Socially Responsible Modeling, Computation, and Design

An Analysis of the Impact of Social Media and Search Engines on Decision-Making

Angela Petrone — 2023-11-01

With the constant advancement of technology and the advent of a global pandemic, as of 2023 it is safe to say our lives are as affected by our physical surroundings as they are by the virtual spaces we inhabit.

Social media and search engines constitute a big part of how people use technology to aid in their decision-making processes. The current state of social media and search engines regulation in the United States is one of stall: while public discourse continues and concerns among experts keep raising at each iteration of existing platforms or introduction of new tools, policymakers have not made as much progress in regulating the actions of the companies owning these platforms, in spite of their awareness of the impact these tools have on the public’s decision-making abilities. In this context, the spread of dis- and mis- information is a particularly dangerous phenomenon that can only be tackled with a radical change in the way platform owners are held accountable for the content they allow the circulation of.

This study aims to serve as a much needed reminder of the effects of social media and search engines usage on the public’s agency, decision-making processes, and ultimately the real-life consequences of the exposure to and interaction with online misinformation and disinformation.

A specific focus on how Covid-19 disinformation (false information which is deliberately intended to mislead) and misinformation (false or inaccurate information) spreading on two specific platforms (Reddit, and Google) was handled by said platforms will serve as a magnifying glass on the aforementioned issues. Analyzing the prominent design and ethics concerns in this landscape, I intend to propose heuristics to inform policy-oriented solutions to a set of issues that has been largely misunderstood and underestimated at the policy level in the United States. I argue that these concerns will only increase in complexity if left untackled, and the introduction of Artificial Intelligence (AI) tools to the public might have already exponentially complicated the position of the United States’ governmental entities; while explicitly clarifying their intention to insure people’s well-being, governmental bodies are struggling with either understanding the policy/regulatory options available to them or getting them passed. The influence of the lobbying power of tech companies and governments' conflicts of interests in the matter will be discussed.

Health Impacts of Environmental Inequalities in Redlined Areas

Sarah Exline — 2023-11-01

Chicago has a long history of redlining, a discriminatory housing process that has led to segregation in Chicago up to the modern day. This practice marginalized people of color and created a significant and still prevalent wealth gap between redlined and non-redlined communities. It is well known that poorer communities in Chicago are victims of negative environmental factors, such as industrial corridor proximity, and higher air pollution levels. There have been studies done on these things, but there are many overlapping factors that have led to Chicago’s prevalent inequality, creating a complex problem.

Our study aimed to tackle some of this complexity and to analyze how various environmental indicators impacted the health outcomes of people based on the HOLC (Home Owners’ Loan Corporation) grade they lived in. We conducted a literature review to see which health impacts were tied to which significant environmental indicators and designed our technical portion to account for the complexity and inter-relation of the data, but we wanted to do more with the communities as well, rather than just analyzing data. A major part of our project was inspired by the work of Phillip Boda of UIC in regards to designing research centered around communities rather than around data.

We came to the conclusion that the scope of our project was larger and more complex than any two people sufficiently cover and decided to design a coding tool alongside our analysis that will allow for communities to both interpret our findings and run their own analyses in the ways they deem most useful. We hope that this can both provide communities with a more thorough understanding of the complex relations between the environment and health. We also hope to provide a tool that can be more useful than existing resources we’ve used and found to have issues, such as the EPA’s Environmental Justice Screening tool (EJScreen).

We found that higher percentages of greenlined and bluelined areas had little significance to negative health outcomes, or lowered risk, while higher percentages of red and yellowlined areas had greater significance to the model, increasing risk of negative health outcomes with increasing area. The impact of environmental indicators on our model varied depending on the health impact being analyzed, but in the case of every health impact, there was a semi-linear positive trend when a model was created taking into account all of the independent variables and their coefficients.