1. Combining the strengths of UMIST and The Victoria University of Manchester Participation and e-Participation: Involving Stakeholders in the Management of Food Chain Risks in the Rural Economy Simon French, Gary Barker, Clare Bayley, Emma Carter, Andy Hart, John Maule, Christoph Mohr, Richard Shepherd

2. Combining the strengths of UMIST and The Victoria University of Manchester 2 Plan Introduction and background Type of issue considered TED project –HCI issues ― taken very broadly RELU project Issues of selecting appropriate (e-participation) methods Conclusions and questions

3. Combining the strengths of UMIST and The Victoria University of Manchester 3 Background UK rural community –General social and economic change –Specific impacts BSE Salmonella Foot and Mouth Rural Economy and Land Use Programme (RELU) –Funded by UK research councils

4. Combining the strengths of UMIST and The Victoria University of Manchester 4 Cynefin model of decision contexts Knowable Cause and effect can be determined with sufficient data The realm of scientific inquiry Known Cause and effect understood and predictable The realm of scientific knowledge Complex Cause and effect may be explained after the event. Social systems Chaos Cause and effect not discernable

5. Combining the strengths of UMIST and The Victoria University of Manchester 5 Knowable Cause and effect can be determined with sufficient data Assess, learn and respond Known Cause and effect understood and predictable Categorise and respond Complex Cause and effect may be explained after the event. Sense, judge, act flexibly Chaos Cause and effect not discernable Act, reflect, act Cynefin model of decision contexts

6. Combining the strengths of UMIST and The Victoria University of Manchester 6 Context expected by Government in handling issues Knowable Cause and effect can be determined with sufficient data Assess, learn and respond Known Cause and effect understood and predictable Categorise and respond Complex Cause and effect may be explained after the event. Sense, judge, act flexibly Chaos Cause and effect not discernable Act, reflect, act

7. Combining the strengths of UMIST and The Victoria University of Manchester 7 and then as data accumulates … Knowable Cause and effect can be determined with sufficient data Assess, learn and respond Known Cause and effect understood and predictable Categorise and respond Complex Cause and effect may be explained after the event. Sense, judge, act flexibly Chaos Cause and effect not discernable Act, reflect, act

8. Combining the strengths of UMIST and The Victoria University of Manchester 8 What can we learn from the past?

9. Combining the strengths of UMIST and The Victoria University of Manchester 9 Knowable Cause and effect can be determined with sufficient data Assess, learn and respond Known Cause and effect understood and predictable Categorise and respond Complex Cause and effect may be explained after the event. Sense, judge, act flexibly Chaos Cause and effect not discernable Act, reflect, act BSE Government: “Don’t worry; trust the scientists”

10. Combining the strengths of UMIST and The Victoria University of Manchester 10 Knowable Cause and effect can be determined with sufficient data Assess, learn and respond Known Cause and effect understood and predictable Categorise and respond Complex Cause and effect may be explained after the event. Sense, judge, act flexibly Chaos Cause and effect not discernable Act, reflect, act F&M Government: “Don’t worry; trust the scientists”

11. Combining the strengths of UMIST and The Victoria University of Manchester 11 ESF TED Programme Towards Electronic Democracy Can we use web-enabled decision analytic tools to involve citizens in deliberative democracy? An electronic Athenian ideal

12. Combining the strengths of UMIST and The Victoria University of Manchester 12 The middle ground Representatives elected to take decisions (Parliamentary Democracy) Individuals participate and vote in all decisions (Athenian Ideal) Individuals interact and participate; but authorities or parliament decide. (e-participation) Where decision analysis can help bring deliberative e-democracy?

13. Combining the strengths of UMIST and The Victoria University of Manchester 13 First steps: e-participation in analysis Formulate issues and structure problem Analysis Decide and Implement discussion web-sites (straw) e-voting current vision deliberative e-participation

14. Combining the strengths of UMIST and The Victoria University of Manchester 14 Human Computer Interface (HCI) Multiple users –often untrained/unfacilitated So the HCI needs to recognise each user’s –culture –knowledge and skills base –behavioural biases –philosophy (e.g. Bayesian vs fuzzy vs AHP vs …) –… TED Workshop on HCI and e-democracy. Manchester Business School Nov 9 – 11, 2005

15. Combining the strengths of UMIST and The Victoria University of Manchester 15 RELU-RISK Project just beginning  Not sure what we are doing Possible scenarios ─Choice between strategies for improving hygiene in the food chain ─An increase in the occurrence of toxoplasmosis in pigs ─Relative risks from two pesticide regimes ─Withdrawal of exemption licence on existing pesticides

16. Combining the strengths of UMIST and The Victoria University of Manchester 16 Food chain 1 Food chain 2 Food chain 3 Modular food chain models Each chain is a combination of modules representing production, processing, storage, consumption, etc. Dietary risk modelling National diet survey data 2D Monte Carlo engine Post-processing & analysis Long-term extrapolation Participatory Processes ‘Live’ groups Stakeholder workshops citizen juries focus groups Web-enabled interactions Surveys All stages of process: from problem definition to interpretation, decision-making, communication Predicting changes in consumer behaviour Analyse effects of communication and management actions Predict dietary changes Case studies A chemical contaminant A microbial contamination A scenario with unanticipated risk Specialist user Decision- making forums Lay public and stakeholders Communication and decision support interfaces Results for technical reports Test alternate scenarios and management options Lay user: What if? Risk to me? Media direct via internet indirect Models, systems and processes designed and validated with respect to

17. Combining the strengths of UMIST and The Victoria University of Manchester 17 How do we select appropriate (e-)participation methods? Literature has –Lots of theory –Lots of big ideas –Lots of studies of particular participation instruments –A few comparative studies –Very little guidance on selection –… and no agreement on terminology

18. Combining the strengths of UMIST and The Victoria University of Manchester 18 Possible objectives in design of participatory process If we take a democratic ideal perspective, principles matter most. If we take the perspective of a regulator, the choice is based upon more pragmatic attributes

19. Combining the strengths of UMIST and The Victoria University of Manchester 19 Separation of ‘science’ and values Issues Uncertainty modelling Preference modelling Decision Analysis Science What might happen Values How much it matters if it does Democratic Principles Decision Quality multiple perspectives

20. Combining the strengths of UMIST and The Victoria University of Manchester 20 Have begun to build comparative matrices:

21. Combining the strengths of UMIST and The Victoria University of Manchester 21 Process of participation We are not going to select a best instrument We need to develop a process in which several instruments are blended into a hybrid process –E.g. a mix of web-sites with information and decision analyses, plus stakeholder workshops, plus postal consultation, plus … Will there be interaction effects?

22. Combining the strengths of UMIST and The Victoria University of Manchester 22 Questions Particularly, please answer ours!