Envisioning the expertise of the future

Principle-based recommendations for big data and machine learning in food safety: the P-SAFETY model

Big data and Machine learning Techniques are reshaping the way in which food safety risk assessment is conducted. The ongoing ‘datafication’ of food safety risk assessment activities and the progressive deployment of probabilistic models in their practices requires a discussion on the advantages and disadvantages of these advances. In particular, the low level of trust in EU food safety risk assessment framework highlighted in 2019 by an EU-funded survey could be exacerbated by novel methods of analysis. The variety of processed data raises unique questions regarding the interplay of multiple regulatory systems alongside food safety legislation. Provisions aiming to preserve the confidentiality of data and protect personal information are juxtaposed to norms prescribing the public disclosure of scientific information. This research is intended to provide guidance for data governance and data ownership issues that unfold from the ongoing transformation of the technical and legal domains of food safety risk assessment. Following the reconstruction of technological advances in data collection and analysis and the description of recent amendments to food safety legislation, emerging concerns are discussed in light of the individual, collective and social implications of the deployment of cutting-edge Big Data collection and analysis techniques. Then, a set of principle-based recommendations is proposed by adapting high-level principles enshrined in institutional documents about Artificial Intelligence to the realm of food safety risk assessment. The proposed set of recommendations adopts Safety, Accountability, Fairness, Explainability, Transparency as core principles (SAFETY), whereas Privacy and data protection are used as a meta-principle.

EFSA's third Scientific Conference 'Science, Food, Society': concluding remarks

From 18-21 September 2018, EFSA hosted its third Scientific Conference on Science, Food and Society in Parma, Italy. This paper summarises the overall recommendations on future actions and research priorities of the conference and complements the earlier multi-authored papers in this issue. The conference started and closed with the plenary sessions 'where science meets society: putting risk assessment in context' and 'staying relevant in a changing world', respectively. In between, there were seven breakout sessions five of which aimed at advancing risk assessment science in the areas of human health, the environment, biological hazards, nutrition and managing evidence, and two of which were dedicated to the societal aspects of risk assessment: engaging with society and envisioning the expertise of the future. During the 4 days of the event, participants addressed the complex interplay between science, risk assessment, policy and society, and explored how to advance food safety risk assessment to address the challenges of a changing world and ensure preparedness. Acknowledging that good science alone is no longer sufficient to ensure fit-for-purpose food safety risk assessments, EFSA must further build on its current five Strategic Objectives. To ensure that its risk assessments remain scientifically robust and sound, EFSA should strive for robust and fit-for-purpose risk assessments; consider food in the context of safety, nutrition and sustainability; and explore further how EFSA can work with other organisations to achieve the One Health/One Environment goals. In addition, EFSA should base scientific risk assessments on reliable science while capitalising on scientific advances; address scientific uncertainties; and fully publish the evidence and data used. In line with societal expectations, EFSA, in coordination with risk managers, should frame risk assessments through clear policy goals and problem formulation; be explicit about value judgements; communicate clearly and consistently and in coordination with risk assessors and risk managers; involve society; avoid conflicts of interest; and follow trustworthy processes.