Knowra Dataism Dataism Dataism is a worldview that treats data and information processing as fundamental, often favoring unrestricted data flows and algorithmic decision-making over human judgment.
Yuval Noah Harari : An Israeli historian and author whose book Homo Deus popularized dataism as a worldview. Harari frames dataism as a successor to humanism that places data flows above individual experience.
Information : Meaningful or structured content that can be represented, transmitted, or interpreted. Dataism depends on treating information as a basic account of reality.
Algorithmic decision-making : The use of computational procedures to make or support decisions about people and institutions. It puts the claim that algorithms can outperform human judgment into practice.
Algorithmic bias : Systematic and unfair outcomes produced or amplified by algorithmic systems. Biased outputs undermine the assumption that algorithmic decisions are inherently superior to human ones.
Data quality : The degree to which data is accurate, complete, consistent, timely, and fit for use. Dataist conclusions depend on records whose limitations can be difficult to detect.
Humanism : A family of philosophies that centers human dignity, agency, and reason. Dataism challenges humanism by treating people as information-processing systems rather than ultimate sources of value.
Data : Recorded observations or values used to describe entities, events, or processes. The worldview elevates recorded data from evidence into a guiding principle.
Big data : Large, complex datasets analyzed computationally to identify patterns and support decisions. Big-data systems embody the belief that more information can yield better knowledge.
Tacit knowledge : Knowledge gained through experience that is difficult to express fully in words or formal rules. It marks forms of understanding that data systems may fail to capture.
Measurement problem : The challenge of deciding how an abstract property should be operationalized and measured. Choosing what to measure embeds judgments that dataist language can make seem neutral.
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