Computer Science Homework Help

For the Algorithms Around Us assignment, each student will create their own reference guide to explain a particular use of algorithmic decision making in contemporary society by integrating student-written text and carefully chosen multimedia (images, articles, video, etc.) using Google Sites (Links to an external site.), to create a cohesive explanation of the positive and negative aspects of that use of algorithms using the description of algorithms provided by Cathy O’Neil in the book Weapons of Math Destruction.

Students’ reference guides will be graded based on the Algorithms Around Us Assignment Rubric. Please familiarize yourself with this rubric so you will understand the instructor’s expectations and how you will be graded. A sample of this kind of web page has been mocked up at https://sites.google.com/scarletmail.rutgers.edu/algorithms-around-us/home (Links to an external site.) – this is approximately the same length and contains the same headings and incorporates the same APA citation standards as the assignment.

NEWS ITEMS

Choose one of the news items listed below to work on.

• AI generated text: Hern, A. (February 14, 2019). New AI fake text generator may be too dangerous to release, say creators. The Guardian. Retrieved from: https://www.theguardian.com/technology/2019/feb/14/elon-musk-backed-ai-writes-convincing-news-fiction (Links to an external site.)
• Character and AI: Hardy, Q. (July 26, 2015). Using Algorithms to Determine Character. The New York Times. Retrieved from: https://bits.blogs.nytimes.com/2015/07/26/using-algorithms-to-determine-character/ (Links to an external site.)
• College Admissions and AI: Allen, B. (August 27, 2019). College Board Drops Its ‘Adversity Score’ For Each Student After Backlash. National Public Radio. Retrieved from: https://www.npr.org/2019/08/27/754799550/college-board-drops-its-adversity-score-for-each-student-after-backlash (Links to an external site.)
• Content Moderation: Fussel, S. (March 21, 2019). Why the New Zealand Shooting Video Keeps Circulating. The Atlantic. Retrieved from: https://www.theatlantic.com/technology/archive/2019/03/facebook-youtube-new-zealand-tragedy-video/585418/ (Links to an external site.)
• Dating and AI: Tiffany, K. (March 18, 2019). The Tinder algorithm, explained. Vox. Retrieved from: https://www.vox.com/2019/2/7/18210998/tinder-algorithm-swiping-tips-dating-app-science (Links to an external site.)
• Debate and AI: Samuel, S. (February 12, 2019). An AI system competed against a human debate champion. Here’s what happened. Vox. Retrieved from: https://www.vox.com/future-perfect/2019/2/12/18222392/artificial-intelligence-debate-ibm-san-francisco (Links to an external site.)
• Driverless cars: Samuel, S. (March 6, 2019). A new study finds a potential risk with self-driving cars: failure to detect dark-skinned pedestrians. Vox. Retrieved from: https://www.vox.com/future-perfect/2019/3/5/18251924/self-driving-car-racial-bias-study-autonomous-vehicle-dark-skin (Links to an external site.)
• Education and surveillance: Beckett, L. (October 22, 2019). Under digital surveillance: how American schools spy on millions of kids. The Guardian. Retrieved from: https://www.theguardian.com/world/2019/oct/22/school-student-surveillance-bark-gaggle (Links to an external site.)
• Facial recognition: Canon, G. (February 15, 2019). How Taylor Swift showed us the scary future of facial recognition. The Guardian. Retrieved from: https://www.theguardian.com/technology/2019/feb/15/how-taylor-swift-showed-us-the-scary-future-of-facial-recognition (Links to an external site.)
• Fast food and machine learning: Yaffe-Bellany, D. (October 22, 2019). Would You Like Fries With That? McDonald’s Already Knows the Answer. The New York Times. Retrieved from: https://nyti.ms/2We5OZH (Links to an external site.)
• Gig economy: Ghaffary, S. (February 6, 2019). Gig economy tech companies like Instacart have been accused of tip theft. But the problem is bigger than that. Recode. Retrieved from: https://www.recode.net/2019/2/6/18213872/gig-economy-instacart-tip-theft-contract-workers (Links to an external site.)
