20%, Individual. Launches Week 3. Due Week 7.

Ethics Case Analysis

A technology was deployed on people who could not easily refuse it. Something went wrong, or something went right, and everyone is pointing at “the algorithm.” Your job is to get the system on the bench, open it up, and name the part.

The assignment

Every one of these systems is a stack of human decisions: who defined the problem, what data got used, what a high score triggers, who reviews the output, and who bears the cost when it fails. “The algorithm did it” is where lazy analysis stops. Your analysis traces the harm (or the success) to a specific decision, with primary-source evidence, and then proposes fixes assigned to the people who could actually make them.

You rehearsed this in the Week 3 lab, where the class tore down two systems built on the same math, one that triggers investigations (Allegheny) and one that triggers offers of help (LA County). This assignment is the solo performance. The deliverable is a structured document of at most 3 pages (bullets and tables expected) or the stated equivalent for your mode, plus a 5-minute recorded walkthrough.

Download the working template for the default mode: SIL503_teardown_sheet.docx

Whatever case and mode you choose, four things are the graded core: run the sociotechnical protocol, apply NASW values and the NASW Technology Standards by name, trace the outcome to a specific decision with evidence, and propose concrete, role-specific mitigation.

Your case

Pick from the case bank, Option A or Option B. Off-bank cases are welcome with instructor approval (see FAQ).

Option A: a harm case. Your question is where the harm entered and who decided.

• Michigan MiDAS (unemployment fraud detection, the local case)
• Allegheny Family Screening Tool (child welfare)
• Dutch toeslagenaffaire (child benefits)
• Australia Robodebt (benefits debt recovery)
• SafeRent (tenant screening, 2024 settlement)
• TennCare Connect (Medicaid eligibility)
• UnitedHealth nH Predict (coverage denials)
• COMPAS (criminal justice risk scores)

Option B: a success case, analyzed to the identical standard. Success cases are graded with the same rigor plus the conditions-of-success questions: what made it work, whose participation shaped it, and would it replicate without its champions.

• GetCalFresh / Code for America (benefits access)
• LA County Homelessness Prevention Unit (preventive risk scoring)
• Annie MOORE / GeoMatch (refugee placement matching)
• Trevor Project Crisis Contact Simulator (counselor training)
• Te Hiku Media / Papa Reo (Māori-owned speech AI)
• NVDA screen reader (disability-led open source)
• Be My Eyes / Be My AI (visual assistance)
• M-Pesa (mobile money, contested evidence)

Your mode

The mode is only a container for the same analysis. All three carry the same four graded elements and the same rubric.

The Teardown (default)

You are a repair technician making an exploded-view diagram. The teardown sheet has five sections:

1. The system on the bench. What it is, who it acts on, and what a high score or output actually triggers in a person’s life.
2. The parts list. The protocol mapped onto the system: whose problem definition, whose data and labor, what it assumes about users, who bears the risk of failure, what arrangement it locks in.
3. The failure point (or, for Option B, the load-bearing part). The single decision that most separates harm from hope, traced with primary-source evidence.
4. The values diagnosis. Each part run against NASW values (dignity, self-determination, social justice, integrity, competence) and the NASW Technology Standards.
5. The mitigation kit. Two or three concrete moves, each assigned to someone who could make it (designer, deploying org, front-line worker, regulator) and tied to the part it fixes.

The walkthrough is narrated like a repair video. It is the default mode because the method carries over to any system you meet later.

The Second Opinion

A colleague at an organization is about to adopt a technology, or was just burned by one, and asks you for a consult. Write it in the practice register: Situation (what they’re deciding and why now), Background (the system and its track record, evidenced), Assessment (the protocol as your instrument, NASW values as the ethical differential), Recommendation (adopt, defer, or refuse, plus the contraindications: the conditions under which you would not adopt, which is your mitigation section). The walkthrough is the verbal hand-off to the requesting practitioner.

Board Testimony

A board, city council, or oversight committee is deciding whether to keep, kill, or fix the technology. You file written testimony (who you are and your standing, the finding, the sociotechnical evidence, the values argument, the specific ask) and deliver it to camera as if at the hearing. The recording is the centerpiece here and absorbs the required walkthrough. It suits a public-voice entry point.

A compressed sample teardown

The real thing runs up to 3 pages. This 350-word compression of the Week 3 worked example shows the moves.

1. The system on the bench. MiDAS, the Michigan Integrated Data Automated System, was the state unemployment agency’s automated fraud detector. When it spotted a discrepancy between employer records and a claimant’s answers, it did more than flag the file. From 2013 to 2015 it adjudicated: the system itself issued fraud determinations, which triggered penalties of four times the alleged overpayment against people who had just lost a job, collected through garnished wages and seized tax refunds.

2. The parts list. Problem definition: the state’s (catch fraud, cut staffing costs); claimants were never in the room. Data: employer-reported records mismatched against claimant answers, with any discrepancy read as intent to deceive. Assumption about users: a mismatch means a lie. Risk of failure: borne entirely, and automatically, by the claimant. What it locks in: an agency staffed down on the promise that the machine would decide.

