Day 1: Biometrics

Part I: The Hook

Welcome to your first day as a forensic investigator! Every person on Earth has a unique set of fingerprints, even identical twins. Law enforcement agencies have used fingerprints to solve crimes for over 100 years.

Today’s Case Briefing: A break-in occurred at a local research lab. The only evidence left behind? A set of fingerprints on a glass door. Your mission: lift, classify, and analyze the prints to help identify the suspect.

Discussion: What other types of biometric data do you think exist? (Hint: Think about your phone — Face ID, fingerprint, voice assistant. Now think bigger: What data does your body give off that you can’t control?)

Part II: The Physical Lab

Materials

  • Fingerprint powder (black or magnetic), 1 container per table
  • Fingerprint brushes, 1 per student
  • Clear lifting tape, 1 roll per table
  • White index cards, 3 per student
  • Magnifying glasses or hand lenses, 1 per student
  • Ink pads, 1 per table (for recording known prints)
  • Printed ridge pattern classification chart (loops, whorls, arches)

Carefully view the below video before conducting the lab: 

Procedure

Step 1: Record Your Own Prints

  1. Press each fingertip firmly onto the ink pad, then roll it onto a white index card. This is your “known print card” and will be used later to compare against mystery prints.
  2. Label each print (thumb, index, middle, ring, pinky) for both hands. Write your name on the back of the card only (not the front).
  3. Use your magnifying glass to identify your dominant ridge pattern: Loop, Whorl, or Arch. Note it on your card.

Step 2: Dust for Latent Prints

  1. Practice the dusting technique first: press your own fingertip firmly onto a clean glass slide or smooth surface.
  2. Gently dip your brush into the fingerprint powder. Lightly dust the surface using small circular motions.
  3. Blow away excess powder gently. You should see the ridge pattern appear.

Step 3: Lift and Preserve

  1. Place a strip of clear lifting tape directly over the dusted print. Press firmly and smoothly.
  2. Carefully peel the tape off the surface and place it sticky-side-down on a white index card.
  3. Label the card with where you found the print and the date. This practice round helps you refine your technique before the real challenge.

Step 4: Classify and Compare

  1. THE MYSTERY SWAP: Now for the real challenge! Each person at your table secretly presses ONE fingertip onto a clean glass slide, then places the slide into the “evidence bin” (a tray in the center of the table). Do not let anyone see which finger you use.
  2. Your team randomly draws slides from the evidence bin. Dust, lift, and classify each mystery print using the steps you just practiced. Then compare each one against everyone’s known print cards to figure out WHO left the print and WHICH finger they used.
  3. Record your findings: for each mystery print, write whose print it is, which finger, and which pattern type (loop, whorl, or arch). How many did your team correctly match?

Step 5: Interactive App

  • Open this interactive guide to see detailed examples of loops, whorls, and arches — then test yourself with a 10-question quiz. Use it alongside your magnifying glass to double-check your print classifications5

Step 6: Reflection Questions 

  1. What ridge pattern type (loop, whorl, or arch) was most common in your group? Why do you think that is?
  2. What challenges did you face when trying to lift a clean fingerprint? How could you improve your technique?
  3. If a fingerprint at a crime scene is smudged, how reliable do you think it is as evidence?

Part III: AI & Digital Literacy

Data Privacy and AI: Biometric Surveillance

Your fingerprints are one form of biometric data — unique physical characteristics that can be used to identify you. But biometrics in 2026 go far beyond fingerprints: facial recognition, iris scans, voiceprints, typing patterns, heart rhythm signatures, and even the way you walk (gait analysis). Apple’s Face ID maps 30,000 invisible infrared dots on your face. Amazon’s palm-scanning payment system (Amazon One) reads the vein pattern inside your hand.

AI systems are trained on massive databases of biometric data to power everything from unlocking your phone to real-time surveillance cameras in airports, stadiums, and even some schools. The FBI’s facial recognition system alone has access to over 640 million photos. But who owns this data? And what happens when it’s collected without your knowledge or consent?

Case Study: The company Clearview AI scraped over 40 billion photos from social media to build a facial recognition database sold to law enforcement — without a single person’s consent. In 2024, Clearview settled a landmark lawsuit and was banned from selling its database to most private companies in the U.S. But the database still exists, and law enforcement agencies in over 30 countries still use it. Your photo might already be in it.

Keeping the above case in mind, carefully view the below video: 

Activity

Step 1: Face Detection vs. Face Recognition 

  • Click here to open  a face-detection tool and begin experimenting with it. Your job is to figure out what the system can detect… and where it starts to fail. Try one face, then two faces. Try turning your face to the side. Try covering part of your face with your hand, hair, glasses, or a hood. Try showing the camera a printed photo, a face on another screen, or even a drawing.  As you test, record what the tool detects accurately and what seems to confuse it. Pay close attention to the difference between a system that simply detects that a face is present and one that actually identifies who the person is.
Step 2: Explore Biometric Tracking with MediaPipe Studio
 
  • Click here to open MediaPipe Studio and choose a tool that tracks part of the human body, such as a face detector, face landmark model, hand tracker, or pose tracker. Your job is to investigate how AI turns a person into measurable data. Begin by using the tool normally and watching what appears on the screen. Notice the points, lines, boxes, or landmarks the system places on your body or face. Then begin experimenting. Move closer and farther away. Turn to the side. Change your expression. Move quickly, then slowly. Cover part of your face or hand. Change the lighting if possible. If you are using a pose tool, try unusual body positions or partial movement off screen. As you test, record what the system tracks well and what causes it to lose accuracy. Pay attention to the fact that the AI is not simply “seeing” you … it is reducing your body into coordinates, patterns, and data points that can be measured and analyzed.
Step 3: Become the AI Trainer
 
  • Click here to open Teachable Machine and build a simple image classifier of your own. Your goal is to train a model using examples you choose so that you can experience how AI systems learn from data. You might create categories such as real face vs. printed face, masked vs. unmasked, or one expression vs. another. As you build your model, notice how much the results depend on the examples you provide. If your examples are too similar, too limited, or unbalanced, your model may perform poorly or make strange mistakes. Test your model several times and record where it succeeds and where it fails. This step is meant to help you see that AI systems are only as strong as the data they are trained on, which raises important questions about fairness, bias, and trust when biometric systems are used in the real world.

Step 4: Interactive App

  • Reopen the app and tap the “Learn More” tab for the history of fingerprinting, how AFIS/NGI works, and forensic biometrics career paths. Useful context for the debate prep.

Step 5: Reflection Questions 

  1. Do you think the benefits of biometric AI (safety, convenience) outweigh the risks (privacy, misuse)? Why or why not?
  2. Who should have the right to collect your biometric data, the government, companies, both, or neither?
  3. If an AI system incorrectly identifies someone as a criminal based on facial recognition, who is responsible?

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