliability and more. Another project of the platform is about birds and relationships to noise – which is an example of open question in the science, but there is value in the learning.

Question – Which budget should be used: research money or public engagement funds? Marie is using official government money with big investment, the open university are getting money from research, trusts, volunteers and more. Michael get funding from the government research and others. Is it possible to get ‘research money’ to do citizen science? The FWF in Austria started providing additional funding for citizen science for projects. This is also happening also at the H2020 level. Michael – citizen science is quality science but perceived as risky, and make research funders reluctant to invest in it. Looking at cost and benefits of citizen science, which was challenging. There are risks but the benefits are especially big when it works. There are also innovations that helped the EU.

How to measure engagement? is it quantity or quality? Marie – in Austria they offered awards to citizen science activities to encourage the incentives carefully – to make sure that data is valid. There are issues about quality of conversation and check that they lead to shared understanding – e.g. how you calibrate instruments. Looking at the conversations and outcomes. David – quality of engagement should be the top. There are challenges and funders sometime want to see high number of participation. Isabel – the importance was the engagement of gardeners was about quality and not quality. It is important to have trust and not just forced to interact with highly educated people.

Is citizen science about generating new science in civic engagement or engagement. Mike – they try to learn good science and good learning. David – the open agricultural project of MIT is carrying a message of decentralised agriculture and also doing good research Michael – citizen science is central to my work, but it is not possible to do the science without that. Equally, engaging with people give benefits to both side. The worst words in citizen science are ‘they should’ towards participants. Marie – there is a need to integrate both. Isabel – there can be a focus on engagement that also lead to science.

Citizen Science strategy and impact development in Germany – Aletta Bonn, Katrin Vohland. They shared the experience in Germany in development of citizen science strategy. there were hopes from government, NGOs and researchers – thinking about the added value of citizen science. The project funded by the ministry of science and education. They created a platform that share citizen science projects, providing events, interaction, discussions etc. Key insights: there was a question about the definition of citizen science – need a clear definition, but keep it open. At the core, these are questions about cooperation and participation and what conditions are needed for it. There is mutual learning which is under exploit area. The results is a green book with the strategy. A video show the details participatory process that they went through to arrive to the paper.

Some core issues in the consultation includes: fairness in participation process, sustainability of collaborative activities, and move towards responsible research and innovation. People comments include fun but also ‘science should be accessible to everyone’. There are in position papers different views of where citizen science fit. In the institutions, researchers thought that it should be in data collection and maybe dissemination. but civil society organisations seen a much wider role – less in design, but everywhere else. The recommendation include strengthening existing structures: networking, funding instruments, citizen science training and volunteer management, and synergies with science communication. Understanding different roles. There was also a recommendation to think of new structures – building a culture of valuing citizen science in society, science and policy. We need data quality and data management and the last recommendation is to integrate citizen science in scientific processes, in education and in decision making. They aim to move from green to white paper.

17:00 Citizen Science as an input for better policy formulation & implementation Chairs/Organisers: Jose Miguel Rubio-Iglesias DG Research & Innovation, European Commission, & Susana Nascimento Joint Research Centre – JRC, European Commission New order of panelists

Lea Shanley (co-Execuctive Director, South Big Data Innovation Hub at Renaissance Computing Institute (RENCI), University of North Carolina-Chapel Hill, USA). Lea experience from tribal mapping to policy engagement in washington. In 2010 she looked at public involvement in managing NASA assets. There is a citizen science act to help federal agencies to get hrough it – basic legislation that give authorisation to agencies to do what they want to achieve. These were concepts that work in the senate, but then reachign out to 60 organisations and people and then integrate the results into the legaslistic process

Roger Owen. There is a distinction between participation and citizen science. There is a long tradition in the UK of using citizen science data for decision making, but if we want to get into behaviour change, we need better dialogues and enagement. This is indeed top down – EPAs know what they got to do, and they tend to commission top-down process, but then they need to also thinking about other observers and what they are interested in, and we need to feed back what they are doing with data and how it is used in decision making

Christian Herbst (Deputy head of Strategic Foresight and Science Communication, Federal Ministry of Education and Research, Germany). The interest started from science communication perspective during the year of science. The ministry see citizen science as part of science communication. The coalition treaty stated that it should bring participation and science communication together. Bringing society and science together – involve more people in science. We need quality and quantity – we need to involve a lot of people. We need to have dialogues with citizens about science and need to initiate decision making process, co-design and co-production can be integrated in decision preparation phases – that’s an area for citizen science now.

Sven Schade (Joint Research Centre – JRC, European Commission). JRC is an internal science service for the EC. The process that the JRC done was to look at data driven information. They started in 2012 to look at crowdsourced data, but then more and more citizen science. They have just published a report about data management in citizen science – over 120 projects, and most in the environmental area. They are now moving to look at the way citizen science can be used to influence decision making. It doesn’t influence the process.

Elena Montani (Policy Officer, Knowledge, Risks and Urban Environment Unit, DG Environment, European Commission). Policy making is slow, especially when new technologies emerge. So they are reflecting on how they can integrate citizen science in decision making process. There is big potential: behaviour change, economics – showing that it will be cost effective, there are no success stories at member states to integrate into a wider framework. There is environmental knowledge community, and exploring how new forms of knowledge are emerging – looking specifically about Nature 2000 areas. They accept the challenges and also other opportunities . Apps are easy to use about noise, but they can be contradictory to official records, so need to consider how to reconcile these forms of data collection.

Lea – they are building on the long work of Cornell Lab of Ornithology, and the federal government agencies there were a range of interest across the board – but they found agency staff that were interested, but didn’t know what to do. They began by linking champions through the federal community of practice – with funding from the Sloan foundation, the commons-lab in the Wilson center commissioned studies to deal with barriers – data quality, privacy, costs and created case studies approach. Also a set of case studies that demonstrated success. The ‘new visions on citizen science’ worked well to promote attention – getting high level support to such action. There is risk averse approach at federal agencies, and working through high level bodies such as the White House allowed the development of list of tools, and get their commitment – have executive on record that it is permitted.

