Lecture

Introduction to Human Rights

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In course

HUM-485: Data in context: Critical Data Studies I

Le cours "Critical Data Studies" s'inscrit dans la nouvelle offre d'enseignements TILT qui propose de croiser des savoirs provenant des SHS et des sciences de l'ingénieur afin d'aborder des thématiques complexes qui nécessitent une méthodologie interdiscip ...

Description

This lecture covers the fundamental concepts of human rights, including equality, non-discrimination, and a human rights-based approach. It explores the impact of social norms, stereotypes, and the digital age on human rights. The lecture delves into the principles of human rights, the prohibition of discrimination, and the importance of temporary special measures. It also discusses the relevance of a human rights-based approach in developing algorithms, using real-world examples like Tinder's algorithm patents. The lecture emphasizes the complexity of ensuring fairness in algorithms and the societal impact of biased data and models.

Official source

Related concepts (32)

Selection bias

Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. It is sometimes referred to as the selection effect. The phrase "selection bias" most often refers to the distortion of a statistical analysis, resulting from the method of collecting samples. If the selection bias is not taken into account, then some conclusions of the study may be false.

Sampling bias

In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in a biased sample of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected. If this is not accounted for, results can be erroneously attributed to the phenomenon under study rather than to the method of sampling.

Bias

Bias is a disproportionate weight in favor of or against an idea or thing, usually in a way that is closed-minded, prejudicial, or unfair. Biases can be innate or learned. People may develop biases for or against an individual, a group, or a belief. In science and engineering, a bias is a systematic error. Statistical bias results from an unfair sampling of a population, or from an estimation process that does not give accurate results on average. The word appears to derive from Old Provençal into Old French biais, "sideways, askance, against the grain".

Social norm

Social norms are shared standards of acceptable behavior by groups. Social norms can both be informal understandings that govern the behavior of members of a society, as well as be codified into rules and laws. Social normative influences or social norms, are deemed to be powerful drivers of human behavioural changes and well organized and incorporated by major theories which explain human behaviour. Institutions are composed of multiple norms.

Discrimination

Discrimination is the act of making unfair or prejudicial distinctions between people based on the groups, classes, or other categories to which they belong or are perceived to belong, such as race, gender, age, religion, or sexual orientation. Discrimination especially occurs when individuals or groups are unfairly treated in a way which is worse than other people are treated, on the basis of their actual or perceived membership in certain groups or social categories.

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