The Fallibility of Objective Metrics
Autor/ka: Mgr. Branislav Čáp
Department of Philosophy and Applied Philosophy, Faculty of Arts, University of Ss. Cyril and Methodius in Trnava
Abstrakt
Objective metrics are often upheld as tools of precision and neutrality, promising consistent evaluations across domains like law, psychology, and aesthetics. However, this paper interrogates the assumption that objectivity guarantees truth. Drawing from both fictional and real-world cases, it demonstrates how metrics—though outwardly scientific—can obscure nuance and perpetuate flawed reasoning. The Voight-Kampff Test in Blade Runner exemplifies how physiological data may misrepresent emotional authenticity (Dick, 1968). Real-life polygraphs, too, fail to distinguish between deception and anxiety, leading to unreliable conclusions (National Research Council, 2003). Body language analysis suffers similar issues, as nonverbal cues are often misinterpreted due to cultural and individual variability (DePaulo et al., 2003; Hartwig & Bond, 2011). Even in art, the Golden Ratio is misapplied as a universal aesthetic ideal, despite lacking historical and empirical support (Markowsky, 1992). These cases illustrate Goodhart’s Law: When a measure becomes a target, it ceases to be a good measure (Goodhart, 1984). Referencing Adorno’s critique of commodification, the paper explores how the quantification of aesthetic experience, particularly through market prices and engagement metrics, erodes art’s critical and experiential power (Adorno, 1970). Nonetheless, the paper acknowledges that metrics can play a constructive role when used diagnostically. For instance, museum analytics have improved visitor experience by identifying barriers to engagement (Yoshimura et al., 2014). Ultimately, the paper calls for reframing metrics—not as arbiters of value, but as provisional tools, useful only when contextualized and critically applied.
Klíčová slova: objectivity, metrics, art criticism, Goodhart’s Law, Adorno
Reference
- Adorno, T. (1970). Aesthetic Theory. Minneapolis: University of Minnesota Press.
- DePaulo, B. M., et al. (2003). The Detection of Deception in Forensic Contexts. Cambridge: Cambridge University Press.
- Dick, P. K. (1968). Do Androids Dream of Electric Sheep? New York: Doubleday.
- Goodhart, C. A. E. (1984). Problems of Monetary Management: The U.K. Experience. In Monetary Theory and Practice. London: Macmillan.
- Hartwig, M., & Bond, C. F. (2011). Why Do Lie-Catchers Fail? A Lens Model MetaAnalysis of Human Lie Judgments. Psychological Bulletin, 137(4).
- Markowsky, G. (1992). Misconceptions About the Golden Ratio. The College Mathematics Journal, 23(1).
- National Research Council. (2003). The Polygraph and Lie Detection. Washington, D.C.: National Academies Press.
- Yoshimura, Y., et al. (2014). An analysis of visitors’ behavior in The Louvre Museum: a study using Bluetooth data. Environment and Planning B: Planning and Design, 41.