Jan-Martin – we need to educate policy makers about the need to integrate citizen science. Sven – there is another level in the EU – the 28 member states have their own understanding, culture, approaches, regulations and systems. There are plenty of success stories at the national level across the board. Christian – although government provide funding for governmental guidelines, but in the end, but there is a need to listen to people and understand more about citizen science. Citizen science is about getting involved with science, which will influence scientific decision making. There is scientists opposition to citizen science – see it as a danger. Jan-Martin – use of citizen science for data collection – to what degree can they use the information for decision making, Roger – the anglers monitoring initiative show us that the aggregate data does provide early warning to the professionals. Data can be filtered and use properly for decision making. Sven – there are ways to measure lakes in Finland that provide new information that can be tested. Lea – in the federal government they talk about augmenting and filling the gaps, not about replacing. Elena – the EU is interested in encouraging participation – as part of Aarhus convention. Roger – air quality as a method to engage people and see how policies are in terms of effectiveness. Elena – They are potential that cannot be ignores . Sven – at different levels there are different needs and approaches. Christian – participation is different at different levels: local, regional and national.

Can citizen science help us in understanding the how? Roger – yes, it give us an understanding of how to do things not just in what. What do we need to tell policy makers? Elena – how the data that is provided can be integrated into their policies, and need to be reassured that it is comparable, and also what it brings to society – need dialogue: there is utilitarian approach from institutions to reduce cost of data gathering. Lea – another way of understanding what the citizens want, understanding of improving the missions of the organisation. Link the priorities to the interests of the policy maker. Sven – the opportunity is part of the digital single market as an entry point. Christian – there is also the potential of social innovation. Give new ideas to policy makers. Roger – regarding standards for citizen science, not simple, but SEPA develop the choosing and using citizen science guide. Sven – in basic services there are interoperability standards, Lea – for some data need to match standards. ECSA already published two policy paper. Questions to the audience: what are the experience of working with policy? what tools help with that? Christian – how many think that citizen science is about impact on policy making – an aspect but not the only. Roger – success of citizen science is about changing people behaviour – quite a lot of people.

Last question: one term – inequality: participation, opportunity, knowledge. Christian suggest that every citizen science should include dealing with inequality. Roger – interest in reaching hard to reach and marginalised communities, through dealing with housing association. Alena – citizen science is about dealing with inequality. We cannot field the gaps without full participation. Need to empower people that are not empowered. Christian – very important issue, as people across Europe are opposing political systems. We need to engage more people in scientific processes. We need spectrum of projects. LEa – pariticpatory mapping community have done that for many years, giving people a seat at the table. They reached out to groups who are doing social science data. Sven – citizen science is one approach but it can be used to help with inequality. Lea – there is also controversy about citizen science.

Aletta – observations: we had an inspiring day and we can think of new questions that are being asked and how people in the conference and outside the society address them. The diversity of the field is very rich in experience and knowledge. It is exploding on twitter (and there is this blog). There are new books emerging about citizen science.

Following the day a reception at the Natural History Museum and three rounds of discussion tables under the dinosaurs at the entrance to the museum…

 

ECSA 2016: Open Science – Policy Innovation & Social Impact (Day 1 morning)

wp-1463648689152.jpgThe 19th May 2016 was a special day for the European Citizen Science Association, with the opening of the first conference of the organisation, focusing on the links between citizen science and open science. 

You can find the report on the afternoon of the first day, second day (morning, evening), third day, my talk at the conference, and the ThinkCamp challenge, elsewhere on this blog.

Aletta Bonn opening ECSA2016The opening of the conference was by the conference chair, Aletta Bonn (Helmholtz Association | German Center for integrative Biodiversity Research (iDiv) – GEWISS). Aletta welcomed everyone to the conference, exploring the balances between science, technologies and inclusion, and use of the information is central to citizen science. We have 350 people that came from different countries, organisations and projects to discuss citizen science. In Germany, there is already a working document that aim to support citizen science. In 2013, the German coalition agreement declared ‘we want to develop new forms of citizen participation and the communication of science‘ – the ministry of science newsletter this week is focusing on science for all as its theme. in this conference we have three full days. The first day dedicated to policy impact and social impact – we will have different ways to work together. The second day is about scientific innovation – we have almost 100 posters, and the breaks are opportunities for people to talk with other people and create new connection, the third day is open to the maker community in Berlin – celebrating success in many projects. We have an unconference programme in the thinkcamp to allow this openness. We have the citizen science disco on the second night, and a citizen science festival – linking to the activities of ECSA in Barcelona last year when we had citizen science safari. We had a big conference committee and many people where happy to help. The people who run the effort to make the conference happen led by Susanna Hecker and Ogarit Uhlmann. During the conference we will also have the launch of the new citizen science journal and also a joint book is in the planning.

Katrin Vohland (Museum of Natural History Berlin – GEWISS, Vice-chair ECSA). She noted that citizen science is now a global movement. Institutionalisation is a signal for development of the area, with ECSA, CSA (US), ACSA (Australia) and also networks in China, New Zealand, and other places. There is also coming together on identity in the principles of citizen science.

Citizen science should be part of identity of democratisation, European culture of joint effort and collaboration. Citizen science also go through professionalisation – we exchange not only experience, but we also think of social and political impact. Citizen science gains discursive power in the scientific and political arenas and  that is important to be taken seriously. While we are getting over the issue of trusting data, other issues emerge – there is no trade-off between freedom of academic research and citizen science but some researchers think so. We can see links to policy, and to responsible research and innovation. ECSA members jointly developed a strategy : promoting sustainability, developing a think-tank for citizen science, and developing methodological best practice. We want to see marginalised groups joining in participatory science. Citizen science can also help migrants to join citizen science. There are now H2020 projects that ECSA is part of them  – among them DITOs which links the dots in citizen science.

Roger Owen (Head of Ecology, Scottish Environment Protection Agency). For environmental protection agencies (EPAs) there are clear goals – to regulate, but also establishing partnerships, raising environmental awareness, and building up the evidence based – this is important to other people who act on the environment. This is also an opportunity to assess the success of policies. For EPAs, public engagement helps in raising awareness, engagement, getting data. In the range of tools that are available to EPAs, there can be expert assessment that is very expensive – and citizen science is cost-effective. Activities in Scotland include meteorological observations with many volunteers and over 650 anglers that do ecological assessment of streams. SEPA is also developing apps, and they commissioned a guide for the best use of citizen science for EPAs, There is now a network through the EEA to engage in citizen science activities: well design citizen science assist policy formation, provide monitoring data and evidence, serve as early warning, harness volunteer thinking, work across scales and more. EPAs can provide data and infrastructure, access to technology (e.g. apps), provide best practice guidelines, help with funding. The EPA network want to understand the success criteria and lessons from initiatives. The EPSAs also want to understand motivations and incentives so they can work better with citizen science. They also want joint and complementary ECSA/EPA network activities across Europe.

