In response to the emergence of COVID in England in 2020, the government declared a suspension of face-to-face education. To deal with the cancellation of exams, then minister of education Gavin Williamson assigned the Office of Qualifications (OfQual) with devising a method for awarding grades to students based on the standards they would have met had the examinations not been cancelled. As a response, OfQual implemented a prediction matrix based on the resources available to them: this system is wildly referred to as the OfQual algorithm. However, as the points were delivered on 13 August 2020, disputes arose leading to the cancellation of the algorithm. This paper will focus on the OfQual algorithm as a particularly relevant case to highlight the tensions around the notion of fairness in the implementation of such systems. Drawing on Science and Technology Studies, I will start by opening the black box of the OfQual algorithm. This will, in turn, allow me to identify the conflicting accounts of what is considered as fair in such system and how such accounts were inscribed within this algorithm, questioning what it means for such system to be fair in contexts marked by inequalities.

The principle of open justice is a constituent element of the rule of law: it demands publicity of legal proceedings, including the publication of judgments. Since 2017, the UK government has systematically published first instance Employment Tribunal decisions in an online repository. Whilst a veritable treasure trove for researchers and policy makers, the database also has darker potential – from automating blacklisting to creating new and systemic barriers to access to justice. Our scrutiny of existing legal safeguards, from anonymity orders to equality law and data protection, finds a number of gaps, which threaten to make the principle of open justice as embodied in the current publication regime inimical to equal access to justice.