• Human resources and AI: Irwin, N. (June 15, 2019). The Mystery of the Miserable Employees: How to Win in the Winner-Take-All Economy. The New York Times. Retrieved from: https://www.nytimes.com/2019/06/15/upshot/how-to-win-neil-irwin.html (Links to an external site.)
• Human sexuality and AI: Levin, S. (September 8, 2017). New AI can guess whether you’re gay or straight from a photograph. The Guardian. Retrieved from: https://www.theguardian.com/technology/2017/sep/07/new-artificial-intelligence-can-tell-whether-youre-gay-or-straight-from-a-photograph (Links to an external site.)
• Journalism and AI: Levin, S. (August 8, 2019). Revealed: how Monsanto’s ‘intelligence center’ targeted journalists and activists. The Guardian. Retrieved from: https://www.theguardian.com/business/2019/aug/07/monsanto-fusion-center-journalists-roundup-neil-young (Links to an external site.)
• Machine learning and civic resources: Madrigal, A. (January 3, 2019). How a Feel-Good AI Story Went Wrong in Flint. The Atlantic. Retrieved from: https://www.theatlantic.com/technology/archive/2019/01/how-machine-learning-found-flints-lead-pipes/578692/ (Links to an external site.)
• Medecine and algorithms: Lecher C. (October 24, 2019). A health care algorithm affecting millions is biased against black patients. The Verge. Retrieved from: https://www.theverge.com/2019/10/24/20929337/care-algorithm-study-race-bias-health(Links to an external site.)
• Misinformation: Kelley, L. (September 23, 2019). The Google Feature Magnifying Disinformation. The Atlantic. Retrieved from: https://www.theatlantic.com/technology/archive/2019/09/googles-knowledge-panels-are-magnifying-disinformation/598474/ (Links to an external site.)
• Predictive policing: Doctorow, C. (February 13, 2019). Beyond GIGO: how “predictive policing” launders racism, corruption and bias to make them seem empirical. Retrieved from: https://boingboing.net/2019/02/13/algorithmo-cop.html (Links to an external site.)
• Reading and AI: Paul, K. (February 3, 2020). ‘They know us better than we know ourselves’: How Amazon tracked my last two years of reading. The Guardian. Retrieved from: https://www.theguardian.com/technology/2020/feb/03/amazon-kindle-data-reading-tracking-privacy (Links to an external site.)
• Real Estate: Dezember, R. (March 5, 2019). Buyer Beware: Hollywood Special Effects Now Permeate Property Listings. Wall Street Journal. Retrieved from: https://www.wsj.com/articles/home-sellers-doctored… (link to article .pdf)
• Recidivism: Israni, E. (October 26, 2017). When an Algorithm Helps Send You to Prison. The New York Times. Retrieved from: https://www.nytimes.com/2017/10/26/opinion/algorithm-compas-sentencing-bias.html(Links to an external site.)
• Religion and Machine Learning: Samuel, S. (September 9, 2019). Robot priests can bless you, advise you, and even perform your funeral. Vox. Retrieved from: https://www.vox.com/future-perfect/2019/9/9/20851753/ai-religion-robot-priest-mindar-buddhism-christianity (Links to an external site.)
• Shopping and AI: Kwet, M. (June 14, 2019). In Stores, Secret Surveillance Tracks Your Every Move. The New York Times. Retrieved from: https://nyti.ms/2WI8bCy (Links to an external site.)
• Social impact uses of algorithms: Rosenburg, T. (February 12, 2019). Making an App to Make a Difference. New York Times. Retrieved from: https://www.nytimes.com/2019/02/12/opinion/start-ups-apps-social-impact.html?action=click&module=Opinion&pgtype=Homepage (Links to an external site.)
• Wildlife and AI: Temple-Raston, D. (October 25, 2019). Elephants Under Attack Have An Unlikely Ally: Artificial Intelligence. National Public Radio. Retrieved from: https://www.npr.org/2019/10/25/760487476/elephants-under-attack-have-an-unlikely-ally-artificial-intelligence (Links to an external site.)
• Workplace surveillance: Doctorow, C. (March 6, 2019). From prisons to factories to offices: the spread of workplace surveillance and monitoring tech. Retrieved from: https://boingboing.net/2019/03/06/robo-taylorism.html (Links to an external site.)

