The AI Boom and the Rise of Modern Slavery: Unveiling the Cost Behind the Glitz

Few would argue that artificial intelligence hasn’t transformed our world in remarkable ways. From powering self-driving vehicles to diagnosing diseases with unprecedented accuracy, AI stands at the frontier of innovation. But beneath the glamorous veneer of technological advancement lies a pressing moral dilemma. It’s a predicament that challenges every notion of progress we hold dear: the supply chain fueling AI is riddled with exploitation, echoing historical patterns of forced labor that many believed were left behind. In the Democratic Republic of Congo, laborers in cobalt mines face hazardous working conditions to unearth minerals essential for GPUs. In under-discussed corners of the globe, underpaid content moderators sift through disturbing material to cleanse AI training data. A new digital era is emerging, but at whose expense? Let's shed light on the shadowy edges of this tech revolution, urging each of us to scrutinize the true cost of convenience.

Tech corporations, consumed by the race to perfect the next groundbreaking algorithm, often tout the wonders of cutting-edge research in machine learning. They point to feats like neural networks replicating human cognition or deep learning breakthroughs unraveling complex scientific mysteries. Yet these achievements don’t tell the full story. When researchers tout the virtues of “intelligent automation” and “data-driven optimization,” they rarely mention the unspoken, invisible workforce enabling these breakthroughs. Whether it's the miner in sub-Saharan Africa digging for rare metals or the contractor in Southeast Asia poring over graphic images to sanitize training sets, each plays a role in a global supply chain that remains largely hidden from public view. This asymmetry—where a privileged few reap enormous profits while thousands labor in obscurity—exposes a paradox at the heart of modern technology.

Global watchdogs like Amnesty International and the Global Slavery Index have long flagged these exploitative labor conditions, but they often struggle to capture the public imagination. After all, the conversation around AI is anchored by glossy product launches and enchanting possibilities, not labor abuse. Yet the very real human cost of extracting raw materials for lithium-ion batteries and GPUs is profound. According to the International Labour Organization, around 27.6 million people globally are trapped in conditions of forced labor as of 2022. While not all of these individuals are directly tied to the tech industry, this staggering number underscores how exploitation remains a consistent thread in global supply chains. If we take a closer look at the swirl of dirt and sweat surrounding cobalt mining in Congo, for instance, it’s sobering to learn that more than 60% of the world’s cobalt hails from this region. Many of the laborers there earn far less than a living wage, and some reports reveal the involvement of child workers in extracting minerals that ultimately power smartphones, laptops, and AI-driven supercomputers.

Cobalt is hardly the only raw material fueling modern digital magic. Rare earth metals, including neodymium and dysprosium, underpin advanced electronics and high-performance components. Their extraction, often happening in developing nations, isn’t free of contention. Communities around these mines experience environmental degradation, groundwater pollution, and unsafe working conditions. For tech conglomerates, it becomes convenient to label these issues as “externalities.” But for the families who grapple with contaminated water or the laborers suffering from respiratory illnesses, these consequences are deeply personal. They bear the brunt of a system obsessed with profits and enamored with the next big AI breakthrough, while neglecting the human element that underpins the entire production pipeline.

Beyond the mines, another form of exploitation festers in the digital realm. Large-language models, image recognition systems, and content recommendation algorithms rely on meticulously curated training data. Most of the time, these data sets require labeling, moderation, and cleaning on an immense scale. The underpaid workers who tackle this herculean task often operate in outsourced firms located in regions with lower labor costs. Consider the recent revelations regarding content moderation for social media giants, where employees in Kenya or the Philippines spent hours sifting through violent or disturbing material to keep online platforms user-friendly. Their pay was meager, and the psychological toll significant. Still, the conversation remains overshadowed by the fascination with what AI can do, rather than whose well-being is sacrificed to make it function smoothly.

A Historical Echo: The Architecture of Oppression

To understand this tangled web, it’s worth reflecting on how forced labor has shaped economic systems throughout human history. In the 19th century, cotton from the American South fueled the textile mills of England, generating enormous wealth for industrialists while enslaved people labored under inhumane conditions. Today’s technological supply chain bears haunting similarities. There are different legal frameworks, of course, and a smokescreen of corporate social responsibility statements, but the underlying mechanics remain parallel: wealthy nations and corporations absorb the bulk of the benefits, while marginalized communities are saddled with the worst consequences.

