Task 1:

AI Tool Analysis Declaration

The AI Tool Analysis Paper (1500 to 2500 words) is one of the course’s two major papers, due at the end of Week 6. It asks you to analyze one publicly available AI tool not as a user, but as a critic examining the design assumptions, data practices, stated and unstated values, likely users and affected communities, and accountability structures embedded in that tool as a sociotechnical system.

You are encountering this page in Week 3 because the analytical frameworks you will apply to your tool are still being built. Weeks 1 through 5 give you the vocabulary training data, discriminatory design, behavioral surplus, opacity, governance gaps. By the time the paper is due at the end of Week 6, you will have five weeks of frameworks to bring to bear. The tool you choose now may change as those frameworks sharpen your sense of what is worth analyzing.

What this page asks of you right now is modest: name a tool you are currently thinking about, justify why it is analytically interesting, and identify one question it raises for you. That declaration is due Sunday at midnight. It is not a contract it is a starting point.

What the Paper Will Ask You to Do

The paper analyzes your chosen tool across five analytical dimensions the same lenses the course applies to AI systems throughout the term:

Design assumptions what the tool assumes about its users, their needs, and the problem it is solving

Data practices what data the tool uses, how it was collected, and what communities or contexts it may underrepresent

Stated and unstated values what the tool claims to do versus what its design encodes

Likely users and affected communities who benefits and who bears costs, including communities not counted as users

Accountability structures what mechanisms exist for oversight, contestation, or redress and what is absent

What Counts as an Eligible Tool

Any publicly available AI tool is eligible there are no restrictions on medium, domain, or geography. The only requirement is that the tool be publicly accessible and that you can make a genuine analytical case for why it is worth studying. The constraint is in your justification, not the eligibility rules.

Tools that tend to generate strong papers are ones where the gap between stated values and actual design is visible, where the affected communities are broader than the intended user base, or where the accountability structures are notably absent or theatrical. Analytically thin choices tend to be tools where everything the company says about the tool is true and uncontested those leave little for the five dimensions to work on.

Domain	Example types (not an exhaustive list)
Hiring and employment	Resume screening tools, interview analysis platforms, workforce monitoring software
Healthcare and welfare	Clinical decision support tools, benefits eligibility systems, mental health chatbots
Content and recommendation	Social media feed algorithms, news recommendation engines, content moderation systems
Surveillance and policing	Facial recognition systems, predictive policing tools, border control AI
Education	Proctoring software, automated grading tools, adaptive learning platforms
Finance and credit	Credit scoring algorithms, fraud detection systems, automated loan decisioning

Your Declaration Three Parts

Submit your declaration as a text entry in the Canvas assignment below. Keep it brief 150 to 250 words total. Respond to all three parts. What matters is specificity and honest engagement, not polish.

1	Name your tool. Give the full name of the tool, who made it, what it does, and where it operates publicly, in what sector, for what stated purpose. If you are considering more than one tool, name both and say what is pulling you in each direction.
2	Justify your choice. In two to four sentences: what makes this tool analytically interesting? Where do you sense a gap between what the tool claims to do and what it actually does, or between who it is designed for and who it affects? You do not need to have done research yet you are naming an instinct or observation and explaining why it is worth pursuing.
3	Name one question. What is one question about this tool related to its design, its affected communities, its values, or its accountability that you want to be able to answer by the time you finish the paper? This does not need to be your thesis. It is the question that makes the tool worth analyzing for you right now.

Declaration Due Sunday of Week 3 Midnight

Submit your three-part declaration as a text entry in the Canvas assignment. 150250 words total. No special formatting required.

This is a graded completion check. What it is looking for is specificity and honest engagement not a finished argument. Your tool may change between now and the paper deadline. That is expected and fine.

Your Tool May Change That Is the Point

The frameworks you will use to analyze your tool discriminatory design, surveillance capitalism, technological due process, ethics-washing are introduced across Weeks 1 through 5. It is entirely possible that a framework you encounter in Week 4 or 5 will change which tool feels most worth analyzing, or will reveal something about your current tool you had not noticed. Declaring a tool now is not locking you in. It is giving you a concrete object to think with as those frameworks arrive.

