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This chapter examines the scientific ambition to measure consciousness despite its fundamentally subjective nature, focusing on the tension between quantitative science and subjective experience. The chapter surveys behavioural, neural, and theoretical approaches to gauging consciousness, including brain mapping, neural correlates, artificial neural networks, and structured questionnaires such as the ASC Rating Scale, PCI, HRS, and MEQ30. Rickles highlights a central difficulty: even if two people report identical experiences, there is no guarantee their inner states are the same—an epistemic barrier that complicates any scientific method. Examples such as the viral “black-and-blue or white-and-gold dress” illustrate how perception diverges across individuals, raising questions about whether reality is partly constructed and observer-dependent. The chapter then turns to machine learning and artificial intelligence, noting that AI systems can mimic intelligent behaviour yet lack evidence of subjective experience. This raises the question of whether observable behaviour is sufficient to infer consciousness.