CIRCLE WITH A DOT

@stepheneb thank you. It was almost as much work as it was fun to put together. A bunch of things just clicked.

@blogdiva if you want just one bookmark, this blog post puts it all in one place (and even adds a bit) https://suffolklitlab.org/algos-bias-due-process-you/

@blogdiva D, there isn't enough information/no way to know given just the info in the question. You need to know how prevalent the thing you're testing for is before you can venture a guess. See e.g., https://bail-risk-simulator-50382557550.us-west1.run.app/

@D_J_Nathanson yes, they were competing against each other, but the pacing buddy wasn't one of their peers. It was just a script that made it look like someone was just a head of them. All the "AI" suggested flags were per-determined. So nothing they did would effect the "AI" but of course, how carefully they read the materials effected their own performance.

@JeffGrigg That's a measure of the tool's flag/recommendation accuracy, which was perfect in 1 and 2. So, the students were never quite as good as the tool though it did make them better in phase 2 than they were in phase 1. It was a highly-engineered scenario (unlikely to occur IRL) designed to make falling victim to automation bias likely.

@anwagnerdreas also, thank you. You are very kind.

@anwagnerdreas yes, though the last exercise didn't have the time to breathe I would have liked. In my own classes I usually take things a lot slower, but this was a guest lecture, and last year one of my students told me my Ai & the Law class was the first time they had been shown any of Ai's downsides. So, I wanted to make sure I got as much in as I could. The simulations really helped folks jump right into conversations. And yeah, our students are great!

33/End

Thank you for making it all the way to the end. I'm pretty sure this is the longest thread I've ever written. If you came in halfway through & thought, "this should have been a blog post," I agree, and here it is: https://suffolklitlab.org/algos-bias-due-process-you/

32/ Man, I love my job. Stay warm. Stay safe. Stay free.

31/ As we packed up, I invited them to revisit the question that preceded the first exercise:

What makes something a good decision assistant?

I reminded them every sim was a decision assistant, told them it had been an honor to be their teacher for the day, & that I was always available to talk.

30/ I left them with my most charitable reading of the theory of fairness consistent with ICE actions. The last question, "how is this consistent with constitutional guarantees of due process?" was, as they say, "left as an exercise for the reader."

29/ As they clicked away at the simulation, I reminded them of Blackstone's ratio.

28/ They were provided w/ the following simulation comparing due process to medical screening & diagnostic tests. It lets you explore how changes to thresholds at different points in the process effect different measures of cost. https://screening-vs-diagnostic-tests-50382557550.us-west1.run.app/

27/ They were. I speculated that the "targeted operations" cited were possibly driven by ‘ELITE’: The Palantir App ICE Uses to Find Neighborhoods to Raid⁷ and presented the following questions for them to consider in their groups.

⁷ https://www.404media.co/elite-the-palantir-app-ice-uses-to-find-neighborhoods-to-raid/

26/ I then asked if folks were familiar with the two incidents reported here:

ICE Arrest of a Citizen, Barely Dressed, Sows Fear in Twin Cities https://www.nytimes.com/2026/01/20/us/chongly-scott-thao-ice-arrest.html?smid=bs-share

and

ICE detains five-year-old Minnesota boy arriving home, say school officials https://www.theguardian.com/us-news/2026/jan/21/ice-arrests-five-year-old-boy-minnesota

25/ It was only later in the week, after I taught the class, that a few Senators introduced the ICE Out of Our Faces Act. https://arstechnica.com/tech-policy/2026/02/ice-out-of-our-faces-act-would-ban-ice-and-cbp-use-of-facial-recognition/

24/ Then I told them that there actually was a federal law enforcement agency actively using facial recognition out in the real world called ICE, and I asked what safeguards folks thought they had in place… Things got a bit quiet, and I shared the following reporting. https://www.404media.co/ices-facial-recognition-app-misidentified-a-woman-twice/

23/ Some folks suggested requiring equal treatment of populations before they would consider using the tech; others, setting high thresholds. We talked about requiring warrants before running a check, & I shared how MA has attempted to address these issues. https://www.nytimes.com/2021/02/27/technology/Massachusetts-facial-recognition-rules.html

22/ Here's the simulation they were asked to explore while considering the above. https://facial-recognition-bias-sim-50382557550.us-west1.run.app/

21/ Only now did I introduce the reporting on machine bias, sketching out the broad strokes. I focused on the fact that these tools can make different predictions for different populations based on their training data. Finally, I presented them with their role play.