How we can use data science to make our nations better

Overview

As i am heading towards the end of my time in my computer science boot camp i have realized i needed to see some real life examples of things i could potentially do in the future. the easiest way to do that was look at real life examples of big projects that have been taken in the past.

i wanted to find a research paper withing the last few years as computer science is ever evolving so taking things from the recent past will hold more weight for me now. the paper i chose was from december 2nd 2021 so its been less than a year since this came out and it was called "How We Determined Crime Prediction Software Disproportionately Targeted Low-Income, Black, and Latino Neighborhoods". the title instantly hooked me because these are things i have always believed happened but would have trouble finding defined evidence to present other people.

Now as someone who has a decent amount of knowledge in this field i was able to fully understand all of the code and techniques but how would i be able to explain this to someone who is not as tech-savvy?

Summary

to begin what exactly are the writers of this paper looking at to make their claims? and how do we know its correct? well, according to the author they obtained PredPol crime prediction data that has never before been released by PredPol. One of their associates 'Gizmodo' found it exposed on the open web (the portal is now secured) and downloaded more than seven million PredPol crime predictions for between 2018 and 2021. After securing the data and categorizing it they were able to find a number of factors that happen during most police interactions, such as number of times arrested, how many uses of force, amount of patrols by police and many more, then compared those metrics between different ethnicities and income ranges.

this is one of their final models and clearly shows that the low end of the spectrum in terms of blocks targeted by PredPol was vast majority white people while blocks with the highest amount of targets from PredPol are considerably disproportionate towards black and latino groups. this clearly shows in real data what a lot of people in America have known for a long time. but their data not only showed statistics unfairly targeting those not of white ethnicity but also how income ranges come into affect.

Once again you can see the very drastic difference between the most targeted blocks and least target blocks of households. households that have high diversity of both ethnicity and wealth numbers often see similar amounts of patrols regarless of any circumstance but blocks with disproportionately large amount of poor residence see such a jump up in targeting from the PredPol.

Final thoughts

obviously a lot of the stuff talked about in this paper is seen as common sense to certain groups, but that only is because those groups might have had first hand experience with these troubles with police, being able to take data from PredPol which is a data collection agency themselves just shows how much data reveals truths, they tried to hide this data but it was eventually leaked and now we can point to real life companies that work with cops to try and target marginalized groups.

this paper was really informative to me because Ive always been interested in figuring out very broad problems in our country today and learning how to take data and present them plainly to others will be a huge boost in what i want to do in the future for government work.

if i were to try and better explain this paper in plain words to either a business stakeholder who has interests in human resources or even a politician who wants to see change in our country like i do this paper would be extraordinary in pointing to facts when deciding policies to help others.
in conclusion i would recommend people read the whole paper as it is too much to explain in a short blog but i hope i was able to represent at least a little of their points well.

The paper i referenced: https://themarkup.org/show-your-work/2021/12/02/how-we-determined-crime-prediction-software-disproportionately-targeted-low-income-black-and-latino-neighborhoods#2021-predpol-methodology_race-percentile