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/

Zendy Plus

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

Zendy Tools

Zendy Open

How can society understand and hold accountable complex human and algorithmicdecision-making systems whose systematic errors are opaque to the public? Thesesystems routinely make decisions on individual rights and well-being, and onprotecting society and the democratic process. Practical and statisticalconstraints on external audits--such as dimensional complexity--can leadresearchers and regulators to miss important sources of error in these complexdecision-making systems. In this paper, we design and implement asoftware-supported approach to audit studies that auto-generates auditmaterials and coordinates volunteer activity. We implemented this software inthe case of political advertising policies enacted by Facebook and Googleduring the 2018 U.S. election. Guided by this software, a team of volunteersposted 477 auto-generated ads and analyzed the companies' actions, findingsystematic errors in how companies enforced policies. We find that software canovercome some common constraints of audit studies, within limitations relatedto sample size and volunteer capacity.

Software-Supported Audits of Decision-Making Systems: Testing Google and Facebook's Political Advertising Policies