Critical discourse analysis uncovers how balanced AI compromises justify surveillance data extraction in parliamentary debates, highlighting the moral costs of automated policing.
Key Points
To examine how political discourse uses 'third way' compromises to legitimize the extraction of public surveillance data for training police artificial intelligence systems.
Conducted a Critical Discourse Analysis of parliamentary debates concerning an automated police CCTV project in Hamburg, Germany.
Applied the pragmatist 'economy of conventions' framework to assess five evaluative orders of worth (security, individual freedom, social justice, automation, and experimentalism) and operationalize the concept of 'data sacrifices.'
Demonstrated that the 'third way' framing internalizes civic values like equality and privacy to legitimize automated surveillance while systematically discrediting and excluding civic critics.
Identified that this political justification strategy realigned watchdogs and culminated in the first German legislation authorizing police to transfer both anonymized and non-anonymized public surveillance data to external machine learning developers.