3. The failure point. The failure point is not the matching code. The decision that separates this case from an ordinary screening tool is that auto-adjudication was switched on with no human review of fraud determinations. When the determinations were later reviewed, a 93% error rate surfaced, and roughly 40,000 people had been falsely accused. The same software with a caseworker reviewing every flag is a defensible tool; with the reviewer removed, it accused people automatically.

4. The values diagnosis. Dignity and worth: quadruple penalties treated claimants as presumptive criminals. Self-determination: people were penalized by a process they could not see, question, or answer. Competence (and the Technology Standards): the agency deployed a system whose determinations it could not explain or audit. Social justice: the burden landed on people already in economic freefall.

5. The mitigation kit. For the deploying agency: no fraud determination issues without individual human review; the flag advises, a person decides. This repairs the failure point directly. For the legislature: mandatory error-rate audits with a threshold that suspends penalties automatically. Michigan was eventually ordered to refund victims; audits move the remedy from after the harm to before it.

Suggested process

1. Pick your case and mode; read the entry-point source in the case bank (1 hour). Log your AI research plan at the Week 3 launch.
2. Gather primary sources (2 to 3 hours). Court rulings, audit reports, agency documents, the underlying investigations. AI is a fine scout here; it is never a source.
3. Run the protocol (90 minutes). Fill every row before you decide anything. The rows you cannot fill tell you what to go find.
4. Find the decision (1 hour of honest thinking). Locate where the harm enters, or which part carries the load. Test it: if that one decision had gone the other way, the outcome should flip too.
5. Run the values diagnosis (1 hour). Work each NASW value against a specific part. If a value produces only a general sentence, cut it and work a different one harder.
6. Build the mitigation kit (1 hour). Every move gets an owner and points at a named part.
7. Draft into your mode’s structure (2 hours). Tables and bullets are expected; 3 pages is a ceiling.
8. Verification pass (45 minutes). Every claim that came through an AI gets checked against a primary source. Write the disclosure line: tool, what you used it for, what it got wrong or slanted.
9. Record the walkthrough (1 hour, including the retake you will want).

The whole process runs roughly 10 to 12 hours across the weeks between launch and due date.

The 5-minute walkthrough

A good recording is a performance for your mode’s audience, and it is graded on whether a non-technical stakeholder in that role could follow it. Roughly, spend one minute putting the system on the bench in plain language, two minutes on the decision and the evidence for it, one minute on the values stakes, and one minute on what to do and who does it. Do not read your document aloud. Talk to the person who has to trust or distrust this machine tomorrow morning.

Rubric (100 points, scaled to 20%)

Common ways to lose points

• Blaming “the algorithm.” The 25-point line item asks for a decision: a design choice, a data choice, a trigger, a deployment choice, an oversight choice. “The AI was biased” names nothing anyone can fix.
• Decorative ethics. The five NASW values pasted as a closing list score as decoration. They earn their 20 points only when each one is worked against a specific part of the system.
• Unverified AI claims. One confident, wrong, unchecked fact in your evidence section costs you there and undermines everything around it.
• The plant. Some case packets contain one plausible but false “fact” that AI research assistants will cheerfully repeat. Catching it against a primary source earns verification points, and repeating it costs them.
• Mitigation without an owner. “There should be more oversight” is a wish. “The county board requires an annual disparate-impact audit before contract renewal” is a move.
• Option B as press release. A success case retold in the vendor’s voice misses the assignment. You are asked what made it work and whether it would survive its champions leaving.

FAQ

Can I analyze a case that isn’t in the bank? Yes, with approval. Pitch it at the Week 3 launch: name the system, the population it acts on, and two primary sources you already have. If the sources exist, the answer is almost always yes.

Can I pick MiDAS? You can, but the bar is higher: the compressed sample above and the Week 3 seminar walkthrough already do the obvious version. You would need a fresh angle, for example the seven-year accountability fight or the design of the remedy.

What does “3 pages or the stated equivalent” mean? The Teardown and the Second Opinion are documents: 3 pages maximum, structured, tables and bullets welcome. Board Testimony is a written filing of about 2 pages plus the recorded delivery, which is the centerpiece there.

What counts as a primary source? Court rulings and filings, government audits, agency documents, the original investigative reporting (with documents), peer-reviewed evaluations, and first-party statements from the organizations involved. A chatbot’s answer is not a source. A blog post summarizing a news story that summarizes an audit is two steps too far; go to the audit.

How does AI disclosure actually work? A short disclosure line on the submission, in the format the class charters in Week 5: which tool, what you used it for, and what it got wrong or slanted. The “what it got wrong” field is required; leaving it blank reads as not having checked.

Is a success case easier? No. Option B carries the same protocol, the same evidence standard, and the extra conditions-of-success questions. Praising a system is easy; explaining why it holds is the hard, gradeable part.