Ground Truth

In machine learning, the labels treated as authoritative when training or evaluating a model - typically produced by human annotators or expert consensus and assumed to represent the 'correct' answer. Critical AI scholarship has shown that ground truth is socially constructed: it reflects the positionality, training, organisational control, and cultural assumptions of whoever produced it. In accessibility research, 'ground truth' labels produced without input from disabled people can encode ableist assumptions and systematically penalise non-normative bodies, voices, and communication practices.