3 ms·

Hi. I'm one of the project creators. Happy to answer any questions.

• panarky 9y ago
  As a proof of concept, we have downloaded the pictures of 7000 corporate executives whose LinkedIn profiles suggest they work for financial organizations, and then averaged their faces to produce generalized white collar criminal subjects unique to each high risk zone. Future efforts will allow us to predict white collar criminality through real-time facial analysis. I'm guessing that's a riff on this? https://arxiv.org/pdf/1611.04135v1.pdf https://arxiv.org/pdf/1611.04135v1.pdf (Automated Inference on Criminality using Face Images) Too bad there haven't been enough arrests of financial criminals to get actual mugshots.
• refractal 9y ago
  I tried to use your app but I still got defrauded. 2/5 stars
• mjfl 9y ago
  What specifically are you trying to say/show with this satire? I mean I get the point but I think you are underestimating the usefulness of models for predicting white collar crime and crime in general by giving a really bad model for doing so. In terms of data analysis, the geotag stuff has decent specificity in terms of narrowing down your universe (from entire US to city blocks), but the face stuff probably doesn't have very good specificity (probably lots of false positives there). A good "data science" person would probably try to find factors with higher specificity. But most of the stuff in this model is already known via common sense and acted upon. The SEC knows to look for white collar crime in Manhattan and not Lebanon NH without such a model.