The Machine and the Margin: What Slavery’s Technology Teaches Us About Today
A Reflection Using the See · Judge · Act Method
There is a temptation, when we study history, to place ourselves safely on the correct side of it. We read about slavery and think: I would never have done that. I would have known better. But history does not offer us that comfort so easily. The dynamics that shaped American slavery — the way technology concentrated wealth while multiplying the vulnerability of the most powerless — are not buried in the past. They are running on our phones. They are embedded in the algorithm that rates your delivery driver. They are built into the supply chain that made the shirt on your back. That is the thesis of this reflection: the same patterns that enabled slavery still shape how technology distributes power today.
This is not an argument that today’s injustices are identical to slavery. They are not, and the distinction matters. But the pattern — the way technology is wielded to extract maximum value from the bodies of the most marginalized — demands our attention. That is the question this reflection asks us to face. The See · Judge · Act method, rooted in Catholic Social Teaching and used across many justice traditions, gives us a discipline for that attention. First, we look honestly. Then we evaluate morally. Then we respond.
See — Looking Clearly at What Is
The first movement asks us to resist the instinct to look away. To observe, without flinching, the reality in front of us — and to recognize its shape.
The Cotton Gin and the Gig Economy Algorithm
In 1793, Eli Whitney’s cotton gin made separating cotton fiber from seeds roughly fifty times faster. It seems, on the surface, like a story of progress. But the gin did not reduce the demand for enslaved labor. It exploded. Because cotton suddenly became so profitable, slaveholders needed more land, which in turn required more people to work it. The enslaved population in the American South grew from around 700,000 in 1790 to nearly four million by 1860. The technology did not liberate — it multiplied bondage, because the economic system ensured that efficiency gains flowed entirely upward, to those with ownership. This pattern will reappear throughout this reflection.
Now consider the gig economy. Platforms like Uber, DoorDash, and Amazon Flex promise flexibility. But algorithmic management sets the prices, the routes, the ratings, and the “deactivation” decisions — often with no human oversight and no meaningful appeal. When the algorithm gets more efficient, the worker does not earn more. The company does. Drivers take on the full risk of car maintenance, health insurance, and income volatility, while the platform captures the gains. The structure is different. The logic is the same.
Slave Passes and Workplace Surveillance
The institution of slavery required a surveillance infrastructure. Printed slave passes controlled movement. Wanted posters with physical descriptions helped track down those who escaped. Armed slave patrols — an early form of American policing — operated across the South as an enforcement mechanism. The printing press and ironwork technology made this system scalable: bureaucracy in the service of bondage.
Today, Amazon warehouse workers are tracked in real time by handheld scanners that measure their “time off task.” Delivery drivers are monitored by AI-powered cameras inside their vehicles. Gig workers receive algorithmic performance scores that determine whether they continue to work, often with no human to appeal to and no explanation offered. The technology is different. The function — using data to discipline the bodies of working people — is continuous. This continues the same pattern of control.
Northern Mills, Global Supply Chains, and the Distance of Innocence
The textile mills of New England and Britain were not slave plantations. But they were the reason for them. The industrial loom created an insatiable appetite for raw cotton, which meant that Northern and British industrialists were economically bound up with slavery while remaining geographically — and, they told themselves, morally — distant from its violence. The cotton passed through many hands before it became a garment. Distance, they believed, conferred innocence.
Today, global supply chains for electronics, clothing, and food depend on labor conditions that, in many cases, include forced labor, extreme wage suppression, and dangerous working conditions — often in countries far from consumers. A smartphone contains minerals extracted under coercive conditions. A fast-fashion garment was likely sewn by a woman earning dollars a day. Technology makes global supply chains faster and more efficient. It also makes it easier for the worker to hide. Distance still invites innocence, but the system remains connected.
Slave Notices and Predictive Policing
The printing press made it possible to distribute descriptions of enslaved people who had escaped, framing Black bodies as property to be recovered. The technology of categorization — of surveillance and classification — was race-coded from the beginning. Blackness was the marker of suspicion.
Facial recognition software trained on predominantly white datasets misidentifies Black faces at significantly higher rates. Predictive policing algorithms, built on historical crime data that reflects decades of racially biased policing, systematically over-police Black and brown communities. A man in Detroit was arrested based on a facial recognition match that was wrong. The technology was presented as objective. But there is no neutral algorithm — only the values, biases, and choices of those who built it, encoded and automated at scale. The pattern is clear: classification becomes control.
