# Applications and Broader Impact: Optimization

:::{admonition} Draft chapter
:class: warning
This chapter collects the broader-impact discussion and readings that accompanied Part IV in AM207 (Harvard, Fall 2021). It will be expanded into a full chapter.
:::

## Readings

**Applications and Broader Impact**

- [FTC Declares Racially Biased Algorithms in Artificial Intelligence Unfair and Deceptive, Prohibited by Law](https://www.lawyerscommittee.org/ftc-declares-racially-biased-algorithms-in-artificial-intelligence-unfair-and-deceptive-prohibited-by-law/)
- [Legal requirements on explainability in machine learning](https://link.springer.com/article/10.1007/s10506-020-09270-4)
- [Blind Justice: Fairness with Encrypted Sensitive Attributes](https://arxiv.org/pdf/1806.03281.pdf)
- [Awareness in Practice: Tensions in Access to Sensitive Attribute Data for Antidiscrimination](https://arxiv.org/pdf/1912.06171.pdf)
- [Equal Protection Under the Algorithm: A Legal-Inspired Framework for Identifying Discrimination in Machine Learning](http://Equal%20Protection%20Under%20the%20Algorithm:%20A%20Legal-Inspired%20Framework%20for%20Identifying%20Discrimination%20in%20Machine%20Learning)
- [The Problematic Nature of Racial and Ethnic Categories in Higher Education](https://www.equityinhighered.org/resources/ideas-and-insights/the-problematic-nature-of-racial-and-ethnic-categories-in-higher-education/)
- [Gender (mis)measurement: Guidelines for respecting gender diversity in psychological research](https://onlinelibrary.wiley.com/doi/full/10.1111/spc3.12506)