Diskrimination

Diskrimination is a term that commonly appears as a misspelling of discrimination. In most contexts, the standard term is discrimination, defined as the act or practice of treating people differently based on group membership such as race, gender, age, or other characteristics. Some writers use Diskrimination intentionally as a coinage to emphasize issues in digital or data-driven environments, though this usage is not standardized.

In discussions that connect technology with social inequality, Diskrimination is sometimes used to describe bias that emerges in algorithms, datasets, or user interfaces. Proponents may point to biased training data, skewed feature selection, or feedback loops that yield unequal outcomes in areas like hiring, lending, health care, or online recommendations. The idea is to highlight that unfairness can be built into automated systems as well as into human practices.

Despite occasional usage in tech commentary, Diskrimination is not a widely recognized term in scholarly literature. When it appears, it is typically treated as a stylistic variant or a rhetorical device rather than as a distinct field of study. The established concept remains discrimination, while discussions about algorithmic bias, data bias, and fairness in AI provide the formal framework for analyzing unfair treatment in digital contexts.

Related topics include discrimination, algorithmic bias, data bias, the digital divide, and broader concerns about social inequality and fairness in technology-mediated decision making.