Big data faces three philosophical issues. The first is digital ontology, which changes from static to dynamic, breaking the dichotomy between subject and object. The second is data cognition, which changes from the clear cognitive style of formula to the fuzzy cognitive style of construction and then from the mechanical superposition to the dialectical unity. The third is data reasoning, which shifts from the traditional science's emphasis on deduction to the big data era's emphasis on induction, and its function has changed from the balance of traditional scientific interpretation and prediction to the emphasis on prediction. These three philosophical issues reflect the phenomenological scientific philosophy tendency of big data. The entire information consists of subject construction. Nonetheless, data plays a role in each reproduction round, leading to a gradual increase in the construction factor of the subject. The starting understanding gradually shifts from precise to general, and the rough understanding as a whole is depicted in the general knowledge, leading to a comprehension of the object. In the age of big data, data is sourced from search engines, and design decisions are made using algorithms. The search engine's limits are predetermined, and users predefined the kernel based on their preferences and requirements.

Haoran Meng, Fengya Gao. Three Philosophical Issues of Big Data. The Frontiers of Society, Science and Technology (2024), Vol. 6, Issue 6: 95-99. https://doi.org/10.25236/FSST.2024.060615.

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