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Managing food chain risks: the role of uncertainty Richard Shepherd University of Surrey Project partners Person responsible Organisation Richard Shepherd University of Surrey Andy Hart Central Science Laboratory Gary Barker Institute of Food Research Simon French Manchester Business School John Maule Leeds University Business School Uncertainty • There are known knowns – there are things that we know that we know • There are known unknowns – that is to say, there are things that we now know we don't know • But there are also unknown unknowns – there are things we do not know we don't know • And each year we discover a few more of those unknown unknowns Donald Rumsfeld, US Secretary of Defense Winner of Plain English Campaign ‘Foot in Mouth Award’ 2003 Cynefin model of decision contexts Complex Cause and effect may be explained after the event. Social systems Chaotic Cause and effect not discernable 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 Snowden (2002) Need to communicate uncertainty • Need for: – Transparency – Openness • If uncertainty subsequently found it will lead to problems of credibility • ‘… the need to be open about uncertainty and to make the level of uncertainty clear when communicating with the public’ HM Government Response to the BSE Inquiry (2001) Presenting uncertainty to the public • Admission of uncertainty (Johnson and Slovic, 1995) – More honest – Less competent • Public preferences (Frewer et al. 2002) – Public want information on uncertainty – More accepting of uncertainty when due to scientific process than lack of interest or action by government Project objectives • Develop interactive web-enabled tools for quantitative assessment of risks and uncertainty • Use participatory methods to ensure webenabled tools, etc. appropriate for stakeholders • Develop methods to predict consumer behaviour driven by perceptions of risk and uncertainty • Develop improved methods for communicating with stakeholders • Test, evaluate and demonstrate improved approaches in case studies of food contamination and microbiological hazards Modules within the project Participatory Processes Modular food chain models Dietary risk modelling Food chain 1 National diet survey data Food chain 2 2D Monte Carlo engine Predicting changes in consumer behaviour Surveys Long-term extrapolation Food chain 3 Web enabled interactions Predict dietary changes Post-processing & analysis Each module includes production, processing, storage, retail, cooking etc. ‘Live’ groups • Stakeholder workshops • citizen juries • focus groups Analyse effects of communication and management actions Communication and decision support interfaces Specialist user Decision-making forums Lay public and stakeholders direct via internet All stages of process: from problem definition to interpretation, decision-making, communication Results for technical reports Test alternate scenarios and management options Lay user: What if? Risk to me? Media indirect Models, systems and processes designed and validated with respect to Case studies A chemical contaminant A microbial contamination A crisis scenario Participatory processes • Participatory methods – – – – Stakeholder workshops Citizens’ juries Focus groups Scenarios to stimulate discussion • Runs throughout project to: – Inform initial developments and ensure processes and web-enabled tools appropriate for stakeholders – Test in case studies Dietary risk modelling • Develop web-based tools based on CSL probabilistic tool • Probabilistic methods of risk assessment: – Take account of variability and uncertainty – Usually aimed at specialists • Hierarchical 2D Monte Carlo to quantify uncertainties • Expand to include: – – – – Other contaminants and pathogens Long term exposures Suitable for non-technical users ‘What if’ tools Modular food chain models • Managing risk across the food chain • Modularisation of food chain – Production, processing, storage, consumption • Dependencies across the chain concentrations of agent a function of: – Control measures – Performance criteria • Build set of uncertainty distributions Predicting changes in consumer behaviour • Impact on consumer behaviour of communication and management actions • Issues addressed: – Risk information v direct recommendation – Personal relevance of information – Presentation of uncertainty – Numerical/verbal presentation of uncertainty • Predict consumer behaviour changes Communication and decision support interfaces • Communication dependent on how different actors understand and think about risk • Mental models • Social representations • Test using scenarios Case studies • Chemical - pesticide – Data available – Amenable to probabilistic modelling • Microbiological - cross contamination with campylobacter – Undercooked chicken – Mainly caused by cross contamination • Scenario with unanticipated risk – Hypothetical scenarios – Rapid response Key audiences • Natural and social scientists • Stakeholders throughout the food chain – Producers – Manufacturers – Risk managers and regulators • General public(s) • Communication through: – Dissemination activities – Stakeholder workshops Concluding comments • Interdisciplinary research – Natural sciences – Social sciences • Quantitative assessment and modelling of risks and uncertainty across the food chain • Stakeholder involvement and participatory processes • Effective communication with the public and stakeholders