English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Central to a number of scholarly, regulatory, and public conversations aboutalgorithmic accountability is the question of who should have access todocumentation that reveals the inner workings, intended function, andanticipated consequences of algorithmic systems, potentially establishing newroutes for impacted publics to contest the operations of these systems.Currently, developers largely have a monopoly on information about how theirsystems actually work and are incentivized to maintain their own ignoranceabout aspects of how their systems affect the world. Increasingly, legislators,regulators and advocates have turned to assessment documentation in order toaddress the gap between the public's experience of algorithmic harms and theobligations of developers to document and justify their design decisions.However, issues of standing and expertise currently prevent publics fromcohering around shared interests in preventing and redressing algorithmicharms; as we demonstrate with multiple cases, courts often find computationalharms non-cognizable and rarely require developers to address material claimsof harm. Constructed with a triadic accountability relationship, algorithmicimpact assessment regimes could alter this situation by establishing proceduralrights around public access to reporting and documentation. Developing arelational approach to accountability, we argue that robust accountabilityregimes must establish opportunities for publics to cohere around sharedexperiences and interests, and to contest the outcomes of algorithmic systemsthat affect their lives. Furthermore, algorithmic accountability policiescurrently under consideration in many jurisdictions must provide the publicwith adequate standing and opportunities to access and contest thedocumentation provided by the actors and the judgments passed by the forum.

A relationship and not a thing: A relational approach to algorithmic accountability and assessment documentation