The next talk: Citizen science – Connecting to the Open Science Agenda was given by Jose-Miguel Rubio (Policy Officer at the Directorate General for Research and Innovation of the European Commission. on behalf of John Magen).

He aimed to provide the policy context for open science. One of the major drivers for open science is the digital single market (with support from commissioners Ansip, Oettinger, and Moedas). The research and innovation team of the EU is central: Moedas stated: ‘help us ensure citizen scientists contribute to European Science as valid knowledge producers by 2020′ during the open science conference in April 2016. By open science, we mean the transformation and opening up of the scientific process, through collaborative work that is facilitated by innovative information and communication technologies. We see shift from only publications, to sharing knowledge through the web: it makes it more efficient, transparent and collaborative. The benefits that are expected – good for science (efficient, verified, transparent), economy (access and reuse of scientific knowledge by industry, and good for society (broader, faster, transparent, and equal access to it). The open science evolved from public consultation that started 2 years ago – on science 2.0. Policy recommendations include the need to support citizen science platforms, and support its development. 5 broad policy actions which include citizen science in them – creating incentives, removing barriers, promoting open access, developing open science cloud, and embedding open science in society. citizen science is appearing in the top level ambitions. Citizen science is embedded in specific approaches by research funding, making it linked to society. There are several activities that relate to citizen science and public engagement. Seeing citizens are many roles: scientist , consumer, decision maker, user of data. In H2020, which is much of the biggest funding programme for science in the world, including citizen science – through open access. Examples for the activities are the collective awareness platforms for social innovation and sustainability (CAPS programme) including bottom up activities. There is also reports about citizen science – the white paper of Socientize, and the UWE report on environmental citizen science, there are the Citizens’ Observatories projects including 5 FP7 projects, and 4 new projects that start next year – LandSense, GROW, GroundTruth2.0 and Scent (ECSA is member in one of those). The MyGEOSS competition is another area of activity.

Panel discussions facilitated by: Jan-Martin Wiarda Germany who got interested in the area as a journalist. the different panel members explore Citizen Science – Demonstrating Success

Josep Perelló (OpenSystems, Spain): open systems propose opening up research, complex systems research that are about society, but do experiments in public space and in collaborations with people with different skills – ordinary citizens, artists, designers and scientists. They also have a citizen science office in Barcelona with 20 groups and support from the city council. There is a Flickr album of open systems, and they do experiments in the street – asking people to understand how we cooperate – we are opens to allow designers and artists to work together in a city square. They have done reforestation in addition to the experiment to have the social impact after the project to pay back in social and environmental aspects. This was successful – it need to have scientific impact, in high impact journal (including Nature communications), they want to see 3 actors – scientists, artists and public authorities for example, and also want to demonstrate positive social impact

Arnold van Vliet (Natuurkalender Netherlands) – the project on which Arnold involved in is about phenology network, and it involves thousands of volunteers, with a long term changes – they can show tick bites and the link to lime disease. They reach out through media and get to 250 million times, which is a lot in the Netherlands – being media academic help to increase public awareness.

Daniel Dörler (citizenscience.at, Austria). In 2012 Florian and Daniel started doing citizen science in Austria, like SciStarter. They found 30 different projects from all sort of institutions – some by citizens, some by NGOs, universities. The main goal is to connect citizen science actors in Austria to help them collaborate. The platform is independent , and the system is more than a hobby, and along side a PhD work but support to the project can be an issue. What is making citizen science successful – the quality fo a project need to be high – scientific results, data but also how they give back to citizens. Citizens contribute for fun, but it need to give back more than just fun

Doreen Walther (Mosquito Atlas, Germany). The Mückenatlas project – the project focus on human health and it point to Mosquito borne diseases across Europe. Germany was assumed that no malaria will happen after WW II. there was no attention for a long time, but with invasive species, there was a need to notice them and endemic species. They realised that people want to learn more about mosquito biology and life. Doreen is interested in the life of mosquito and their development. They are doing molecular analysis. Ask people to collect mosquitos, kill them and share them with the scientists. Over 30,000 samples arriving in a year

Louise Francis (Mapping for change, UK). Started with projects about noise issues, but then turned into air quality issues with response from local authority to monitor locally. Worked with over 30 communities, using simple methods that can be used even by children in schools, working together with local authorities, there are cases of changes in buses from transport providers. Success is when there is an active change in the area. Engaging people is challenging to scale up – by making the data opened and shared, we are providing the tools to let communities to the work by themselves. Can be overwhelming demands when communities want to join. There are different approaches – when people live in a certain area and concerned about development project. Purchasing diffusion tubes for community can be €8 for one diffusion tube, and then buy them themselves. The people decide by themselves where they want to work.

Discussion: Need to use different networks, and need to show that the content is valuable, information need to be relevant to people – to get ideas of mosquitoes and collecting information from licence plates was possible in the Netherlands with 600 people but not huge scale. Josep pointed that you need to adapt to the specific situation and it’s not only about autonomy – it’s more like guerilla than an army with regular structure. Martin – there are tensions between top-down and bottom-up. Louise – we set up a separate social enterprise for flexibility and responsiveness, but the issue is autonomous from what – there is sometime lack of trust by the local government, so sometime the link to university is useful to increase trust. There is value in a third-party between local government and communities. Doreen – they deal with insect of medical importance, and media is getting involved, and creating panic is actually useful, but people have question marks in their heads and contact experts, which they offer and give an answer. This also encourage people to participate. Martin – relevance is coming again many time. Scientists don’t decide what is relevant. Arnold – scientists can have an important question to ask people to help, the other way around is also useful – both directions are useful and can work. If the scientist can’t communicate with the public than it won’t work. Josep – working with local authorities does require asking them what is relevant to them to address as that helps in participation.

