# What does it mean for an algorithm to be fair?

DevFeed: [What does it mean for an algorithm to be fair?](<https://devfeed.tech/articles/what-does-it-mean-for-an-algorithm-to-be-fair-40385.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2015/07/13/what-does-it-mean-for-an-algorithm-to-be-fair/>)

Published: 2015-07-13T09:00:00Z

Content type: opinion

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Algorithms](<https://devfeed.tech/topics/algorithms.md>), [Algorithms, Complexity](<https://devfeed.tech/topics/algorithms-complexity.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [Programming](<https://devfeed.tech/topics/programming.md>)

Tags: [accountability](<https://devfeed.tech/tags/accountability.md>), [algorithm](<https://devfeed.tech/tags/algorithm.md>), [algorithms](<https://devfeed.tech/tags/algorithms.md>), [data-mining](<https://devfeed.tech/tags/data-mining.md>), [deep-learning](<https://devfeed.tech/tags/deep-learning.md>), [discrimination](<https://devfeed.tech/tags/discrimination.md>), [disparate-impact](<https://devfeed.tech/tags/disparate-impact.md>), [fairness](<https://devfeed.tech/tags/fairness.md>), [google](<https://devfeed.tech/tags/google.md>), [law](<https://devfeed.tech/tags/law.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [mathematics](<https://devfeed.tech/tags/mathematics.md>), [neural-networks](<https://devfeed.tech/tags/neural-networks.md>), [transparency](<https://devfeed.tech/tags/transparency.md>)

## AI overview

The article examines algorithmic fairness and argues that algorithms trained on historical human data can facilitate illegal discrimination and reinforce social prejudices. It uses targeted loan advertising, Google autocomplete, and predictive policing as examples, though the supplied text is incomplete.

## Source excerpt

In 2014 the White House commissioned a 90-day study that culminated in a report (pdf) on the state of "big data" and related technologies. The authors give many recommendations, including this central warning. Warning: algorithms can facilitate illegal discrimination! Here's a not-so-imaginary example of the problem. A bank wants people to take loans with high interest rates, and it also serves ads for these loans. A modern idea is to use an algorithm to decide, based on the sliver of known information about a user visiting a website, which advertisement to present that gives the largest chance of the user clicking on it.