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The aim of this paper is to contribute to knowledge about the diversity of credibility arrangements in new audit spaces “in the margins” of auditing and the implications of such arrangements.

The paper is based on an in-depth qualitative study of the lesbian, gay, bisexual, transgender, queer and intersex (LGBTQI) rights certification run by the Swedish Federation for Lesbian, Gay, Bisexual, Transgender, Queer and Intersex Rights (RFSL) during its first decade of operation. We have interviewed employees and studied documents at the certification units within the RFSL. We have also interviewed certified organizations.

We highlight two features that explain the unusual credibility arrangements in this audit practice: the role of beneficiaries in the organizational arrangements chosen and the role of responsibility as an organizing value with consequences for responsibility allocation in this certification. These features make it possible for the RFSL to act as a credible auditor even though it deviates from common arrangements for credible audits.

The RFSL certification is different in several ways. First, the RFSL acts as both a trainer and an auditor. Second, the trainers/auditors at the RFSL have no accreditation to guarantee their credibility. Third, the RFSL decides for itself what standards should apply for the certification and adapts these standards to the operation being audited. Therefore, this case provides a good opportunity to study alternative credibility arrangements in the margins of auditing as well as their justifications.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.