Regarding open data policies – Daniel: encouraging projects to move towards this to encourage partner projects. The platform is trying to facilitate engagement but not to force policies. in terms of relevance, it is hard to judge what are the success factors – for example a project about wild life in the city. Louise – in terms of mobile app, our conclusion was to keep very simple approach of using diffusion tubes, so it’s very simple way to record data collection process, and then record the results from the lab – so facilitating simple sensing. Doreen – regarding how many people engage: the use of media TV, radio and newspaper help people to engage, but also internet platform and word of mouth. People have events – BBQ to attract and collect mosquito.

Are there examples of people that turned into professionals scientists but we did work with people that we seen change to move to further education – participants can be empower people in what they want to do. Josep – with the impact in school. Arnold – The population of participation – up to 60% of participants have higher education and therefore are scientists. Most people are already educated.

Audience poll – about 15% work on citizen science full time, 60% part time, and 15% as a hobby – but with overlaps .

Unsuccessful project can be things like for Josep, when urban bee hive remain illegal. For Doreen, the costs and complexity and loss of time can lead to failed projects. Louise  – questions of data and data validity – volunteer work hard to collect data and then ist is questioned and requestioned, and sometime that the research team ask us to collect a lot of data collection, and there are issues of thinking about the motivations of participation.

The lunch break provided time for experimentation

The afternoon session started with The diversity of citizen-science technologies: traditional and new opportunities for interactive participation in scientific research. We are covering the areas of the impacts of technologies, and this session explore how they influence participation, with a distinctive marine flavour

Jaume Piera (Institut de Ciències del Mar, Spain) – see the need to change and obtain observations, and changing the paradigm of information flow – from linear to complex. We need to think of acquisition, validation, data sharing, data tracking, engagement, data exploration and more. They work with makers and DIYrs to create cheap and easy to use instruments that produce high quality data – linking apps to DIY buoy .

Robert Arlinghaus (Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Germany). The only professor for angling in Germany. He started with all fashion way – diaries. Wanted to empower anglers to do experiments about stocks in their lakes. They’ve done experiments with anglers in their clubs, with participation in the design and the experiment itself. The anglers had high engagement, and low engagement – with a control groups. They engaged anglers even involved in the assessment of the results, and they showed that the engagement is empowering people – there is knowledge gain from seminar who lead to low level of retained knowledge, compared to those who were involved, and clear change in cognition – beliefs and personal norms. Limited use of technology, but now developing apps to catch assessment – need to consider who are the anglers, who are not used to advanced technology. Risk of exclusion through technology. They had 30% response rate on the paper diaries.

Neil Bailey Earthwatch, UK. In Earthwatch, working with fresh water watch involving many volunteers across the world, with an importance of having a global programme with local touch – in each of the 30 locations the local scientists managed their own variables and focus . Important to put flexibility to allow local variation. This need to express itself in apps. The website of the HSBC project include 1 day training and then on going engagement through the site. FreshWaterWatch is working with many partners: shell, HSBC, PwC, Heathrow, Riverfly partnership, Water Aid.

Discussion: Robert – there are exciting innovation in technology, that can show invasion and provide early warning. There are challenges of participation and bias, and privacy is a big issue in terms of privacy about the catch. Jaume – creating technical tools allow scaling and there is need to develop apps that are inclusive and don’t rely on the latest technology. Neil – there are questions about the exclusion potential, but there are already very cheap devices across the world. Having the smartphone doesn’t mean that you can use it well. Robert – we need to think who participate and who benefit in the results – you can have many people who benefit from the results that go to scientists who analysed it. However, the maps are becoming global and then there are many people receiving and using the information. Jaume – there are people who are enjoy makers, other observes, and other analysers. Different people have different skills and wish to participate. It allow different modes of participation. Martin – technology allow more people who use the results. Is the main thing collection of data or use, and will technology increase use of data? Do we get better data in terms of quality? Robert – in fresh water there is plenty of useful examples – information about the location from the GPS – trust technology on that. Neil – there are load of potential for technology and can be mine by different ways. Sensing is also useful, as well as allowing more data to understand the situation. Jaume – technology can help in collective intelligence, and people can identify species and so on. Audience question: how to merge data from different projects be shared? Neil – need to move data outside silos and need to figure out how to share it and use shared platforms. User interfaces are critical – need to allow working with the data in a way that is useful and effective. Need more partnership. Jaume – there is an international working group on interoperability of citizen science data. Q: How to engage people with little technological knowledge? Why Africa not in FreshWaterWatch? Neil – providing people technology is an incentive and possible to share it with more people. Q – technology is fine, but become out of data – how do you keep it? Neil – need to work with different technologies, but indeed require updating. Jaume – people can also participate in updating systems through open source and wider participation. Q – is the project design consider reuse in other contexts? This is happening in different project and being considered by the people in the projects. Jaume highlight the open source ability to share the underlying code.

What is the innovation that you see most important? Jaume – open hardware. Robert – web application, diaries on the web. Neil – flexible platforms

Algorithmic Governance Workshop (NUI Galway)

Algorithmic Governance Workshop (source: Niall O Brolchain)

The workshop ‘Algorithmic Governance’ was organised as an intensive one day discussion and research needs development. As the organisers Dr John Danaher
and Dr Rónán Kennedy identified:

‘The past decade has seen an explosion in big data analytics and the use  of algorithm-based systems to assist, supplement, or replace human decision-making. This is true in private industry and in public governance. It includes, for example, the use of algorithms in healthcare policy and treatment, in identifying potential tax cheats, and in stopping terrorist plotters. Such systems are attractive in light of the increasing complexity and interconnectedness of society; the general ubiquity and efficiency of ‘smart’ technology, sometimes known as the ‘Internet of Things’; and the cutbacks to government services post-2008.
This trend towards algorithmic governance poses a number of unique challenges to effective and legitimate public-bureaucratic decision-making. Although many are already concerned about the threat to privacy, there is more at stake in the rise of algorithmic governance than this right alone. Algorithms are step-by-step computer coded instructions for taking some input (e.g. tax return/financial data), processing it, and converting it into an output (e.g. recommendation for audit). When algorithms are used to supplement or replace public decision-making, political values and policies have to be translated into computer code. The coders and designers are given a set of instructions (a project ‘spec’) to guide them in this process, but such project specs are often vague and underspecified. Programmers exercise considerable autonomy when translating these requirements into code. The difficulty is that most programmers are unaware of the values and biases that can feed into this process and fail to consider how those values and biases can manifest themselves in practice, invisibly undermining fundamental rights. This is compounded by the fact that ethics and law are not part of the training of most programmers. Indeed, many view the technology as a value-neutral tool. They consequently ignore the ethical ‘gap’ between policy and code. This workshop will bring together an interdisciplinary group of scholars and experts to address the ethical gap between policy and code.

