Eric Schles on Fighting Human Trafficking with Python - Episode 12

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Brief Introduction

  • Date of recording – June 10th, 2015
  • Hosts Tobias Macey and Chris Patti
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  • Overview – Interview with Eric Schles

Interview with Eric Schles

  • Introductions
  • How did you get introduced to Python?
  • What inspired you to take up the fight against slavery? Is there personal story behind this choice?
  • Some of your work touches on the “Deep Web”. Can you provide listeners with some context around what that term means and role it plays in what you do?
    • Tor .onion sites (Hidden Services) are examples
    • Anonymous Web Experience
    • Anonymity allows for illegal, immoral things like buying selling people
    • Conceptually very important idea
    • Bruce Schneier – Web technologies need to be more privacy aware
    • Like a really scary version of “The Internet of the Old Days”
    • Photos of young, exploited men and women
    • Pedophiles are building communities, having parties through these hidden services
    • Eric feels that Tor is an extreme
    • Feels there had to be a way to protect the rights of legitimate while protecting against pedophiles
    • Maybe a voting system?
    • The Tor project feels that any compromise lessens the that’s so important for people in embattled or countries (Worded that poorly -Chris)
    • No metrics on the amount of pedophilia that actually happens Tor – probably a lot
    • Sexually abused victims of trafficking grow up damanged unable to do anything else
    • Consumers of this type of porn were often themselves victims sexual abuse
    • Structural dissonance which exists to create this problem society needs to be addressed
    • Google puts the number to the anti-trafficking hotline at top of any trafficking search results
    • Darren (Derek?) Hayes – redirect to trafficking resources when viewing advertisements for victims trafficking
  • Why did you choose Python as opposed to any other tool for your search engine?
    • Needed solutions quickly with the ability to evolve as needed
    • Able to rapidly develop and incorporate new features rapidly
    • Easy to scale as needed
    • Flask is easier to prototype and iterate with
    • Python data science tools make the analysis easy
    • Able to finish a 2 year C++ project in 3 weeks using Python
    • Doing data science in Ruby is challenging
    • Pandas Dataframe galvanized the creation of a lot of other useful tools
    • Vincent – write Python which compiles to D3
  • Can you provide a high level description of the technical details the search engine that you created, and what it’s like to with Tor through Python?
    • Directed search engine
    • “It would be like if you went to Google but everything watched was Porn which you were uncomfortabl seeing and you sad”
    • Get most case information through regular old detective work
    • Person arrested / in holding yields phone number, other attributes that can feed the search engine
    • Google can’t scrape the deep web
    • Memex tool indexes the deep web – Eric’s search engine uses that
    • Eric does design work for the Memex project
    • Developed by the amazing Chris White
    • Eric’s search engine uses the Tor driver in Selenium to .onion sites
  • What are some of the technical and legal challenges that you experienced in the course of your work?
    • Most of the technical challenges are around automated processing
    • Legal structure provides some limits on what can be worked on
  • Does your search engine try to infer who might be engaged in work voluntarily as opposed to those being forced into it their will?
    • No, because they get all their case referrals from detective work
    • You have to have been hospitalized or in some other way come the attention of the authorities for being deprived of rights
    • Trafficking looks very different in different cultures
    • Global similarities
    • Afraid to say why if hurt
    • Forced into having sex against your will
    • Clear patterns of indication
    • Urban versus Suburban versus Rural
    • Fracking towns
    • Demographics are very different – mostly men very women, LOTS of ads for sex workers
    • Only helping people that want to be helped
  • What was the most surprising fact you uncovered as part of research?
    • Imagery of exploited children is so depressing and sad
  • Without revealing anything you shouldn’t, are you aware of being set free as a result of your work?
    • “Not my work, our work”
    • Not an individual effort
    • lawyers, analysts, larger DAs office
  • Given the complicated socio-economic aspects of human and prosecution of those who are responsible, can you discuss of the moral and ethical considerations that you have confronted with while building these tools?
    • Privacy is the biggest concern
    • Open source book to teach colleagues at the DA’s office how program to in Python
    • Sometimes Eric works at Civic Hall
  • Are there any projects out there that you consider similar to you are working on?
  • What would it take for other municipalities and law agencies to get started with using your tools?
  • How can our listeners get involved and help you with this Chris
    • Tweet at @EricSchles or E-mail Eric
    • Volunteer for any of the non profit anti-trafficking groups
  • Message to the community: There is a world of good waiting to happen

Picks

Keep in Touch

More From Eric

  • He presented at PyGotham 2014
  • He also talked at the Open Data Science Conference 2015 Boston

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

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