Even big data does not speak for itself

2026/07/27 by Jürgen Landes · 1 voice
Computer Science · #Bayesian Modeling and Causal Inference #Gaussian Processes and Bayesian Inference #Explainable Artificial Intelligence (XAI)

paper · pdf · doi:10.1007/s11229-026-05732-5

openalex publication_date 2026/07/27 · openalex created_date 2026/07/28 · openalex updated_date 2026/07/29

Abstract

Abstract This paper demonstrates that in an important class of data-integration problems even Big Data cannot speak for itself: marginal probabilities provided by large and unbiased datasets do not determine a unique joint probability distribution. Big Data must instead be accompanied by further reasoning methodologies for handling unavoidable uncertainties. I assess how Bayesian approaches handle this underdetermination and argue that they face practical challenges when dealing with Big Data that does not speak for itself.

Citations

• Hyper Markov Laws in the Statistical Analysis of Decomposable Graphical Models
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Discussions

• Newly published: "Even big data does not speak for itself", by Jürgen Landes, Synthese, 2026, doi.org/10.1007/s112... [bsky, 2 points, 0 comments]

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