The workshop was structured around 3 sessions of short presentations of about 12 minutes, with an immediate discussion, and then a workshop to develop research ideas emerging from the sessions. This very long post are my notes from the meeting. These are my takes, not necessarily those of the presenters. For another summery of the day, check John Danaher’s blog post.

Session 1: Perspective on Algorithmic Governance

Professor Willie Golden (NUI Galway)Algorithmic governance: Old or New Problem?’ focused on an information science perspective.  We need to consider the history – an RO Mason paper from 1971 already questioned the balance between the decision-making that should be done by humans, and that part that need to be done by the system. The issue is the level of assumptions that are being integrated into the information system. Today the amount of data that is being collected and the assumption on what it does in the world is a growing one, but we need to remain sceptical at the value of the actionable information. Algorithms needs managers too. Davenport in HBR 2013 pointed that the questions by decision makers before and after the processing are critical to effective use of data analysis systems. In addition, people are very concerned about data – we’re complicit in handing over a lot of data as consumers and the Internet of Things (IoT) will reveal much more. Debra Estrin 2014 at CACM provided a viewpoint – small data, where n = me where she highlighted the importance of health information that the monitoring of personal information can provide baseline on you. However, this information can be handed over to health insurance companies and the question is what control you have over it. Another aspect is Artificial Intelligence – Turing in 1950’s brought the famous ‘Turing test’ to test for AI. In the past 3-4 years, it became much more visible. The difference is that AI learn, which bring the question how you can monitor a thing that learn and change over time get better. AI doesn’t have self-awareness as Davenport 2015 noted in Just How Smart are Smart Machines and arguments that machine can be more accurate than humans in analysing images. We may need to be more proactive than we used to be.

Dr Kalpana Shankar (UCD), ‘Algorithmic Governance – and the
Death of Governance?’ focused on digital curation/data sustainability and implication for governance. We invest in data curation as a socio-technical practice, but need to explore what it does and how effective are current practices. What are the implications if we don’t do ‘data labour’ to maintain it, to avoid ‘data tumbleweed. We are selecting data sets and preserving them for the short and long term. There is an assumption that ‘data is there’ and that it doesn’t need special attention. Choices that people make to preserve data sets will influence the patterns of  what appear later and directions of research. Downstream, there are all sort of business arrangement to make data available and the preserving of data – the decisions shape disciplines and discourses around it – for example, preserving census data influenced many of the social sciences and direct them towards certain types of questions. Data archives influenced the social science disciplines – e.g. using large data set and dismissing ethnographic and quantitative data. The governance of data institutions need to get into and how that influence that information that is stored and share. What is the role of curating data when data become open is another question. Example for the complexity is provided in a study of a system for ‘match making’ of refugees to mentors which is used by an NGO, when the system is from 2006, and the update of job classification is from 2011, but the organisation that use the system cannot afford updating and there is impacts on those who are influenced by the system.

Professor John Morison (QUB), ‘Algorithmic Governmentality’. From law perspective, there is an issue of techno-optimism. He is interested in e-participation and participation in government. There are issue of open and big data, where we are given a vision of open and accountable government and growth in democratisation – e.g. social media revolution, or opening government through data. We see fantasy of abundance, and there are also new feedback loops – technological solutionism to problems in politics with technical fixes. Simplistic solutions to complex issues. For example, an expectation that in research into cybersecurity, there are expectations of creating code as a scholarly output. Big Data have different creators (from Google to national security bodies) and they don’t have the same goals. There is also issues of technological authoritarianism as a tool of control. Algorithmic governance require to engage in epistemology, ontology or governance. We need to consider the impact of democracy – the AI approach is arguing for the democratisation through N=all argument. Leaving aside the ability to ingest all the data, what is seemed to assume that subjects are not viewed any more as individuals but as aggregate that can be manipulated and act upon. Algorithmic governance, there is a false emancipation by promise of inclusiveness, but instead it is responding to predictions that are created from data analysis. The analysis is arguing to be scientific way to respond to social needs. Ideas of individual agency disappear. Here we can use Foucault analysis of power to understand agency.  Finally we also see government without politics – arguing that we make subjects and objects amenable to action. There is not selfness, but just a group prediction. This transcend and obviates many aspects of citizenship.

Niall O’Brolchain (Insight Centre), ‘The Open Government’. There is difference between government and governance. The eGov unit in Galway Insight Centre of Data Analytics act as an Open Data Institute node and part of the Open Government Partnership. OGP involve 66 countries, to promote transparency, empower citizens, fight corruption, harness new technologies to strengthen governance. Started in 2011 and involved now 1500 people, with ministerial level involvement. The OGP got set of principles, with eligibility criteria that involve civic society and government in equal terms – the aim is to provide information so it increase civic participation, requires the highest standards of professional integrity throughout administration, and there is a need to increase access to new technologies for openness and accountability. Generally consider that technology benefits outweigh the disadvantages for citizenship. Grand challenges – improving public services, increasing public integrity, public resources, safer communities, corporate accountability. Not surprisingly, corporate accountability is one of the weakest.