What Comes Next

You will submit the paper in the Week 6 module. Bookmark it now and read through it before Week 4 begins knowing the five analytical dimensions early gives you something to look for as you encounter each week’s frameworks.

The paper is due at the end of Week 6. There is no formal approval process for tool selection unlike the Narrative Analysis, you do not need to wait for instructor sign-off before you begin. The declaration is for your benefit: naming a tool now makes the next five weeks of reading more purposeful.

Task 2:

Preliminary Narrative Analysis Declaration

The Narrative Analysis assignment is one of the course’s two major papers, due at the end of Week 7. You have been using the four-question framework since Week 1 this assignment asks you to take that method into a text you choose yourself and work through it in sustained, written form. You are encountering this page in Week 3 because the most important decision you will make about this assignment is which text to analyze. That decision shapes everything that follows. The earlier you make it, the better your paper will be.

Before you begin writing anything, you need to submit a brief text proposal and receive instructor approval. This is not a bureaucratic hurdle it is the same practice we used for the gallery case study: a moment of deliberate choice and public justification before the analytical work begins.

What the Assignment Asks

You will select one narrative text written or visual/media and analyze it as a form of anticipatory social analysis about AI, automation, or algorithmic systems. Using the four-question framework, you will make a sustained argument about what the text reveals that purely technical or policy analysis cannot see. You will connect your analysis to at least one real AI system or policy case discussed in the course.

Full assignment instructions including the four questions, format requirements, length, and submission details are on the in the Week 6 module. Read those instructions before submitting your proposal.

What Texts Are Eligible

Your text must engage directly or obliquely with AI, automation, algorithmic systems, or the idea of machine intelligence. It does not need to use those words. What matters is that it opens a question about intelligence, agency, prediction, labor, accountability, or what it means to be classified by a system.

WRITTEN / TEXTUAL TRACK	VISUAL / MEDIA TRACK
Short stories, novellas, novel excerpts, poetry sequences, graphic novels, comics	Films, television series (one season or a sustained arc), podcasts, video game narratives, documentary films
Note on scope: If you choose a novel, focus your analysis on a specific section or set of scenes rather than attempting to analyze the full text in 1,2002,000 words.	Note on scope: If you choose a TV series, focus your analysis on one season, one episode, or a specific narrative arc not the full series.

On Course Texts

Texts we analyzed together in class Yez Cosso’s “La IWM 1000,” Chiang’s “Exhalation,” and Borges’ “The Library of Babel” are not eligible. The assignment asks you to do original analytical work, not extend our class discussion.

Texts assigned to the course but not fully analyzed in class Dick’s “The Minority Report” and Le Guin’s “The Ones Who Walk Away from Omelas” are eligible, but only with a strong justification explaining what angle your analysis will take that goes beyond anything we touched on in class.

A Note for Visual and Media Track Students

The four-question framework was developed primarily for written fiction. Visual and media narratives carry meaning through additional channels cinematography, editing, sound design, mise-en-scne, music that the four questions do not explicitly address. If you choose a film, series, podcast, or other media text, you will use a supplemental set of visual analysis prompts alongside the four questions. Those prompts are included on the full assignment page in Week 6.

Choosing a visual text is not easier or harder than choosing a written one it is methodologically different. Make sure you are choosing a visual text because it is the right text for your question, not because you find it more accessible. In your proposal, explain specifically how the visual or sonic elements of your text are doing analytical work that a written text could not.

Your Proposal: Three Parts

Submit your proposal as a private text entry in the Canvas assignment below. Your proposal should be 150250 words total, organized around three questions. There are no right answers what the proposal is looking for is evidence that you have made a deliberate choice and that you can articulate why it matters.

1	Identify your text. Give the full title, author or creator, medium, and year. If it is a visual/media text, specify what you are focusing on (a single film, one season of a series, a podcast episode, etc.).
2	Justify your choice. In two to four sentences: what does this text engage however indirectly about AI, automation, algorithmic systems, or machine intelligence? Why is it the right text for this assignment and not just a text you happen to like?
3	Name your opening question. What is one question the text raises for you about intelligence, agency, accountability, labor, or what it means to be classified by a system that you want to pursue in your analysis? This does not need to be your final argument. It is the question you are starting with.

