“Double Baking” Beliefs and Integrating Systems with FRDM
As a student of multiple interdisciplinary sciences, I am constantly thinking about ways to integrate.
Be it disparate ideas, distant friends, even conflicting perspectives - I love that we can use our mind to resolve conflicts or contradictions. So I am excited when I find opportunities to do so, especially in times when I think that I see the world so clearly, but it turns out to differ from another’s viewpoint.
One of these ideas that seems really clear to me is role of slavery. I would think that societally, we can all agree that it is wrong — yes? However, there are currently more slaves in the world today than there have been in recorded history. Slavery can be defined as “being forced to work without pay, under threat of coercion or violence, for the purposes of exploitation or bondage, against one’s own will”. According to the International Labor Organization (ILO), 40.3 million people face slavery today, and of these victims, 25% of them are children and 75% are women or girls. (Source)
So why is this happening? Zooming in from massive/structural explanations a bit, it turns out that humans hold a lot of conflicting belief systems (thank you, Cognitive Science degree). For example, I may believe that humans contribute to climate change with our consumption patterns, and also still believe that is okay to use single-use plastic (as evidenced in my own personal use of them (sorry world)). Because of how many conflicting beliefs we have, it is unrealistic that we align all of our actions with all of our beliefs. That’s a full time job! So, we pick and choose what our most important values are, and try our best to live up to them. Compounded over everyone in society, some important values can get lost in the sauce.
Double Baking Beliefs
Whether we like it or not, we tend to encounter moments that motivate us to re-examine and update our contradicting belief systems. An old philosophy professor of mine called this update “double baking” a belief. One of these moments for me was back in 2017 when I was preparing for the United Nations Commission on the Status of Women (CSW). I learned that there was a group of delegates a couple of years before me who had set out to dismantle some human-trafficking hot spots (mostly hotels) in NYC. The two weeks of programming at the CSW opened my eyes to the “world of work” for many women worldwide, and it was terrifyingly illuminating to learn about the current oppressive conditions of work that are still in practice today. It made me want to question my belief system — is what am I doing with my time contributing to a world I want to live in, or not?
I’ve been grappling with this realistic idealism and how to find meaning in life choices as long as I can remember, and presently I feel that gradualism is key to integrating realism and idealism. We can change the world, just, gradually. This is something that I felt at the United Nations that year, something that I continue to see in my brave classmates choosing to pursue a rapid-fire program to “level-up” in Data Science, and in the constantly evolving world around me. We are all working together to figure out what we need to do in order to be where we want to go, one step at a time.
Data Science Applications
For the Individual
This is why, upon finishing Weapons of Math Destruction by Cathy O’Neil (see my past blog on this), I was so excited to read about one of the positive examples of predictive algorithms that a Harvard PhD researcher, Mira Bernstein, was building. The model is intended to scan vast industrial supply chains and find signs of forced labor. She made it for a nonprofit called “Made in a Free World”. I am very curious to learn more about the inner workings of that particular model, and hope to have more to report back on in the near future. Until then, I’d like to share a bit more about the organization that Bernstein partnered with, to understand the path of how a nonprofit can go from idea to mass implementation of a data-driven solution.
In 2008, Justin Dillon made his directorial debut in the film Call + Response, spreading the message that there are more slaves today than ever before in human history. In 2009, he founded “Made in a Free World”. This is the org that Bernstein worked with. In 2011, Justin then founded the nonprofit organization Slavery Footprint. Partnering with the U.S. State Department, they launched a multiple-award-winning website that asks the question, “How Many Slaves Work For You?”. Similar to looking at our own carbon footprint, “Slavery Footprint” allows us to see which daily choices we make contribute to inhumane working conditions (hint: it’s a lot).
I think that this is a valuable way to begin acclimating oneself with the reality of the world. Back in the day, taking one of those “carbon footprint quizzes” gave me a chance to better grasp my own personal impact, and maybe make more choices that help my alignment with the future I want to see happen.
But as we know, climate change isn’t going to stop with just the individual. It’s simply too large-scale of an issue! I’ve heard many folks talk about how the most effective action against further climate change is not simply stopping driving cars or eating meat (not to diminish the importance of these actions!), but implementing effective policies to address the issue.
For Industry
So what about the modern day slave trade — would policy shifts be a good solution here, too? Well, let’s go back to Mira Bernstein’s model.
Her work seems to be most widely implemented in a “Software as a Service” tool called “FRDM” (Forced Labor Risk Determination and Mitigation). Similar to the Slavery Footprint, the goal is to instead help companies root out the slave-built components in their products. The hope is that companies will be incentivized by the fear of a potentially devastating brand association. President Barack Obama and Secretary of State John Kerry have both endorsed their work and have asked the organization to assist with purifying the federal government’s supply chains, which are the largest in the world. They have also partnered with businesses like SAP to disrupt illicit slave markets through the use of big data. FRDM can analyze a company’s data to identify “hot spots” for forced labor in their supply chain, and helps them in mitigating the damage done.
As a data science student, I was curious about what went into the building of this model (hopefully more on this later). From WMD, we know that Bernstein “collected data from a number of sources, including trade data from he United Nations, statistics about the regions where slavery was most prevalent, and detailed information about the component going into thousands of industrial products”. This all goes into the model to score a given product from a certain region on the likelihood that it was made using slave labor, and then generate a user-friendly dashboard to learn more. The idea is that the user would contact the supplier in question and ask them to share more about where they are getting the different parts of the product. This information would then come back to Bernstein to study the feedback and update the model.
So does policy address the issue? At this point in time, international politics and global unity is so precarious that the idea of agreeing upon — let alone implementing and scaling — policies/preventative measures worldwide seems very unlikely. However, a lightweight and consumer-driven system may have the potential to spark healthy pressure on manufacturers to take greater consideration when choosing materials. Slavery Footprint and FRDM seem like a really great start to weeding out the massive industry of human trafficking, and helping to “double-bake” the collective beliefs that make up our world.
