Misinformation in the Digital Era
For the final paper for this course, please submit an essay on the topic of your choosing. The only constraints on content for this assignment are as follows:
• The topic must be relevant to the issues addressed in modules 5 and/or 6.
• Your essay must substantively engage with at least three (3) of the required readings from modules 5 and/or 6.
• You may include outside sources, if appropriate, and you may refer to readings outside modules 5/6, as long as you have satisfied the above criterion. As before, keep in mind that you should not lean too heavily on external sources, insofar as this is a short essay and we are interested in your views on the subject.
• Since there is no specific prompt for this assignment, your thesis statement should be clearly stated near to the start of the paper. It should be obvious to your reader what the topic of your paper is, and what you are arguing.
As with essays 1 and 2, your final submission should be around 1250 words in total (±10%), excluding references.
Your essay submission is subject to the following restrictions:
• Do not include any identifying information in your submission. The essays will be graded anonymously.
o Note : Including identifying information (name, banner number, etc.) anywhere on your essay or the file name will be sufficient for a penalty of 1 mark on your final grade for essay 3.
• As per the syllabus, you must have completed and obtained 100% on the plagiarism quiz prior to submitting your assignment. If the plagiarism quiz is not submitted, or a score of 100% is not obtained, then your essay submission will not be graded. In this case, the 'submission date' of your essay will be counted as the submission date of your plagiarism quiz, and the essay will then be subject to the late penalty policy outlined in the syllabus.
o Note : You only have to complete the plagiarism quiz once. If you have already completed the quiz and obtained a score of 100%, you do not need to re-take the quiz.
• Your essay should be around 1125-1375 words in length.
• Your essay should be submitted in .pdf or .docx format.
• Your essay should be double-spaced with standard formatting (12 point, times new roman or similar font, 1 inch Margins, etc.)
• Any quotations or paraphrases of other people's ideas must be properly cited.
• A complete and properly-formatted list of 'works cited' should be included at the end of the document.
o Note 1 : the 'works cited' does not count toward the word limit.
o Note 2 : a properly-formatted citation for each of the articles in Modules 5 and 6 are given in the complete reading list on the course web page.
• Your submission should be generally free of grammatical and typographical errors—i.e., you should spend some time editing before you submit. A few minor mistakes will not warrant a deduction in points; however, significant typographical and grammatical errors, which lead to unclarity in exposition, will be penalised according to the rubric (below).
• A rubric for how this essay will be graded has been posted on the Additional Resources section of the course webpage. You should look at it before you begin writing so that you understand how your work is being graded.
• You should take account of the feedback given to you by the TAs from your first and second essays.
A summary of the breakdown of points is given in the table below, but more details are provided in the rubric.
Thesis Statement 5 Points
Arguments: Inferential Structure and Consistency 15 Points
Arguments: Strength 15 Points
Consideration of Alternatives / Counterarguments 10 Points
Insightfulness, Creativity, Novelty 5 Points
Explanation and Analysis of Topic/Question/Problem 15 Points
Exposition, Analysis, and Evaluation of Others' Arguments & Position 15 Points
Integration of Background Explanation and One's Own Position 5 Points
Roadmapping 2.5 Points
Guide-Posting 2.5 Points
Structure 5 Points
Readability 5 Points
OVERALL 100 Points
Misinformation in the Digital Era
Student’s Name
Department, University
Course Number: Course Name
Professor
Due Date
Misinformation in the Digital Era
Introduction
In the contemporary world, misinformation is not a new phenomenon, and a debate has ensued within the technology world about whether the trend is likely to decline or not. Presently, the state is such that the level of misleading and false narratives online is on the rise and, with the current pace, is more likely to increase into the future. Optimists believe that the condition will improve with technological fixes and be a long-term solution for society. On the other end, pessimists believe that the advancements in technology will only work to escalate the dark side of human beings; hence the level of misinformation is more likely to increase. O’Connor and Weatherall (2020) note that technology has created a platform through which information is shared and, as a result, has led to a division in opinion among citizens. The division in opinion has contributed a lot to disagreements on matters pertaining to daily lives. They posit that such disputes emerge due to different people trusting different sources of information. In most cases, when people disagree with our views, the assumption is that they are ignorant of the facts. However, the reasoning behind such disagreements is the technology that has introduced a high level of bias regarding the information people receive.
Discussion
The argument presented in this paper is that technology is entirely to blame for misinformation in the modern world. In this sense, the claim is that our cognition plays a less significant role in determining what we process as facts and non-facts. Facts or non-facts are determined by the kind of sources that people prefer for information. For this reason, O’Connor and Weatherall (2020) argue that peoples’ emotions and ideologies play a limited role in the process. The underlying reasoning is that human beings are mere agents who receive information that has already been manipulated through technology to portray their liking. In the past, people relied on mainstream news outlets such as The Washington Post, Fox News, Herald Tribune, and New York Times, among others, which followed a systematic approach of ascertaining facts from non-facts before reporting to the people.
However, with the emergence of social media, there has been a mass shift from reliance on mainstream media to social media platforms for information. Social media has become a powerful tool through which misinformation is spread in the present information age due to a lack of regulation and examination of information posted. Unfortunately, the traditional media has been pulled into social media, which has worsened the state of misinformation. Although the flow of misinformation is primarily a function of human factors, especially biases, it is also a function of technical aspects. The technicality element is based on algorithms where newsfeeds posted and reposted widely by the first viewers tend to be shown to other users. At this point, the widespread newsfeeds tend to tap into peoples’ biases.
While the element of bias cannot be disputed in data-driven systems, there is a contention that the focus on bias is unwarranted. Miceli et al. (2022) argue that bias can penetrate such systems at all levels; design, data, model, and application, potentially producing exclusionary outcomes. In the context of misinformation, they claim that biases locate problems within the technical systems (algorithms and data) and, as a result, fail to determine its root causes. Considering that bias is dependent on values, what counts most is the power relations that inform what should be regarded as a bias or not. Conversely, a power-oriented perspective should be adopted in determining facts from non-facts. The underlying notion, in this case, is that although this perspective looks into the technical bit of the information production system, it focuses more on the social contexts that inscribe values to information. Thus, the most critical aspect to consider when addressing the issue of misinformation is not merely the underlying biases in the data processing and information production systems but, more importantly, the sociotechnical systems that impact information development and deployment more.
When addressing the issue of misinformation in the current technological age, it is vital to acknowledge the role that machine learning plays. In this context, Johnson (2021) argues that machine learning programs reason or draw conclusions subject to underdetermination by proof. This aspect poses an inductive risk considering that such programs follow an inductive decision-making process when processing data. This means that the algorithms applied in such systems have consequences for information correctness...