Discussion:

Using the Foucault framework, the question is about the potential for resistance that is created because of the power increase. There are cases to discuss about hacktivism and use of technologies. There is an issue of the ability of resisting power – e.g. passing details between companies based on prediction. The issue is not about who use the data and how they control it. Sometime need to use approaches that are being used by illegal actors to hide their tracks to resist it.
A challenge to the workshop is that the area is so wide, and we need to focus on specific aspects – e.g. use of systems in governments, and while technology is changing. Interoperability.  There are overlaps between environmental democracy and open data, with many similar actors – and with much more government buy-in from government and officials. There was also technological change that make it easier for government (e.g. Mexico releasing environmental data under OGP).
Sovereignty is also an issue – with loss of it to technology and corporations over the last years, and indeed the corporate accountability is noted in the OGP framework as one that need more attention.
There is also an issue about information that is not allowed to exists, absences and silences are important. There are issues of consent – the network effects prevent options of consent, and therefore society and academics can force businesses to behave socially in a specific way. Keeping of information and attributing it to individuals is the crux of the matter and where governance should come in. You have to communicate over the internet about who you are, but that doesn’t mean that we can’t dictate to corporations what they are allowed to do and how to use it. We can also consider of privacy by design.

Session 2: Algorithmic Governance and the State

Dr Brendan Flynn (NUI Galway), ‘When Big Data Meets Artificial Intelligence will Governance by Algorithm be More or Less Likely to Go to War?’. When looking at autonomous weapons we can learn about general algorithmic governance. Algorithmic decision support systems have a role to play in very narrow scope – to do what the stock market do – identifying very dangerous response quickly and stop them. In terms of politics – many things will continue. One thing that come from military systems is that there are always ‘human in the loop’ – that is sometime the problem. There will be HCI issues with making decisions quickly based on algorithms and things can go very wrong. There are false positive cases as the example of the USS Vincennes that uses DSS to make a decision on shooting down a passenger plane. The decision taking is limited by the decision shaping, which is handed more and more to algorithms. There are issues with the way military practices understand command responsibility in the Navy, which put very high standard from responsibility of failure. There is need to see how to interpret information from black boxes on false positives and false negatives. We can use this extreme example to learn about civic cases. Need to have high standards for officials. If we do visit some version of command responsibility to those who are using algorithms in governance, it is possible to put responsibility not on the user of the algorithm and not only on the creators of the code.

Dr Maria Murphy (Maynooth), ‘Algorithmic Surveillance: True
Negatives’. We all know that algorithmic interrogation of data for crime prevention is becoming commonplace and also in companies. We know that decisions can be about life and death. When considering surveillance, there are many issues. Consider the probability of assuming someone to be potential terrorist or extremist. In Human Rights we can use the concept of private life, and algorithmic processing can challenge that. Article 8 of the Human Right Convention is not absolute, and can be changed in specific cases – and the ECHR ask for justifications from governments, to show that they follow the guidelines. Surveillance regulations need to explicitly identify types of people and crimes that are open to observations. You can’t say that everyone is open to surveillance. When there are specific keywords that can be judged, but what about AI and machine learning, where the creator can’t know what will come out? There is also need to show proportionality to prevent social harm. False positives in algorithms – because terrorism are so rare, there is a lot of risk to have a bad impact on the prevention of terrorism or crime. The assumption of more data is better data, we left with a problem of generalised surveillance that is seen as highly problematic. Interestingly the ECHR do see a lot of potential in technologies and their potential use by technologies.

Professor Dag Weise Schartum (University of Oslo), ‘Transformation of Law into Algorithm’. His focus was on how algorithms are created, and thinking about this within government systems. They are the bedrock of our welfare systems – which is the way they appear in law. Algorithms are a form of decision-making: general decisions about what should be regarded, and then making decisions. The translation of decisions to computer code, but the raw material is legal decision-making process and transform them to algorithms. Programmers do have autonomy when translating requirements into code – the Norwegian experience show close work with experts to implement the code. You can think of an ideal transformation model of a system to algorithms, that exist within a domain – service or authority of a government, and done for the purpose of addressing decision-making. The process is qualification of legal sources, and interpretations that are done in natural language, which then turn into specification of rules, and then it turns into a formal language which are then used for programming and modelling it. There are iterations throughout the process, and the system is being tested, go through a process of confirming the specification and then it get into use. It’s too complex to test every aspect of it, but once the specifications are confirmed, it is used for decision-making.  In terms of research we need to understand the transformation process in different agency – overall organisation, model of system development, competences, and degree of law-making effects. The challenge is the need to reform of the system: adapting to changes in the political and social change over the time. Need to make the system flexible in the design to allow openness and not rigidness.

Heike Felzman (NUI Galway), ‘The Imputation of Mental Health
from Social Media Contributions’ philosophy and psychological background. Algorithms can access different sources – blogs, social media and this personal data are being used to analyse mood analysis, and that can lead to observations about mental health. In 2013, there are examples of identifying of affective disorders, and the research doesn’t consider the ethical implication. Data that is being used in content, individual metadata like time of online activities, length of contributions, typing speed. Also checking network characteristics and biosensing such as voice, facial expressions. Some ethical challenges include: contextual integrity (Nissenbaum 2004/2009) privacy expectations are context specific and not as constant rules. Secondly, lack of vulnerability protection – analysis of mental health breach the rights of people to protect their health. Third, potential negative consequences, with impacts on employment, insurance, etc. Finally, the irrelevance of consent – some studies included consent in the development, but what about applying it in the world. We see no informed consent, no opt-out, no content related vulnerability protections, no duty of care and risk mitigation, there is no feedback and the number of participants number is unlimited. All these are in contrast to practices in Human Subjects Research guidelines.

Discussion:

In terms of surveillance, we should think about self-surveillance in which the citizens are providing the details of surveillance yourself. Surveillance is not only negative – but modern approach are not only for negative reasons. There is hoarding mentality of the military-industrial complex.
The area of command responsibility received attention, with discussion of liability and different ways in which courts are treating military versus civilian responsibility.

Panel 3: Algorithmic Governance in Practice

Professor Burkhard Schafer (Edinburgh), ‘Exhibit A – Algorithms as
Evidence in Legal Fact Finding’. The discussion about legal aspects can easily go to 1066 – you can go through a whole history. There are many links to medieval law to today. As a regulatory tool, there is the issue with the rule of proof. Legal scholars don’t focus enough on the importance of evidence and how to understand it. Regulations of technology is not about the law but about the implementation on the ground, for example in the case of data protection legislations. In a recent NESTA meeting, there was a discussion about the implications of Big Data – using personal data is not the only issue. For example, citizen science project that show low exposure to emission, and therefore deciding that it’s relevant to use the location in which the citizens monitored their area as the perfect location for a polluting activity – so harming the person who collected data. This is not a case of data protection strictly. How can citizen can object to ‘computer say no’ syndrome? What are the minimum criteria to challenge such a decision? What are the procedural rules of fairness. Have a meaningful cross examination during such cases is difficult in such cases. Courts sometimes accept and happy to use computer models, and other times reluctant to take them. There are issues about the burden of proof from systems (e.g. to show that ATM was working correctly when a fraud was done). DNA tests are relying on computer modelling, but systems that are proprietary and closed. Many algorithms are hidden for business confidentiality and there are explorations of these issues. One approach is to rely on open source tools. Replication is another way of ensuring the results. Escrow ownership of model by third party is another option. Next, there is a possibility to questioning software, in natural language.