Judge — Evaluating What We See
Observation without evaluation leaves us passive spectators to injustice. The second movement asks us to bring our deepest moral commitments to bear on what we have seen. This is the test of the reflection: what does the evidence demand of us?
Technology Is Never Neutral
The most persistent myth surrounding technological development is that tools are neutral — that a cotton gin is just a machine, that an algorithm is just math. But every technology is designed within a social context, deployed by people with interests, and shaped by the question: whose problems is this meant to solve? This question keeps the reflection on track. This is why the thesis matters: technology does not simply reflect power; it helps organize it.
The cotton gin was not designed to harm enslaved people. But it was deployed within a society that treated Black people as property, and so its efficiency became their suffering. The hiring algorithm was not designed to discriminate. But when it is trained on historical data from a workforce that systematically excluded women and people of color, it replicates and automates that exclusion — and does so at a speed and scale no human recruiter ever could.
To claim that technology is neutral is itself a moral stance. It is a choice to ignore context, history, and whose bodies bear the cost of “progress.” Justice requires us to reject that claim.
Human Dignity Is Not Negotiable
At the center of most justice traditions — and explicitly in Catholic Social Teaching — is the conviction that every human being possesses inherent, irreducible dignity. Not because of what they produce. Not because of their market value. But because they are human.
Slavery’s foundational crime was to deny this. It valued a person not for who they were, but for what they could extract. The plantation ledger recorded pounds of cotton picked, not names, not stories, not suffering.
The warehouse productivity score, the algorithmic deactivation, the facial recognition database — these systems do not recognize persons. They process units. They optimize outputs. And when a human being is reduced to a data point in an optimization function, something essential is violated, regardless of whether we call it slavery or not. The question justice asks is not only: is this legal? It is: Does this honor the dignity of the person? This is the moral test running through the examples.
Whose Bodies Bear the Cost?
This question cannot be answered without naming race. American slavery fell overwhelmingly on Black people, and its economic and psychological legacy has never been fully reckoned with. Today, the workers most subjected to algorithmic control, most exposed to dangerous conditions in warehouses and fields and gig routes, most likely to be wrongly identified by facial recognition software, most likely to be targeted by predictive policing, are disproportionately Black, brown, and immigrant.
This is not a coincidence. It is a pattern. And the pattern requires explanation.
When the same population that was enslaved, then subjected to Jim Crow, then redlined, then mass-incarcerated, is now the population most harmed by algorithmic labor management and surveillance technology, we are not looking at a series of unrelated accidents. We are looking at a structure. Justice requires us to name that structure — and to resist the comforting notion that because individual engineers did not intend harm, no harm exists. The throughline is not incidental; it is systemic.
Distance Is Not Innocence
The Northern mill owner did not hold the whip. But he bought the cotton, built his wealth on it, and when abolitionists came to his door, he often argued that disrupting the cotton trade would be economically ruinous. Distance from the violence did not mean he was uninvolved in the system. It meant he could afford to tell himself that he was.
Today, we are the mill owners. We carry phones assembled by workers living in company dormitories under conditions documented and reported for decades. We order goods delivered by drivers who cannot afford health insurance. We use platforms that employ contractors with no labor protections. The reporting exists. The knowledge is available. What we do with it — that is the moral question. This is where distance becomes responsibility.
Willful ignorance, in the age of investigative journalism and supply chain transparency tools, is itself a choice. And it is a choice that has consequences for real people.
Act — Responding with Intention
The See · Judge · Act method does not end in analysis. It ends in response. But responses can happen at many levels, and no single person is responsible for dismantling every unjust system. What is asked of each of us is that we act from where we stand, with what we have, in the direction of justice. We must refuse the comfort of distance, name the systems that shape our lives, and choose actions that restore dignity rather than extract value. That is the conclusion this reflection reaches: if technology shapes power, then our response must shape it toward justice.
At the Personal Level: Ask Who Made This — and How
The abolitionist movement of the late 18th century used a boycott of slave-produced sugar as a form of moral witness. Hundreds of thousands of British households refused to buy sugar grown by enslaved people. It did not end slavery immediately. But it made visible a connection between consumer choice and human suffering that people had been encouraged not to see.
Today, tools exist to help consumers investigate the conditions under which products are made. Organizations like Good On You rate fashion brands on labor practices. Know The Chain audits supply chains in electronics, food, and apparel. The Fair Trade certification system, despite its imperfections, attempts to guarantee minimum standards for producers. None of these tools is perfect. But choosing to ask the question — who made this, and under what conditions? — is itself an act of moral seriousness.