The words “modern slavery” might sound hyperbolic to some readers. But the Anti-Slavery International organization defines modern slavery to include forced labor, debt bondage, human trafficking, and other forms of exploitation. It thrives wherever there is desperation, lack of regulatory oversight, or limited economic opportunities—an environment that is unfortunately plentiful in many of the global regions producing the raw materials and services for AI technologies. Multinational corporations often operate through complex layers of subcontractors, making it difficult to hold any single entity accountable. This labyrinthine structure benefits companies at the top, who can point to the difficulty of auditing every tier of their supply chain. Meanwhile, the cost in human lives and suffering remains an abstract footnote in shareholders’ quarterly reports.

Regrettably, modern slavery continues because it’s profitable. The International Labour Organization estimates that forced labor in the private economy generates $150 billion in illegal profits annually. That figure dwarfs the GDP of many smaller nations. When moral responsibility conflicts with enormous financial incentives, corporations often look the other way, especially if the broader public remains uninformed or indifferent. However, the moral and ethical implications of building AI systems on the backs of exploitative labor—whether in mines or behind computer screens—are profound. Eventually, the veneer of technological progress can’t hide the ugly truth: that we have constructed a digital future on a foundation as precarious as it is unjust.

The Underpaid Army of AI’s Secret Workforce

We see their work in everything from voice recognition systems to spam filters, but we rarely see them. They’re the data annotators who draw boxes around objects in images, transcribe audio files, and label complex textual nuances so that machine-learning models can learn from carefully prepared datasets. According to recent lawsuits, some of these workers have been exposed to horrific and traumatizing material, such as explicit violence or hate content, without adequate psychological support. Their wages, often a fraction of what employees in the U.S. or Europe would earn, reflect a glaring global pay disparity that tech giants are more than willing to exploit to maintain competitive edges in the AI arms race.

A 2019 report revealed that some content moderators in the Philippines were earning as little as $1.50 per hour to screen graphic images and videos. The emotional and psychological cost of this work can be devastating. Companies attempt to mitigate this by offering minimal counseling or rotating workers off particularly graphic tasks, but these measures often prove insufficient. Many content moderators describe lasting mental health issues such as PTSD, anxiety, and insomnia. And for every headline-breaking case, countless similar stories remain untold. This invisible workforce keeps the internet “clean” so that mainstream users never see the gruesome underbelly of the internet, enabling major platforms and AI systems to refine algorithms based on sanitized data.

Meanwhile, in the realm of image recognition and autonomous vehicles, there’s an ever-growing demand for data labeling at scale. Pedestrians, cars, road signs—each image must be meticulously marked. The speed at which these tasks need to be done can border on the inhuman, with workers sometimes required to label thousands of images per shift. Companies tout the wonders of advanced driver-assistance systems, but seldom highlight the sheer volume of labor—and underpaid labor, at that—required to teach these systems how to navigate the real world. As the appetite for AI applications grows, so too does the reliance on cheap labor, often in regions with lax labor laws or high unemployment rates, where a job that pays even a marginal wage can be seen as better than none at all.

There’s also the issue of visa-dependent workers in more developed nations. Tech companies routinely import specialized talent on work visas, placing employees in precarious positions where speaking out about unfair treatment risks job security and immigration status. Even if these workers aren’t subjected to the same conditions as miners or moderators in the global South, the power dynamics are still skewed in favor of the employer. Unions and labor rights organizations have repeatedly raised alarms over these practices, yet tech giants frequently resist unionization efforts, citing concerns about innovation and competitiveness. But behind these corporate responses lies a reluctance to cede any control over a workforce that is critical to maintaining high profit margins and rapid product development cycles.

Tangled Global Networks and Limited Accountability

In a global economy, supply chains are complex and often opaque. A single smartphone or GPU can contain components from over a dozen countries. Tech multinationals rely on suppliers and sub-suppliers scattered across the planet, each with their own labor practices and regulatory environments. To track exploitation, you’d have to follow the chain from the final assembly plant back to smelters, then further upstream to the raw mineral extraction sites. Despite well-publicized corporate pledges and compliance audits, the reality is that these chains are designed for efficiency and cost-cutting, not transparent oversight.