Proposal Deadline

Submit your text proposal with your Week 3 Stakeholder Map. Both are due before Week 4 Session A.

You will receive instructor feedback within 35 business days. Do not begin drafting your analysis until your text has been approved. If you are redirected to a different text, you will have enough time to adjust before the Week 6 workshop.

What Approval Looks Like

The instructor will respond to your proposal in one of three ways: approved (proceed with your text); approved with a refinement (your text works, but focus your question in a specific direction); or redirected (this text is not the right fit, with a specific suggestion for why and where to look instead). There is no penalty for being redirected it is part of the process of finding the right analytical entry point.

What Comes Next

Once your text is approved, you have Weeks 4 and 5 to read or view it carefully and begin making analytical notes. In Week 6 Session B, there is a dedicated workshop where you will work with a partner on your draft or outline using the four-question framework. The full assignment is due at the end of Week 7.

The full assignment instructions, the four-question framework, the visual track supplement, formatting requirements, and submission details are all on the . Bookmark it now.

Narrative and Cultural Analysis Assignment

1,2002,000 words Creative Commons licensed Individual assignment

This assignment asks you to do what we have been practicing since Week 1: read a narrative text as a form of anticipatory social analysis. Stories about intelligent machines, automated systems, and algorithmic futures are not predictions. They are cultural laboratories ways of thinking through questions that purely technical or policy analysis cannot reach. This assignment asks you to demonstrate that you can use narrative as a genuine analytical method, not as illustration or decoration.

You will apply the four-question framework introduced in Week 2 to the text you selected and had approved in Week 3. You will connect your analysis to at least one real AI system or policy case from the course. The result should be an argument a specific, evidence-based claim about what your text reveals that a policy document or technical report cannot.

The Assignment’s Central Question

What does this narrative make visible about AI, automation, or algorithmic systems that a technical or policy analysis cannot see and what real-world system or case does that insight illuminate?

The Four-Question Framework

Your analysis must engage all four questions. They do not need to appear as labeled sections in your paper strong papers weave them into a continuous argument. But every question must be addressed, and each should be grounded in specific moments from your text, not in general claims about what the text is “about.”

1	What kind of intelligence does the system in this story exercise and what kind does it lack? This question asks you to characterize the system’s cognitive capacities with precision. Avoid vague terms like “smart” or “limited.” What specifically can it do classify, predict, optimize, generate? And what specifically is absent judgment, context, accountability, the ability to be wrong in a human sense?
2	Who benefits from the system, and who bears its costs? Map the story’s distribution of power and harm. Who commissioned the system, who operates it, who is subject to it, and who is absent from the frame entirely? The most interesting answers often involve characters or groups the story does not name directly.
3	What human capacity does the system replace or displace? This question is not asking what the system automates in a technical sense. It is asking what form of human presence, judgment, or relationship is lost when the system takes over. Memory, care, discernment, witness, accountability these are the kinds of capacities worth examining. What does the story suggest cannot be recovered once they are gone?
4	What does the story’s resolution suggest about accountability and who is absent from it? How does the story end and what does that ending encode about responsibility, consequence, and repair? Does the story imagine accountability as possible? As institutional, individual, or structural? Pay attention to who is not in the room when accountability is or is not achieved.

Visual and Media Track Supplemental Prompts

If your approved text is a film, television series, podcast, graphic novel, video game, or other media narrative, you must engage all four questions above and address at least two of the following supplemental prompts. These are not separate sections they are additional analytical lenses to weave into your argument where they sharpen it.

Visual and sonic elements are not decoration. They are argumentative. A camera angle, a musical cue, a scene cut, a color palette these make claims about power, knowledge, and accountability just as a narrator’s voice does in written fiction. Your job is to show how.