Read through the news item carefully and thoroughly, keeping an eye out for evidence related to O’Neil’s three components of “Weapons of Math Destruction” as discussed in chapter one.

Research the specific use of algorithmic decision making discussed in the article you selected. Your goal in this research is to provide a full explanation of:

• What is algorithmic decision making and why is it important to understand its use?
• The use of this type of algorithmic decision making tool described and why it is significant.
• How this type of algorithmic decision making would line up with each of O’Neil’s three components (transparency, damage or potential for damage, and scale).

Your research used for your reference guide should include at least eight sources that you identified (not counting the original news item from the assignment’s list or Weapons of MathDestruction)of which at least two must be audio or video and at least two must be peer reviewed sources from scholarly journals. In your write-up you will also need to cite the news item and the Weapons of Math Destruction book, for a minimum of ten sources in total for the assignment.

All sources used should be credible as assessed by a test such as the CRAAP test and should be cited using APA citations. The original news item should also be listed among the sources for the assignment.

Synthesize your research to develop a one page reference guide for readers to have their questions related to the news item answered. Word count for this guide should be approximately 1200-1500 words excluding references.

Sources for information on the site must be listed in APA style using full citations for the sources at the bottom of the page in a separate section. See the OWL APA guide (Links to an external site.) for help if needed. When preparing the “Sources” section be sure to also cite the Weapons of Math Destruction book as well as the original news item that you’ve been researching for the assignment! In all, you should wind up with at least ten sources.

Build a one page site with this information using the free “Google Sites” web-based tool. Videos and images should be embedded to clarify or illustrate your points. Design choices for the web page should prioritize clarity of content, specifically ease of reading.

INSTRUCTIONS FOR BUILDING THE REFERENCE GUIDE WITH GOOGLE SITES

STEP 1: Follow the steps outlined on the “Get Started with Google Sites” page: https://gsuite.google.com/learning-center/products/sites/get-started/ (Links to an external site.)

STEP 2: Begin creating your reference guide by adding the following to your new site: Site document name Banner title/header: Short title of your reference guide. Description: Full title of your reference guide. Banner image DO NOT SELECT A TEMPLATE THAT USES MULTIPLE PAGES OR TABS OR COLLAPSING SECTIONS! Your work must be completely visible without clicking on any interface elements when the URL loads. If you’re uncertain if your selected template presents this kind of problem be sure to check with your IA at least 48 hours before submitting your work. Your reference guide will be made public and visible on the open web when you publish it. To maintain your privacy, it’s recommended that you do not use your full name for the “Username” – rather use a first initial and last name or first name and last initial (e.g., msmith; or marys) or some other generic identifier.

STEP 3: Add six subheadings titled “Overview of Algorithmic Decision Making”, “Transparency”, “Potential for Problems”, “Scale”, “Conclusions”, and “Sources” to your Google Sites page. Each of these subheadings should include a discussion supported by source(s) you have found to be helpful in understanding that aspect of the reference guide’s topic. Images and video are often helpful for explaining different aspects of the use of this technology and should be embedded appropriately. Captions explaining the image/video’s context and identifying its source are strongly encouraged where-ever possible. Important notes!: Provide substance in your analysis that demonstrates critical thinking! Engaging in lengthy summaries of your sources without discussing why this information is enlightening or useful in understanding the topic will not result in a good grade. DO NOT copy/paste content from the source word-for-word. This is plagiarism and will result in an automatic zero for this assignment and possible further consequences. Be sure to paraphrase others’ thoughts in your own words! Lengthy direct quotes from your sources will not be viewed as a strong indication of your own understanding of the material.

STEP 4: Preview your Google Sites digital story To see how it will look when published, click on the preview icon. Proofread and edit/revise, as needed, before publishing your Google Sites digital story.

Step 5: Publish Your Google Sites digital story.

STEP 6: Copy your Google Sites URL at the top of the page and then follow the Assignment Submission Instructions below to submit your work