NEW ORLEANS — For two years, New Orleans police secretly relied on facial recognition technology to scan city streets in search of suspects, a surveillance method without a known precedent in any major American city that may violate municipal guardrails around use of the technology, an investigation by The Washington Post has found.
Grade Level: High School (Upper Grades) / Undergraduate
Subject Areas: Civics, Government, Social Studies, Technology & Society, Ethics in Public Policy
Learning Objectives
By the end of this lesson, students will be able to:
- Understand the real-world application of facial recognition technologies in a civic context, using New Orleans as a case study.
- Analyze the legal, ethical, and civil liberties implications of real-time surveillance tools.
- Evaluate competing perspectives from various stakeholders, including law enforcement, civil rights organizations, technologists, and policymakers.
- Critically examine the relationship between surveillance technology and democratic accountability.
- Connect local developments in surveillance technology to national and international debates about privacy, due process, and social equity.
Lesson Outline
1. Introduction: Framing the Inquiry
Begin with a probing question:
“What comes to mind when you hear the term ‘facial recognition’? Who uses it — and for what purposes?”
Facilitate a brief class-wide reflection on how students encounter this technology in daily life — unlocking phones, airport security, or social media. Then pivot to civic uses:
“Today we’ll investigate a real-world case in New Orleans that has raised serious questions about government surveillance and civil liberties.”
Introduce facial recognition as both a technological tool and a subject of ethical and legal debate, particularly in law enforcement contexts.
2. Case Summary: The New Orleans Example
Present key findings from “Police secretly monitored New Orleans with facial recognition cameras;” The Washington Post.
- New Orleans police used real-time facial recognition in conjunction with a privately managed surveillance system (Project NOLA), comprising over 200 live-feed cameras across the city.
- This usage was conducted in apparent violation of a 2022 municipal ordinance that limited such technology to specific violent crime investigations and required transparency and reporting.
- Internal records revealed that officers often failed to document facial recognition use in arrest reports or disclose it to the city council.
- Civil liberties groups argue this constitutes a dangerous overreach and a breach of public trust.
Encourage students to consider why local ordinances regulating surveillance might exist — and what happens when those regulations are bypassed.
3. Primary Source Analysis: Voices and Perspectives
Look at quotes from journalists below:
“This is the facial recognition technology nightmare scenario that we have been worried about. This is the government giving itself the power to track anyone — for that matter, everyone — as we go about our lives walking around in public.”
— Nathan Freed Wessler, ACLU The Washington post
“Police were only supposed to use the software to find ‘specific suspects in their investigations of violent crimes,’ according to the city ordinance… But the investigation found these cameras ‘played a role in dozens of arrests,’ most never disclosed.”
— The Washington Post, summarized in The Independent The Washington post
Use these to prompt a brief textual analysis: What values and concerns are being expressed? What assumptions underlie these positions?
4. Group Dialogue: Stakeholder Perspectives
Organize students into four groups, each representing one stakeholder perspective:
- Law Enforcement Officials: Prioritize public safety and crime deterrence
- Civil Liberties Advocates (e.g., ACLU): Defend privacy, due process, and legal transparency
- City Government / Oversight Bodies: Struggle to balance innovation, regulation, and accountability
- General Public / Local Residents: May be unaware, concerned, divided, or supportive
Discussion prompts:
- What benefits and harms might stem from this kind of technology?
- How should cities ensure accountability when powerful tools are used by police?
- Is real-time facial recognition compatible with democratic civil liberties?
- Should the use of such tools require public consent or notification?
- What checks and balances should exist when police gain access to advanced technologies?
Each group prepares a brief presentation or statement summarizing their analysis.
5. Class Debrief: National and Global Context
After hearing from each group, facilitate a whole-class synthesis. Introduce broader context with a few key points:
- Wrongful Arrests Due to Facial Recognition: Randal Reid (2022), a Black man arrested in Georgia based on a Louisiana warrant generated by faulty facial recognition data. Ap News
- Systemic Bias in AI Systems: Refer to the groundbreaking Gender Shades study (Buolamwini & Gebru, 2018) that showed commercial facial recognition systems are less accurate for women and people of color. MIT News
- Oversight Challenges: The GAO and NIST have documented inconsistent practices across U.S. law enforcement agencies regarding facial recognition oversight and testing for racial bias. GAO Report
- Policy Trends: Cities like San Francisco, Portland, and Boston have banned or tightly regulated facial recognition for policing due to these concerns. BBC
Ask: How do these cases shape our understanding of the relationship between technology and civil rights?
6. Reflective Writing / Assessment
Invite students to respond individually to the following prompt:
Do you believe the benefits of real-time facial recognition in policing outweigh the risks to privacy and civil liberties? Why or why not? Support your answer using at least one fact, quote, or stakeholder position discussed today.
Encourage depth of thought, nuance, and evidence-based reasoning.
Extension / Homework Options
Research & Compare:
Investigate another city or country’s policy on facial recognition technology in law enforcement. Possible examples: London’s CCTV network, China’s social credit system, Canada’s ban on Clearview AI. Compare and contrast with New Orleans.
Civic Engagement:
Write a letter to a city council member or state representative expressing your opinion on the use of facial recognition technology in public safety. Include researched references and propose policy recommendations.
Key Takeaways
- The New Orleans case exemplifies a concerning trend of law enforcement leveraging cutting-edge surveillance tools in ways that may conflict with democratic oversight.
- Real-time facial recognition introduces risks of racial bias, mistaken identity, erosion of public trust, and civil liberties violations, especially when used without transparency.
- As surveillance technologies become more powerful, it is critical for educators, students, and citizens to engage in informed debate about ethical boundaries, regulatory safeguards, and democratic accountability.
- Public engagement, legal regulation, and interdisciplinary education are essential in shaping how societies manage the tension between security and freedom in the digital age.