Supplemental Prompt	What It’s Asking
How does the visual or sonic language construct the AI system’s point of view and whose perspective does it privilege or exclude?	Camera position, framing, and sound design encode epistemic authority. Who sees, and how?
What does the text’s visual or sonic grammar suggest about the relationship between speed and power? Between visibility and control?	Editing pace, surveillance aesthetics, and the look of data often encode assumptions about who controls whom.
Where does the text use visual or sonic ambiguity moments that resist clear interpretation and what does that ambiguity do analytically?	Ambiguity in visual texts is often where the most interesting analytical work lives. Don’t resolve it prematurely.
How does the text use the body human or machine to make an argument about what AI can and cannot know?	Embodiment, gesture, and physical presence often carry the argument that dialogue alone cannot.

Connecting to a Real-World Case

Your analysis must connect to at least one real AI system, policy case, or governance context discussed in the course. This connection is not a footnote it is a structural requirement of the argument. The narrative analysis is the lens; the real-world case is what the lens illuminates.

The connection should be argumentative, not decorative. You are not saying “this story reminds me of facial recognition.” You are saying something like: “this story’s account of delegated judgment without accountability maps precisely onto the opacity problem that Citron describes in automated benefits systems and the story reveals something about that problem that Citron’s legal argument cannot reach.” The narrative does analytical work the policy text cannot. Show that work.

What Strong Analysis Looks Like A Model

The paragraph below is a model of how one of the four questions might be addressed in a paper analyzing E.M. Forster’s 1909 story “The Machine Stops” a text not used in this course. Read it as an example of analytical depth and textual grounding, not as a template to imitate structurally.

Model paragraph Question 3: What human capacity does the system displace?

“What Forster’s Machine displaces is not labor but orientation the human capacity to locate oneself in physical space and to know the world through the body’s encounter with it. When Vashti refuses to look out the airship window, calling the earth ‘just dust and muck’ and retreating to the comfort of her hexagonal cell, the story is not staging a failure of curiosity. It is staging the systematic atrophy of a perceptual faculty that the Machine has made unnecessary. The Machine does not merely automate travel; it renders the experience of place irrelevant. This is precisely what contemporary location-inference systems accomplish at scale: not by physically confining users, but by making the data-processed abstraction of a place its review score, its foot-traffic index, its algorithmic rank more actionable than the place itself. Forster’s story makes visible what machine learning’s optimization logic cannot name: that what is lost when orientation is automated is not a convenience but a form of knowing.”

Note how the paragraph moves: specific moment in the text precise characterization of what is displaced connection to a real system claim about what the narrative reveals that the real-world system’s own logic cannot articulate. That movement text to system to insight is the argumentative spine of this assignment.

Format and Submission

Length	1,2002,000 words, excluding your AI Use Disclosure Statement and references. Papers significantly under or over this range will be asked to revise before grading.
Format	Double-spaced, 12pt font, 1-inch margins. MLA or APA citation format be consistent. Include full bibliographic information for your primary text and all course materials cited.
License	Submit under a Creative Commons Attribution 4.0 (CC BY 4.0) license. Include the license declaration on your cover page: “This work is licensed under CC BY 4.0. The author permits reuse, adaptation, and redistribution with attribution.”
AI Disclosure	Attach a brief AI Use Disclosure Statement at the end of your paper. Describe which tools you used, how, and how AI-generated outputs were revised or rejected. This is required regardless of whether you used AI tools if you did not, say so.
Submission	Upload to the Canvas assignment by end of Week 7. Submit as a .docx or .pdf file. Papers submitted for library deposit will be formatted by the instructor after grading.
Weight	15% of final course grade.

Due End of Week 7

Submit via Canvas by the end of Week 7. The Week 6 Session B workshop is your last structured opportunity for peer feedback before submission.

Your text must have been approved before you begin drafting. If you have not yet received approval, contact the instructor immediately.

What the Paper Is Evaluated On

Criterion	What It Means
Textual grounding	Claims are supported by specific moments, scenes, images, or passages from the text not by general assertions about what it is “about.”
Analytical depth	All four questions are meaningfully addressed. The analysis goes beyond plot summary or thematic description to make a claim about what the text reveals.
Real-world connection	The connection to a real AI system or policy case is argumentative it shows what the narrative reveals that the real-world system’s own documentation cannot.
Clarity of argument	The paper has a central claim a specific, defensible argument that a reader can identify and evaluate. It is written in clear, accessible language.
Responsible AI use	AI use is documented honestly and completely. The intellectual core of the argument the analysis, the claim, the connection to the real world is the student’s own.

