Changing the world with data. (combatting human trafficking, as an example)

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By Eric Schles PyData New York City 2017 How to create change in the world with technology and data science. I'll use my own journey in combatting human trafficking as an example, extracting out themes from these examples. There will be technical demos throughout, showing the gallery of technical solutions I've used to try to solve this social problem. The intention is to show the audience how these solutions generalize. In doing so, the hope is, participants will be able to solve their own social issues.

Technology

Changing the world with Data.
(Combatting Human Trafficking, As An Example)
By Eric Schles

About Me
Background:
● Economics, Mathematics, Computer Science
Work History:
● Manhattan DAs special victims unit - “real life” Law & Order SVU
● White House as Part of the United States Digital Service
● 18F
● Elucd.com ~ current

It starts with a feeling
Decide on an issue you feel you have to work on,
for me this was ending slavery.

Finding your people
You can’t solve anything on your own.
You need a group of people with you.
We have power in numbers and to keep
The work from burning any one person out.

Build a thing
Demo (craigslist scraper)
&&
Results

Find people effected by the issue you care about
Get their feedback and iterate
on your system with them in mind.

Take your thing on the road
Once I iterated I actually was able to
Build a system that helped people
DEMO
(Investigator)

Stay connected with those across the country
Once you build a system that really works
It’s easy to make more
DEMO
(Document Search)

See the change in the world
Eventually, with enough effort you will get results, but it takes long term effort.
With the combined efforts of many people across the country, the cause to end slavery
has:
● Been able to put the CEO of backpage behind bars, sending a strong signal that
trafficking has costs
● Been able to lift some victims out of slavery and find a better life

Some resources
https://www.fightforthefuture.org/ateams/
--start your own idea and get it funded!
https://tech-forward-2.glitch.me/
---volunteer your time with one of these wonderful orgs
https://lists.44.digital/
--or one of these wonderful orgs
https://flipboard.com/@flipboard/-nonprofits-not-silicon-valley-startups-/f-cde264c75a%2Frecode.net
--AI non-profits

Contact Me
eric@elucd.com
Twitter - @EricSchles
Linkedin - https://www.linkedin.com/in/ericschles
Github: https://www.github.com/EricSchles

In his abstract, Scriffignano summarizes as follows: l explore some of the ways in which the massive availability of data is changing and the types of questions we must ask in the context of making business decisions. Truth be told, nearly all organizations struggle to make sense out of the mounting data already within the enterprise. At the same time, businesses, individuals, and governments continue to try to outpace one another, often in ways that are informed by newly-available data and technology, but just as often using that data and technology in alarmingly inappropriate or incomplete ways. Multiple “solutions” exist to take data that is poorly understood, promising to derive meaning that is often transient at best. A tremendous amount of “dark” innovation continues in the space of fraud and other bad behavior (e.g. cyber crime, cyber terrorism), highlighting that there are very real risks to taking a fast-follower strategy in making sense out of the ever-increasing amount of data available. Tools and technologies can be very helpful or, as Scriffignano puts it, “they can accelerate the speed with which we hit the wall.” Drawing on unstructured, highly dynamic sources of data, fascinating inference can be derived if we ask the right questions (and maybe use a bit of different math!). This session will cover three main themes: The new normal (how the data around us continues to change), how are we reacting (bringing data science into the room), and the path ahead (creating a mindset in the organization that evolves). Ultimately, what we learn is governed as much by the data available as by the questions we ask. This talk, both relevant and occasionally irreverent, will explore some of the new ways data is being used to expose risk and opportunity and the skills we need to take advantage of a world awash in data.

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