Correlational knowledge lacks the necessity that causal knowledge requires

Evidence

Hegel, the philosopher of Spirit, would deem the omniscience (All-Wissen) that Big Data promises to be absolute ignorance (Un-Wissen). Hegel’s Logic may also be read as the logic of knowledge. Here, correlation represents the most primitive level. A strong correlation between A and B means that if A changes, a change also occurs in B. But when a correlation holds – however strong it may be – one still does not know why this is the case. It just is that way. Correlation represents a relation of probability, not of necessity. It declares: A often occurs together with B. That is the difference between correlation and causation, which is distinguished by necessity: A causes B. — Byung-Chul Han, Psychopolitics, 159

Categorization

• QUESTION: Is Han’s claim that correlation cannot know why fair to Bayesian causal inference? Would be interesting to check against modern causality literature such as Pearl.
• DEEPTHINKING: The provocation that data-driven omniscience is actually absolute ignorance — correlation’s primitiveness in Hegel’s scheme — is dense and paradigm-shifting.
• XREF: connects to: Big Data’s correlational mode is displacing causal and spirit-driven knowledge — Byung-Chul Han, Psychopolitics: Neoliberalism and New…, 158; Correlation knowledge without causality is, for Hegel, primitive ignorance — Byung-Chul Han, Psychopolitics: Neoliberalism and New…, 159; Correlations without an encompassing concept yield no real knowledge — Byung-Chul Han, Psychopolitics: Neoliberalism and New…, 160 (+4 more)

Related

• Correlation knowledge without causality is, for Hegel, primitive ignorance (similarity 0.96)
• Correlations without an encompassing concept yield no real knowledge (similarity 0.93)
• Big Data’s correlational mode is displacing causal and spirit-driven knowledge (similarity 0.90)
• Big data correlations alone cannot deliver causal knowledge to prediction systems (similarity 0.80)
• Large samples produce significant correlations that explain little variance (similarity 0.78)

Broader Connections

• Correlation knowledge without causality is, for Hegel, primitive ignorance #expands (0.85) — Byung-Chul Han, Psychopolitics, 159
• Understanding arises only from perceiving causal links among facts, not from the facts themselves #corroborates (0.82) — Janet Burroway; Elizabeth Stuckey-French; Ned Stuckey-French, Writing Fiction, Tenth Edition, 471
• Correlations without an encompassing concept yield no real knowledge #corroborates (0.80) — Byung-Chul Han, Psychopolitics, 160
• Big data correlations alone cannot deliver causal knowledge to prediction systems #corroborates (0.80) — Shoshana Zuboff, The Age of Surveillance Capitalism, 930
• Guaranteed prediction products require causal knowledge gained through experiments #corroborates (0.80) — Shoshana Zuboff, The Age of Surveillance Capitalism, 931
• Unidimensionality enables causal explanation rather than mere correlation #expands (0.75) — Bob Altemeyer, The Authoritarian Specter, 671