Task 3:

Preliminary Capstone Declaration

Due before Session B Submit via Canvas Assignment

The Capstone Declaration is not a polished proposal. It is a snapshot of your thinking at the beginning of Week 3 where you currently stand on format, collaboration, and the question you are beginning to develop. You will revise all of this. What matters here is that you commit to a direction clearly enough that your Stakeholder Map in Session B has something concrete to organize around.

The course offers two standard capstone formats and one open pathway for students with a clear alternative vision. All three pathways share the same commitments: rigorous analysis, a global dimension, public circulation under Creative Commons, and work that is genuinely useful to an audience beyond this classroom. The format is in service of those goals not an end in itself.

The declaration has three parts. Each is short. Respond to all three before Session B.

Capstone Milestone Week 3

Submit your Capstone Declaration before Session B this week.

Your Stakeholder Map the second Capstone Milestone is due separately before Week 4 Session A. See the Week 3 Module Overview for details.

What This Assignment Is and Is Not

Is: A working declaration of your current direction honest, specific, and provisional. You are not locked in. Declaring something clearly now is what allows the course’s feedback loops (peer review, instructor notes, Stakeholder Map critique) to actually help you.

Is not: A finished proposal, a literature review, or a guarantee of what your final project will look like. Vagueness is not humility it just makes the next milestone harder. Be as specific as you can be right now.

Part 1 Team Status and Format

Declare your working status and your current capstone format preference. Both can change but both need to be named now so your team (if you have one) can begin the Stakeholder Map together in Session B.

Declare	What to include
Working solo or in a team	If working in a team, list your teammates by name. If working solo, say so explicitly. If you are still deciding, say that and name one person you are considering working with.
Capstone format	Choose from the three pathways below. If you are considering Pathway 3, name your format idea here even roughly and include the short pitch described in that pathway’s entry. If genuinely undecided, describe what is pulling you in each direction.

The Three Format Pathways

All three pathways share the same core requirements: rigorous analysis grounded in course frameworks, a global or comparative dimension, public circulation under Creative Commons, and work that is genuinely useful to an audience beyond this classroom. The format is in service of those commitments not an end in itself.

Pathway 1 Standard

Global Case Study Comparison

A comparative analytical paper examining how an AI system, policy, or governance framework operates across two or more national, regional, or linguistic contexts. Analyzes how values, institutions, and historical conditions produce different outcomes. Deposited in the UO Library Scholars Bank under Creative Commons license.

Well suited for: Students interested in research writing, policy analysis, or global studies including those developing work that could evolve into an honors thesis, a publication submission, or a graduate school writing sample.

Pathway 2 Standard

Public Awareness / Education Campaign

A public-facing project social media series, digital exhibit, educational resource, or multimedia campaign communicating key issues about AI, power, and accountability to a broader public audience. Deployed under Creative Commons license in the social media sphere or other public channels.

Well suited for: Students interested in communications, journalism, design, education, or advocacy including those building a portfolio piece that demonstrates public-facing analysis and storytelling to future employers or graduate programs.

Pathway 3 Open Format Instructor Approval Required

Open Format: Inherited Projects and Original Pitches

Pathway 3 is for students whose analytical goals call for something beyond the two standard tracks. It has three sub-options two are inherited projects with real documents and real stakes waiting for you; one is an original pitch you design yourself. All three require an approval conversation before you declare.

Sub-option	What you do
3A Legislative Imagination AADCSA Multi-Cohort Project	You inherit a draft model federal AI bill and serve as adversarial analyst finding where it breaks and passing your findings to the next cohort via a structured contribution template.
3B Community AI Ethics Montubio Case Study	You inherit curated documents from a real suspended AI project with Montubio community leaders in Ecuador. You analyze the project’s design and ethics, then propose what responsible continuation or responsible suspension would require.
3C Original Pitch Design Your Own	You propose a format not covered by Pathways 1 or 2 longform essay, policy brief, podcast, data art, community toolkit, or something else entirely and make the case for why it belongs in this course’s public knowledge commitment.