Dr Aisling de Paor (DCU), ‘Algorithmic Governance and Genetic Information’ – there is an issue in law, and massive applications in genetic information. There is rapid technological advancement in many settings, genetic testing, pharma and many other aspects – indications of behavioural traits, disability, and more. There are competing rights and interests. There are rapid advances in this area – use in health care, and the technology become cheaper (already below $1000). Genetic information. In commercial settings use in insurance, valuable for economic and efficiency in medical settings. There is also focus on personalised medicine. A lot of the concerns are about misuse of algorithms. For example, the predictive assumption about impact on behaviour and health. The current state of predictability is limited, especially the environmental impacts on expressions of genes. There is conflicting rights – efficiency and economic benefits but challenge against human rights – e.g. right to privacy . Also right for non-discrimination – making decisions on the basis of probability may be deemed as discriminatory. There are wider societal and public policy concerns – possible creation of genetic underclass and the potential of exacerbate societal stigma about disability, disease and difference. Need to identify gaps between low, policy and code, decide use, commercial interests and the potential abuses.

Anthony Behan (IBM but at a personal capacity), ‘Ad Tech, Big Data and Prediction Markets: The Value of Probability’. Thinking about advertising, it is very useful use case to consider what happen in such governance processes. What happen in 200 milliseconds for advertising, which is the standards on the internet. The process of real-time-bid is becoming standardised. Start from a click – the publisher invokes an API and give information about the interactions from the user based on their cookie and there are various IDs. Supply Side Platform open an auction. on the demand side, there are advertisers that want to push content to people – age group, demographic, day, time and objectives such as click through rates. The Demand Side platform looks at the SSPs. Each SSP is connected to hundreds of Demand Side Platforms (DSPs). Complex relationships exist between these systems. There are probability score or engage in a way that they want to engage, and they offer how much it is worth for them – all in micropayment. The data management platform (DMP) is important to improve the bidding. e.g., if they can get information about users/platform/context at specific times places etc is important to guess how people tend to behave. The economy of the internet on advert is based on this structure. We get abstractions of intent – the more privacy was invaded and understand personality and intent, the less they were interested in a specific person but more in the probability and the aggregate. Viewing people as current identity and current intent, and it’s all about mathematics – there are huge amount of transactions, and the inventory become more valuable. The interactions become more diverse with the Internet of Things. The Internet become a ‘data farm’ – we started with a concept that people are valuable, to view that data is valuable and how we can extract it from people. Advertising goes into the whole commerce element.

I’ll blog about my talk ‘Algorithmic Governance in Environmental Information (or How Technophilia Shapes Environmental Democracy) later.

 Discussion:

There are issues with genetics and eugenics. Eugenics fell out of favour because of science issues, and the new genetics is claiming much more predictive power. In neuroscience there are issues about brain scans, which are not handled which are based on insufficient scientific evidence. There is an issue with discrimination – shouldn’t assume that it’s only negative. Need to think about unjustified discrimination. There are different semantic to the word. There are issues with institutional information infrastructure.

Giving time – randomised experiments on volunteering and citizen social science

As the event blurb explained  “the Giving Time experiments were led by a team from four UK universities, who wanted to know whether sharing information about how others have volunteered could help to improve volunteering… this was about giving time – and whether volunteers can be nudged. The methodology was randomised control trial (RCTs) in real-life field settings involving university student volunteers, Parish Councils, National Trust volunteers, and housing association residents.  The research was funded by the Economic and Social Research Council (ESRC).” The discussion of RCTs and Citizen Science in the same event was bound to generate interesting points.

In the first session, Prof Peter John (UCL) discussed The research challenges of large scale RCTs with volunteers and volunteering organisations. Peter covered the principles for Randomised Control Trials  (RCTs) – using randomness in trying something: assuming that two random groups will behave the same if you leave them alone, so you do things only to one group and observe the results. Start with baseline, random allocation to programme and control group, and then compare the outcome. Tying the outcomes to random allocation and – they are unbiased estimates of the impact of outcomes. Key distinguishing features of RCTs: need to deliver an intervention and the research at the same time. He suggests a 10 steps process – assessment of fit for RCTs, recruitment of partner organisations in which the work will be carried out, select a site, decide treatment, specify control, calculation of sample size, develop the procedure for random allocation, collection of data on the subjects, preparation of research plans, and assessment of ethical principles. The things can go wrong include: loss of subjects – people drop out along the way; failed randomization – deciding on who will be included in the process; treatment not given or modified; interference between treatment and control – when the groups meet; unavoidable confounds – when something come along in policy or media and policy change; poor quality data – what the data mean and what is going on with it; loss of cooperation with partners; and unexpected logistical challenges.
The Giving Time was the first RCTs on volunteering experiments – volunteering is more complex than giving money. The question is if behavioural methods can impact on the changes in the process. Working with the volunteering sector was challenging as they don’t have detailed records of volunteers that can be used to develop RCTs. There was willingness to participate in experiments and it was quite interesting to work with such organisations. There was a high level of attrition for those who are staying in the study – just getting volunteers to volunteer – from getting people to be interested until they do something. Is it possible to make it easier, get better quality data? RCTs required changes in organisational practices – if they are information based they are not hugely costly. It is possible to design trials to be sensitive to organisational practice and can be used quickly in decision making. There are issues with data protection and have a clear data sharing agreement.