At the Community Level: Support Worker Organizing
Amazon warehouse workers have staged walkouts and organized campaigns. Rideshare drivers in multiple cities have gone on strike for better conditions. Domestic workers — overwhelmingly women of color — have organized for basic labor protections that most workers take for granted. These are not new tactics. They are the same tactics that ended child labor, established the eight-hour workday, and made workplaces minimally safer in the early 20th century.
Supporting worker organizing means, at a minimum, paying attention. It can also mean financially supporting labor justice organizations, showing up at public hearings, amplifying worker voices in your community and congregation, and refusing to cross picket lines. The struggle for worker dignity is old. The workers fighting it today deserve the same solidarity that the labor movement’s heroes now receive in history books.
At the Civic and Policy Level: Demand Algorithmic Accountability
Technology policy is labor policy is racial justice policy. These are not separate domains. The choices encoded in hiring algorithms, facial recognition databases, and predictive policing software are policy choices — made by corporations and governments — that have profound consequences for real people.
Advocacy in this space looks like: supporting legislation that requires algorithmic transparency and independent audits for racial bias; demanding that gig workers be classified as employees with full labor protections; opposing the use of unaudited facial recognition by law enforcement; and insisting that public procurement of AI systems include mandatory civil rights impact assessments.
This is not utopian. It is the same kind of legislative advocacy that produced the Civil Rights Act, the Voting Rights Act, and the Fair Labor Standards Act — each of which was once called radical, and each of which is now recognized as a baseline of basic decency.
At the Institutional Level: Examine Our Own Practices
Churches, schools, hospitals, and nonprofits are not exempt. They purchase goods. They use delivery services. They deploy HR software. They invest endowments. They are embedded in the same economic system as everyone else.
Institutions can audit their own supply chains and adopt responsible procurement policies. They can review the algorithmic tools they use in hiring and evaluate them for bias. They can divest from companies with documented records of labor exploitation. They can use their public voice — their sermons, their statements, their educational programming — to name what is happening and invite their communities into response.
The question is not only: what are corporations doing? It is: what are we doing?
Closing: The Moral Imagination Required
Frederick Douglass published The North Star. Harriet Beecher Stowe wrote Uncle Tom’s Cabin. Sojourner Truth spoke from platforms across the North. These were acts of moral imagination — attempts to make the invisible visible, to make the distant close, to make the abstract human.
We need that same moral imagination now. Not to equate the suffering of enslaved people with the conditions of today’s gig workers — the differences are real and matter. But to recognize that the impulse to extract maximum value from the bodies of the most vulnerable, and to use technology to do it more efficiently while obscuring it more thoroughly — that impulse is not a relic. It is contemporary. It is active. And it is calling for a response.
The See · Judge · Act method does not promise that the response will be easy, or that it will succeed quickly. History does not offer those guarantees. What it does promise is that clarity, moral seriousness, and action — even imperfect action — are better than the comfortable distance of the uninvolved.
The machine does not decide who bears its costs. We do.
Questions for Reflection and Action
These questions are intended for individual journaling, small group discussion, or community discernment. They are not meant to be answered quickly.
1. Where am I, the mill owner? In what areas of your daily life are you benefiting from a system whose costs fall on people you cannot see? What would it take to look honestly at one of those systems — and what would change if you did?
2. What does “technological neutrality” protect? When someone argues that an algorithm or platform is “just a tool,” whose interests does that argument serve? Who is protected by the claim of neutrality, and who is exposed by it?
3. What is the difference between being uninformed and choosing not to know? Given that information about supply chains, algorithmic bias, and gig worker conditions is widely available, at what point does not-knowing become a moral choice? What would it mean to close that gap — even by one step?
4. Where in your community is the organizing already happening? Worker organizing, tenant organizing, immigrant rights advocacy — this work is likely already underway somewhere near you. What would it mean to show up for it, not as a leader or an expert, but as a neighbor?
5. What would your institution need to examine? If you are part of a church, school, organization, or business, what is one supply chain decision, one technology deployment, or one investment choice that your community has never seriously scrutinized through a lens of labor justice? Who would you need to bring into that conversation?
6. What story are you telling yourself about your own role? The Northern mill owner told himself a story that placed him outside the system he was financing. What story are you telling yourself — and is it true?
This reflection draws on the See · Judge · Act method developed in the Catholic social action tradition, rooted in the work of Cardinal Joseph Cardijn and formalized in papal teaching. The method is used broadly across ecumenical and interfaith justice contexts.