Mission

My name is Connor Ben Vaughs, I am a graduate student at San Diego State University where I earned a BA in Economics with a GPA of 3.22 in my upper division coursework. I am currently enrolled at SDSU as a part of the inaugural cohort of their new Big Data Analytics MS program. I have been working full time while studying as a full-time student throughout my entire collegiate career. I have assumed challenging roles while working for local and multinational businesses while developing professional skills in and out the classroom.

As a 21-year-old student, I became the general manager of an extremely successful casual dining restaurant, where I was responsible for Hiring, Scheduling, Food Cost, Sales Tracking, HR, Accounting, and compliance. I was asked to assume the position of general manager after only being an entry level cashier for this establishment three months prior. This operation grossed roughly $150,000 monthly in revenue. While preforming this function, I managed to complete a bachelor’s program, and enter a master’s program. I chose to further my education in Data Science because in the business world today, many of the decisions we make daily are influence, tracked, and understood by data. I desired to use this education to start my own business in the future devoted to using data to find individuals and communities who are underserved and connecting them with resources and services to help them. I believe data can be a tool, when used ethically and properly, for the betterment of society and our communities.

My area of interest and the field which I plan on devoting my lives work to is civic engagement in our democratic process. What I intend to do is increase the number of registered voters and increase the turnout rate for local and statewide elections. Big data is going to allow me to do this in a way that has not been feasible to previous champions of our democracy. We live in an unprecedented era of data collection, and data science gives us a limited glimpse into a world of knowledge that is right at our fingertips. Data science is currently being used in this field in a way that is derogatory to the manner which I plan on using it. For-profit companies are finding many ways to make money by turning voters into products. In a similar fashion to the way that conglomerates like Amazon and Facebook trade and sell consumer/user information, it is a wild west in the world of politics when it comes to targeting likely voters. There are many negative issues which plague the democratic process due to lack of oversight and a dependency of capital in our political process. Therefore, I am motivated to find a way to counteract this influence using the same data these special interests are using but by applying this information to uncover undisclosed possibilities and untapped political resources.

The way that big data currently intersects our political process is extremely predatory. First, you start with the targets, the consumer. In this narrative they serve as both the targets and the products. There are very few limitations to the type of information companies are currently allowed to keep and sell from users of their services. With most consumers, be that traditional retail or internet, trafficking multiple transactional locations is a regular practice. In today's marketplace, any given transaction may require information not limited to contact information, affiliations, and preferences. Consumers are unwittingly and inescapably arming companies with the ammunition they need to create predictive modeling tools to anticipate future purchases. In addition to this, online interactions add a new layer of insight to these observations (consumers). Social networking and relationship tracking provide an intimate and personal catalog of a persons explicit and implicit community preferences which can and are currently being used to filter sponsored content their way. These interactions, when funneled into machine learning algorithms, begin to advance the capabilities of data scientists to match certain patterns and tendencies to a categorical sorting process which can identify and predict spending habits of consumers. Translating this process to civil politics the way it is currently being practiced is a grim example of the negative effect data is having on this institution. Instead of enticing consumers to buy a product, the desired outcome by companies like L2 and Cambridge Analytica is to provide data sets and voter files which special interests and campaigns use to swing elections with an onslaught of targeted advertising. When you combine this with the practice of negative advertising and social media giants like Facebook who refuse to fact check the advertisements they allow to run on their platform, capital is able to find the demographics of people who have the potential to decide elections and encourage them to often vote a certain way, or even not at all. Mapping services are now able to identify regions, states, counties, cities, neighborhoods, and even smaller target areas for sponsored content to only certain demographics.

It is not all gloom in the future with data in politics. I see a future in which data is being used to empower and uplift citizens to reclaim their voice. The political process is one which did not originally intend on having every America vote, however it provided a vehicle to allow as many people who want to participate to seek engagement. It is for this reason I believe with the innovation of social media and big data; citizen will no longer need to ‘seek’ engagement, we will be able to bring engagement to them. In San Diego County, only 74.76% of eligible voters are registered to vote and in the 2018 election of we saw a record of roughly 69% turnout of registered voters. What data will begin to do is first close the 25% gap of eligible but non-registered voters. Data will do this by using existing registered voter’s location information to locate what I call ‘voter deserts’ which are areas of high density non-registered populations which we already know are traditionally low income and minority populations. Data will also find the largest impediments to registered voters showing up to elections and provide potential solutions to counteract obstacles like ones we already know about like transportation, childcare, employment, and voter exhaustion. GIS and social networking are two of the greatest innovation to the political process regardless of the current state of politics. It is up to scientists to decide the most responsible way this technology is used.

Lets’ set up a hypothetical. Lets’ say there was an energy company which wanted to build a dam on a local river. When some residents found out, environmental activists stepped in to protest the plans because a damn would flood a wetland inhabited by an endangered bird species. The energy company proposes to discount their services to the local city counsel who find the offer tempting enough to put it to a ballot initiative. The activists begin to mobilize and hold informational town halls on why there is a need to protect the wetland, but the energy company has another plan. Backed by Citizen United (the federal court ruling that allows an unlimited and largely underreported amount of money to be funneled into super political action committees to be spent in whatever political way they want under the pretense of free speech) the energy company begins to funnel overwhelming amounts of money into targeted political advertisements on Facebook. They run ads which plainly lie and say that the only time the dam would flood the birds wetland area is during the rainy season when they do not reside in the town at all due to their migration patterns so they would not be effected by the dam. They then use the voter files to target demographics in the town of Facebook users who are climate change deniers, anti-government protesters, and people who believe they pay too much on their electric bills. With the location services and invasive voter profiles on the towns people, the energy company can convince enough people to vote to allow the construction of the dam, and the endangered bird species is never seen again in the area. This hypothetical may seem alarmist, it may sound theoretical, but it is the reality of the state of politics in this new era of data science. With all the power data gives research, when unregulated with no oversight, capitalists hold no concern over the adversely affected third parties which are often the people. In my example it was an endangered bird species, but next time, it will be your town, and considering Russia was able to influence the 2016 election, we might be wishing that all we had to lose was just a bird.