Transparency of algorithms

In January 2018 we kicked off the VWData research programme, with Inald Lagendijk as coordinator: a research programma that brings together academia, government and industry, and that aims to develop technical and societal solutions for using big data and algorithms responsibly (VWData Flyer).

Transparency of algorithms in the context of justice and security

Ibo van de Poel and Paul Hayes of Delft University of Technology, Remco Boersma of the Dutch Ministry of Justice and Security, and me (Marc Steen of TNO), work in the project “Responsible Collection and Analysis of Personal Data for Justice and Security”. We focus on the usage of big data and algorithms in the context of justice and security, e.g., by judges and by police officers, which raihses a range of questions about ethics and justice, e.g., about discrimination against specific groups of people.

Our objective is to make the usage of algorithms in the context of justice and security more transparent, so that their fairness, accuracy and confidentiality can be evaluated.

Clearly, one cannot maximize transparency in justice and security. Rather, transparency will need to be optimized; transparency will need to be balanced with security. The Ministry needs to be open and transparent ‘where possible’ and to provide security and safety ‘where needed’ (Informatiestrategie 2017-2022, pp 17, 23-24; and Informatieplan 2017, pp 15-19).

transparency

We will combine conceptual and practical research:

  • Conceptual: We will clarify what we mean with transparency, vis-à-vis other values, most notably fairness, accuracy, confidentiality, security and safety, and in terms of accountability, i.e. the ability to provide satisfactory accounts to diverse stakeholders, e.g., courts of justice, police officers and their managers, journalists and citizens;
  • Practical: We will conduct one case study, in close collaboration with the Ministry of Justice and Security’s ‘Living Lab Big Data’, and deliver a set of scenarios for optimizing transparency (the topic will be defined by the Ministry). This case study will also take into account the current data handling processes policies of the Ministry.

Auditing algorithms for fairness, accuracy and confidentiality

In parallel, we will also be working on the development of a standard process for the auditing of algorithms (to ‘open the black box’); this process would help:  1) to decide which algorithms should be audited; and 2) to execute the assessment of the algorithm’s fairness, accuracy and confidentiality. Sander Klous and Remko Helms (and others) will also be involved in this work. auditing

Currently, many algorithms function like ‘black boxes’. The give answers but no explanations. This is bad news if you are refused a mortgage (‘algorithm says no’) or if the police arrests you (‘algorithm says yes’).

We foresee that it will be necessary, within the next two years, to audit algorithms, i.e. to assess the algorithm’s fairness, accuracy and confidentiality (maybe use other terms, e.g., reliability, explainability) against a well-defined standard. The results of such an audit can help in various ways: 1) consumers/citizens can assess the algorithm’s fairness, accuracy and confidentiality, similar to how they can assess organic meat or fair trade bananas; and 2) service providers, both public and private, can position their offer as ‘fair’ or ‘accurate’ or ‘confidential’.

We are aware of other initiatives, e.g., “This logo is like an “organic” sticker for algorithms

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