All three sub-options share the same core requirements as the standard pathways: rigorous analysis grounded in course frameworks, a global or comparative dimension, a concrete public output, and Creative Commons licensing.

If declaring Pathway 3: Include a brief pitch in your declaration (35 sentences) naming your sub-option and answering: What is the format or project? What is your role? And why does this serve your analytical goals better than Pathways 1 or 2? For 3A and 3B, name the specific inherited project and what friction zone or framework you plan to lead with.

Instructor approval required before Week 5. See the for full descriptions and document access. You will receive feedback by the end of Week 3 or early Week 4.

Part 2 Topic and Context

Describe the AI system, context, or problem you are currently planning to investigate. Be as specific as you can “AI and healthcare” is too broad; “algorithmic triage systems in under-resourced hospitals in Brazil and the United States” is a direction you can map stakeholders around.

Respond to the following prompts in a short paragraph (35 sentences is enough):

a	What is the AI system or context you are investigating? Name it as specifically as you can. What does it do? Who deploys it? Where does it operate?
b	What drew you to this topic? A reading, a personal experience, a question from the course. The origin of your interest is relevant it often points toward the ethical stake that will drive the project.
c	What is the global or comparative dimension? This course is rooted in the Schnitzer School of Global Studies. Every capstone project must engage a cross-national, cross-regional, or cross-cultural dimension. Name it even if it is not yet fully developed.

Part 3 Your Driving Question

A driving question is the question that makes your project necessary. It is not a topic sentence or a thesis it is the question your project exists to answer, the one that keeps pulling you forward even when the research gets difficult. A strong driving question is specific, researchable, and carries an ethical stake.

This week, you are applying the interrogation and deconstruction techniques introduced in the course to begin sharpening your question. Use the scaffolded prompts below to develop and test it.

Draft your question

Write your current driving question as directly as you can. It may be rough. It may be too broad. Write it anyway.

Sentence starter: “My current driving question is: ___”

Apply the Four-Question Framework

Run your driving question through the course’s analytical framework. Which of the four questions is your driving question most closely aligned with? Which of the four questions does it leave unasked and should it?

Sentence starter: “My question is most directly asking about [benefit and cost / intelligence / displacement / accountability], because ___. The question I am not yet asking but may need to is ___.”

Name the assumption

Every driving question contains at least one assumption about who matters, what counts as a problem, or what a good outcome would look like. Name one assumption embedded in your current question and say whether you want to interrogate it or build on it.

Sentence starter: “One assumption my question makes is ___. I want to [interrogate / build on] this assumption because ___.”

Who is absent?

Return to Hassan’s most important question: who is absent from the frame? As your driving question is currently written, whose perspective is not represented and what would your question look like if you centered that perspective instead?

Sentence starter: “As currently written, my question centers ___. The perspective that is absent or underrepresented is ___. If I centered that perspective, my question might become: ___.”

Length and Submission

Total length	Approximately 300500 words across all three parts. This is a working document precision matters more than length.
Format	Plain prose or labeled sections whatever makes your thinking clearest. No special formatting required.
Where to submit	Canvas Assignment submission . Due before Session B.
Grading	Completion credit. The declaration is evaluated on specificity and engagement not on the quality of the question itself. A rough, honest declaration earns full credit. A vague one does not.
Team submissions	Each team member submits individually but teams should discuss Parts 2 and 3 together before submitting. Your driving questions do not have to be identical, but they should be compatible.

What Comes Next

Your Capstone Declaration feeds directly into your Stakeholder Map, which you begin in Session B and complete before Week 4 Session A. The driving question you draft here is the organizing question for the map your stakeholders are the actors in the system your question is about.

Formal capstone proposals are not due until Week 7. The work you do now declaring a direction, mapping stakeholders, receiving peer feedback is the foundation that makes that proposal possible. Nothing here is final. Everything here matters.

i need short proposal of all three in 24 hours, for approval from professor

WRITE MY PAPER