Against this background, the second session Towards ‘Extreme Citizen Social Science’ – or volunteering as a tool for both social action and enquiry explored a contrasting approach. The session description already explored challenge: “For many, the scale of engagement with volunteers undertaken through Giving Time brings to mind related questions about the role of citizens in formal research – and then of course Citizen Science – or perhaps ‘Citizen Social Science’? At the same time we see the emergence of “Extreme Citizen Science” aimed at stimulating debate and challenging power relationships through citizen involvement in large scale scientific investigations. Extreme citizen science often starts from natural and physical sciences and has citizen researchers working with formal researchers to define the central research questions, and methods of investigation. But what is the potential for Extreme Citizen Social Science – characterised by being large scale, focused on social science questions, exploiting digital technology, having a high degree of participant control, and orientated towards influencing policy?”

Liz Richardson (Manchester Uni) gave her view on citizen social science approach. She is doing a lot of participatory research, and you need to explore with participants what is accepted to do with them. We can solve problems in a better way, if we have conversations on wide knowledge base in science – e.g. – a rough guide to spotting bad science. Liz compared her experience to early memories of the RSPB Big Garden Bird Watch – the natural sciences version of citizen science, and part of it is access to back gardens and wide area research. She also reflected on her participation in Zooniverse and the confusion about what is the science there – e.g. why scientists ask which direction wildebeest look? There are different levels of engagement in citizen science classification, such as Haklay 2013 and a version in the book community research for participation – from low participation to high level. Citizen social science  – example for a basic one is the 2011 big class survey in the BBC – just giving and sharing information – more crowdsourcing. Another, more complex example is Christian Nold emotional maps when people responded to arousal measurement, part of evolution in visualising information and sharing mapping. The app MapLocal is used in local planning and sharing information by community members. Groups can also collect data and analyse it – they then work with social scientists how to make sense of data that they collected (work carried out with White Rock Trust in Hasting). It’s not research that done alone but integrated and leading to a change – it’s community consultation. An example is a game in Boston with Participatory Chinatown – and example for a community-led action research from the Morris Justice Project with support from academics.

I provided a presentation about extreme citizen science, positioning it within social science context (similar to my talk for the Institute for Global Prosperity) with some pointers to underlying social theory – especially that the approach that we take in contrast to some behaviour change approaches that take methodological individualism for granted.

Jemma Mouland (Family Mosaic) provided the provider point of view. Head of research at large social housing provider, with about 45,000 tenants. They have done project with Liz, and she explained it from provider point of view. Family Mosaic is looking at community involvement and decision making – what affect them in their daily life and where the housing provider come in? How to work more collaboratively with the residents. They run the a citizen science project around the meaning of community. They have done that through the Giving Time project – they sent email to recruit people to become citizen scientists – from 8000 people that received the message, 82 were interested, then 13 people were involved. They provided the material to carry out workshops, and didn’t instructed how to carry out the research – that led to 50 responses, although instructed to get at least 3, so some people moved beyond just 3. They also got the citizen scientists to analyse the data and the residents interpreted the data that they have gathered. The results from the survey – different definition of community, with active minority, and barriers include time and articulating the benefits (‘why should I do it?’). The residents felt that it was great, but they weren’t sure about doing it again – and also acting on behalf of the provider can be an issue, as well as feeling that all familiar contacts where used. The issue of skills is also interesting – gave very little information, and it can be effective to train people more. For Family Mosaic – the data was not ground breaking, but prove that collaboration can work and have a potential, it gave evident that it can work for the organisation.

So, *can* volunteers be nudged? Turning the spotlight on the future of Nudge techniques. Professor Gerry Stoker (Southampton Uni) The reasons for the lack of success of intervention was the use of the wrong tool and significant difference of money donation and time donation. Nudge come with a set of ideas – drawing on behavioural economics – we use short-cuts and tricks to make decision and we do what other do and then government followed it in a way to influence and work with people and change their behaviour. There are multiple doubts about nudge – nudge assumes fast thinking, but giving time is in slow thinking mode – donating money closer to type 1 (fast thinking) and volunteering closer to type 2 (slow thinking). Second, humans are not just cognitive misers – there are degrees of fast and slow thinking. Almost all nudging techniques are about compliance. Also it’s naive and overly promotional – and issues when the topic is controversial. The individual focus missed the social – changing people mind require persuasion. Complexity also make clear answers harder to find – internal and external validity, and there are very complex models of causality. There are ironic politics of nudge and experiments – allowed space only at the margins of policy making. Need to recognise that its a tool along other tools, and need to deal with groups side by side with other tools. Nudge is a combination with structural or institutional change, wider strategies of behaviour change, and not that other techniques are not without their own problems and issues

Discussion – need to have methodologies that are responsive to the local situation and context. A question is how do you nudge communities and not work at the individual level.

The final talk before the panel discussion was Volunteers will save us – volunteering as a panacea. Presenter: Dr Justin Davis-Smith (National Council for Voluntary Orgs) State of volunteering in 2015 – volunteering can lead to allow social transformations – e.g. ex-offenders being released to volunteering roles and that help avoiding offending. Another success is to involve people who are far from the job market to get employable skills through volunteering. Volunteering also shown that volunteers have better mental health and wellbeing. Not volunteering has a negative impact on your wellbeing. There are volunteering that can be based on prescription (e.g. Green Gyms). Volunteers are engaged in public services, such as special constables. Social capital is also improved through volunteering. Replacement value £40Bn, and the other impacts of volunteering are not being quantified so the full value is estimated at £200Bn. So volunteer will save us?
However, volunteering is cost effective but not without cost and require investment, which is difficult to make. The discussion about engagement of volunteers in public service put the volunteers against paid labour, instead of co-production. There are also unhealthy dynamic with paid staff if it only seen as cost-saving measure. We have a small core that provide their volunteering effort, and the vast majority of volunteering is made by a small group (work on civic core by the centre for third sector research was mentioned). The search for the panacea is therefore complex. Over effort of 15 years in different forms of volunteering, there is only 5% change in the amount people report about volunteering. Some of the nudge mechanisms didn’t work – there is a lot of evidence to show that campaign on volunteering don’t work well. People react negatively to campaigns. Barrier for volunteering is lack of time, and concerned that getting involved will demand more and more of their time. Reflecting on time constraints and micro-volunteering can work.

The final panel explored issues of co-production of research and the opportunities to work with volunteering organisations to start the process – many social services providers do want to have access to research but find it difficult to start the process.