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Analysis on the Persisting Effects of Redlining on Green Infrastructure in Chicago Neighborhoods
No full textThis report looks at “redlining” maps produced by the Home Owners’ Loan Corporation (HOLC) to analyze the current green infrastructure levels in various neighborhoods of Chicago. Redlining maps, produced in the first half of the 20th century, essentially graded neighborhoods on their riskiness for mortgage lenders. These maps often followed strict racial lines marking neighborhoods with a majority of black and other minority occupants in red to indicate they were the riskiest, hence the term redlining.1 Gathering geospatial data from these HOLC maps and overlaying them with maps showcasing green infrastructure indicators provides a visual representation of the relationship between structural disinvestment in neighborhoods and their current green infrastructure levels. Additionally, some neighborhoods break the pattern, showcasing which areas have changed the most with investment, indicating changes that can be associated with things like gentrification. In the end, k-means clustering best showcases the patterns that have emerged when looking at two variables with such a large gap in time between when the data was collected: redlining information from the 1940’s, and green infrastructure indicators from to 2010’s.
This research was taken a step further to begin descriptive analytical assessments of the ways in which redlining information relates to a variety of other datasets on the built environment. In this way, trends were starting to emerge that could suggest redlining as a predictor for other variables, however, the neighborhood scale at which the data was categorized does not produce strong enough indications. Nonetheless, continuing this line of study at a smaller scale, perhaps at the census tract level, could lead to more conclusive findings with a stronger correlation between redlining information and other datasets on the built environment that highlight the need for, and lack thereof, green infrastructure in disenfranchised areas
The Forecasting and Case Study Modeling of COVID-19 in Chicago: A Data-driven Approach
No full textProbabilistic graphical models and machine learning are powerful data-driven tools for extracting useful knowledge from historical data; this knowledge can facilitate improved decision-making. With the prevailing efforts to combat the coronavirus disease 2019 (COVID-19) pandemic, there are still uncertainties that are yet to be discovered about its spread, future impact, and resurgence. In this paper, a data-driven approach has been adopted in distilling the hidden information about COVID-19 and its symptoms. This paper proposes: a Bayesian network which encodes the causal relationships among COVID-19 symptoms, an unsupervised machine learning algorithm that learns symptoms pattern in COVID-19 dataset, a deep neural network which predicts the symptoms class of patients based on clustering experience with a 99.47% testing accuracy, and a time-series forecasting model that predicts the trend of COVID-19. The results from the experiments show the capability of data-driven methods in addressing the concerns of the society and government in understanding the uncertainties about the virus, providing insights on developing policies, and reducing the spread of the virus
An Analysis of the Impact of Social Media and Search Engines on Decision-Making
No full textWith 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\u27 conflicts of interests in the matter will be discussed
Psychotherapist Bots: Transference and Countertransference Issues
Get PDFThere is a rapid advancement in the development of psychotherapist bots that are based on artificial intelligence. Chatbots and robots may facilitate treatment by reducing barriers and increasing accessibility. Researchers have shown that psychological bots play an effective role similar to traditional face-to-face psychotherapy in reducing depression and anxiety symptoms. Due to the rapid advancement of psychotherapy technology, therapeutic chatbots are likely to become widely used in the near future. In this context, it is essential to consider both the ethical and clinical aspects of bots and chatbots as mental healthcare improvement assistants. The first part of this abstract outlines the concept of transference and countertransference in human-psychotherapist bot interactions. In this novel form of therapy, topics like transference and countertransference need to be discussed, as well as concepts such as empathy, acceptance, judgment, and safety in therapeutic relationships. We attempt to draw attention to the need to revisit clinical and ethical issues related to the interactions between humans and psychotherapist bots
Surveillance Culture and Fundamental Rights: The Excluded and the Beneficiaries
Get PDFSurveillance has progressively grown in social life in the 20th and 21st centuries. It happened partly because of the adoption of multiple sensors that can extract, collect and analyze an enormous volume of data. This expressive data volume, variety, and processing velocity are known as big data. The increasing adoption of big data and models based on algorithmic intelligence has a massive impact on society because of its dissemination among social spheres through relations between the public and private sectors. This paper aims to discuss surveillance culture and its consequences on fundamental rights such as privacy and freedom of speech. In addition, it is intended to debate the excluded and the beneficiaries of a surveillance society. The methodological approach is the literature review. The conclusion relies on the need for intercultural ethics to strengthen the right to privacy to guarantee not only itself but multiple fundamental rights nowadays. 
When AI Moves Downstream
Get PDFAfter computing professionals design, develop, and deploy software, what is their responsibility for subsequent uses of that software “downstream” by others? Furthermore, does it matter ethically if the software in question is considered to be artificial intelligent (AI)? The authors have previously developed a model to explore downstream accountability, called the Software Responsibility Attribution System (SRAS). In this paper, we explore three recent publications relevant to downstream accountability, and focus particularly on examples of AI software. Based on our understanding of the three papers, we suggest refinements of SRAS
Trust Through Explanation? On the claim for explainable medical decision support systems
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Theoretical Underpinnings of Virtual Reality: From Second Life to Meta
Get PDFSince Facebook’s transition and rebranding to ‘Meta’ in October 2021, there is a renewed academic and societal interest in the notions of ‘metaverse,’ ‘virtual reality’ (VR), and ‘virtuality’ (see e.g., Novak, 2022; Gent, 2022). This renewed interest reminds of the debates around the three-dimensional social virtual worlds like Second Life in 2007.
This paper has a two-fold conceptual aim. First, it presents a critical synthesis of how late-twentieth and twenty-first-century philosophers and media theorists have conceptualised virtuality and its relation to reality, in the context of VR. The analysis carefully distinguishes seven theories.
The second part focuses on a comparison (similarities and dissimilarities) between Second Life and Meta. The starting points are four conceptualisations of virtuality: an ontological, a phenomenological (in terms of subjective embodied experience), a cultural, and a technological conceptualisation (e.g., VR; augmented reality).
Ultimately, both aims and parts seek to contribute to a better and more nuanced understanding of the theoretical underpinnings of the current academic and societal discussions about Meta