User:Ethan Toomey/Choose an Article

California's Proposition 65 Bill

 * Article title
 * 1986 California Proposition 65


 * Article Evaluation
 * This article uses a neutral tone to discuss the reasons the California Proposition 65 or more commonly, "Prop 65" Bill was written, how it impacts businesses small and large and how its ultimate goal is to keep people informed about possible cancer and reproductive harm causing chemicals they may be exposed to. Each claim is cited throughout the article, most of the citations come from government websites, referencing parts of the bill or otherwise. I wouldn't say that it tackles the Wikipedia equity gap, nothing discussed here spotlights normally underrepresented or misrepresented populations or subjects.


 * Sources
 * https://oehha.ca.gov/proposition-65
 * https://arstechnica.com/science/2019/06/the-secretive-nonprofit-that-made-millions-suing-companies-over-cancer-warnings/
 * https://www.forbes.com/forbes/2001/1015/080.html#3bfaa0ac60aa

Technocracy

 * Article title
 * Technocracy


 * Article Evaluation
 * The article states the intention of Technocracy with no particular lean for or against it, simply just stating the facts about it as an ideological system of government. The article also talks about governments where it is loosely based around a technocracy with "technocrats". The article cites each claim, and most of the citations come from more respectable sources such as Reuters or MIT, and quite a few published books on the subject. This article doesn't really highlight an underrepresented subject or group of people.


 * Sources
 * https://www.bbc.co.uk/news/magazine-15720438
 * https://www.bbc.com/news/world-europe-15690289
 * https://www.economist.com/international/2011/11/19/minds-like-machines
 * https://www.washingtonpost.com/opinions/facebook-is-looking-a-lot-like-a-government/2020/02/23/2977a204-53f1-11ea-929a-64efa7482a77_story.html

Algorithmic Bias

 * Article title
 * Algorithmic bias


 * Article Evaluation
 * The article goes over the ethical questions raised by the algorithmically motivated biases AI may accidentally create towards a certain group of people. This Article highlights the obstacles this presents in research, it's impact on various protected groups, minorities, etc. It also offers the proposed solutions to this problem in a non-biased and informative matter. It's very well cited from sources such as Reuters to various academic studies and papers. It does meet the requirements of Wikipedias Equity Gap representation.


 * Sources

https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G


 * https://www.washingtonpost.com/health/2019/10/24/racial-bias-medical-algorithm-favors-white-patients-over-sicker-black-patients/
 * https://www.ibm.com/blogs/research/2018/02/mitigating-bias-ai-models/
 * https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6404626
 * http://dl.acm.org/citation.cfm?doid=3287560.3287594