ELS Prevision

Ethical, legal and societal impact assessment in security research – the example of the PREVISION project 

As part of its work on the PREVISION project, Trilateral Research is carrying out an integrated ethical, legal and societal (ELS) impact assessment. PREVISION is a two-year project funded by the European Union under the Horizon 2020 framework programme for research and innovation. More specifically, PREVISION has been funded under the “Secure societies – protecting freedom and security of Europe and its citizens” work programme[1]. An ELS Impact Assessment is appropriate for a project such as PREVISION because of the numerous ethical, legal and societal issues raised by the deployment of big data analytics in policing.

The ethical, legal and societal (ELS) impact assessment in practice

The PREVISION ELS impact assessment spans the lifecycle of the project from the early design to the deployment of the products and services. It is an iterative process, which involves moving back and forth between the available information on the project’s technological design and other components, the available literature and stakeholders.

The aim of ELS impact assessment is to identify and assess issues raised by the PREVISION tools, for example:

  • online data crawling tool
  • community detection tool
  • jargon and key phrases detection tool

and to recommend solutions and remedial actions necessary in order to avoid or minimise the negative impacts of their use. in consultation with the project’s stakeholders.

As the first step, we sought to identify potential impacts at the different levels and aspects of the PREVISION concept and design process. We identified risks generated by the initial PREVISION concept related to the ideas and plans of bulk monitoring and processing of massive data streams, including amongst other topics:

  • open-source data
  • video surveillance and facial recognition
  • use of data for prediction
  • web crawling
  • linguistic analysis and behavioural analysis
  • machine learning and the use of AI

We then mapped the risks raised by the initial concept onto the specific tools developed in PREVISION.

Next, we made a preliminary assessment of the likelihood and severity of the risks and outlined potential solutions. We distinguished between:

  • high concept (policy) solutions
  • existing user requirements with an identified ethical, legal and societal dimension
  • new requirements
  • solutions outside the design process

We suggested more than 20 additional technical requirements that should be fulfilled in the design of the tools and the platform in order to minimise the ELS risks.

Future Steps

Technical solutions should be complemented by non-technical measures to address the risks that could arise from the deployment of PREVISION tools without proper safeguards.

The work carried out so far has become the basis for further steps of the impact assessment, in which we are discussing the interim results with internal and external stakeholders in order to get their views on the risks we have identified, how would they rate the likelihood and severity of the risks, and what mitigation measures might be appropriate.

For more information on this research area, contact our team:

Zuzanna Warso

Zuzanna Warso is Senior Research Analyst at Trilateral Research.

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