Envisioning the expertise of the future

EFSA J. 2019 Jul 8;17(Suppl 1):e170721. doi: 10.2903/j.efsa.2019.e170721. eCollection 2019 Jul.

Abstract

Envisioning the expertise of the future in the field of food safety is challenging, as society, science and the way we work and live are changing and advancing faster than ever before. Future challenges call for multiple and multidimensional responses, some of which were addressed at EFSA's Third Scientific Conference. The participants indicated that risk assessment bodies involved in food safety such as EFSA must recognise that data, methods and expertise (i.e. people) are the three basic elements underlying risk assessments. These elements need constant consideration and adaptation to ensure preparedness for the future. Moreover, it should be recognised that knowledge and expertise are distributed throughout society and are thus not limited to scientists. Aspects considered during the breakout session included: (1) increased complexity, (2) the crowd workforce, (3) citizen science, (4) stakeholder engagement, (5) talent pools and (7) entrepreneurship. To account for future challenges, behavioural, attitudinal and cultural changes must be implemented successfully. At a societal level, people are increasingly going hand in hand with robotics and artificial intelligence in sharing expertise and producing outcome. This needs consideration on ethics and values, both for organisations and individuals. At an organisational level, risk assessment bodies will have to tap into new talent pools and new solutions for a more fluid and ad hoc-based workforce. Future risk assessment bodies will have to actively engage with stakeholders when performing their assessments. It is expected that the impacts of citizen science and involvement of the crowd will become part of risk assessment practices. Consequently, EFSA will have to continue to invest in massive, ongoing skills development programmes. At an individual level, potential recruits will need to be assessed against a whole new set of competencies and capabilities: technical competencies in data science, computational science and artificial intelligence, alongside a large set of soft skills.

Keywords: citizen science; crowdsourcing; expertise; food safety; scientific advice; stakeholder engagement.