When allegations of forced labor or child labor surface, the most frequent corporate defense is ignorance: “We had no idea that our suppliers were engaging in these practices.” But ignorance is hardly a defense when corporate profitability is intimately tied to cost-minimizing measures. Moreover, voluntary audits often paint a misleading picture. Factories and mining operations can be staged for inspections, temporarily concealing abusive conditions. Workers may be coerced to remain silent about their circumstances. What’s required isn’t a quick fix, but long-term systemic change—stronger legal frameworks, meaningful enforcement mechanisms, and robust union representation. Unfortunately, these solutions often run counter to the free-market ethos that drives Silicon Valley. The tension between profit maximization and ethical labor practices remains difficult to resolve, especially when so much of the public’s attention is captivated by shiny new AI demos, not the structural issues that make them possible.

In fairness, some tech companies have begun acknowledging the problem, pledging to source “conflict-free” minerals or establishing funds for improving working conditions. However, critics argue these efforts are often superficial, serving as public relations campaigns rather than genuine attempts to enact structural reforms. The scale of AI's expansion demands a stronger, more collective effort. For every initiative that tries to do right by workers, there are dozens of other corners where labor violations go unnoticed. The problem isn’t that solutions are nonexistent; it’s that they're rarely profitable in the short term, making them unappealing to shareholders. Until societal and political pressures outweigh the financial perks of exploitative labor, transformative changes may remain elusive.

Who Bears Responsibility?

As consumers, we often play an unwitting role in perpetuating these systems. Each time we upgrade our smartphones or binge-watch the latest AI-curated streaming recommendations, we participate in the very machinery that runs on exploitative labor. Our complicity may not be direct, but it’s real. A liberal viewpoint emphasizes the interconnectedness of our global community and the responsibility we share to uphold human rights. We cannot pretend these injustices exist in a distant, unrelated sphere. When modern technology is so central to our everyday lives, ethical consumption becomes a daunting but necessary objective.

Governments also shoulder a critical share of responsibility. Labor laws, trade regulations, and international accords all shape the landscape in which exploitation can flourish or be curtailed. While nations have historically struggled to coordinate effective global labor standards, new momentum is possible if consumer movements, activist organizations, and conscientious politicians join forces. For instance, the European Union’s trade agreements can introduce stricter transparency requirements, while the U.S. Department of Labor can impose penalties on companies found to be using forced or child labor in their supply chains. And on the domestic level, enforcing living wage legislation and guaranteeing the right to unionize can diminish the exploitation of workers, whether they’re content moderators in Manila or data annotators in Nairobi.

Yet policy alone won’t solve everything. Corporations have shown remarkable agility in navigating legislative loopholes or relocating operations to jurisdictions with weaker labor protections. Effective change requires a combined approach of grassroots advocacy, international cooperation, and courageous leadership from within the tech sector itself. Some activists believe the answer lies in more radical transformation—like an overhaul of the profit-driven model that underpins the global economy. While such proposals often face fierce resistance from business lobbies, they at least recognize that tinkering around the edges might not suffice for a problem so deeply rooted in the structures of global capitalism.

Environmental Costs and Their Human Toll

Modern slavery within AI’s supply chain also intersects with environmental degradation, forming a crisis that disproportionately harms communities in the Global South. Extracting rare earth metals not only exploits labor but ravages local ecosystems. Contaminated soils, polluted rivers, and toxic runoff have direct consequences for the health and livelihoods of nearby populations. These communities are often the same ones that lack strong political representation or resources to demand accountability from multinational corporations.

Meanwhile, climate change introduces yet another layer of vulnerability. As weather patterns become more erratic, rural populations in developing countries often migrate to cities in search of work. In these precarious economic conditions, they become prime targets for exploitation by recruiters looking to staff unsafe mines or factories. The cycle is self-perpetuating: climate-induced desperation feeds labor exploitation, which further enriches industries fueling high-consumption lifestyles that drive environmental harm. Addressing one facet of the crisis—like forced labor—must go hand in hand with addressing environmental sustainability if we want to break this deadly loop.

The Roles of Activism and Journalism

Investigative journalism has often been the most potent weapon against hidden labor abuses. Whether it’s The Guardian exposing child labor in cobalt mines or local African journalists uncovering unscrupulous subcontractors, these stories bring much-needed scrutiny to otherwise invisible corners of the global economy. But even journalism faces significant hurdles: reporters risk threats, harassment, or worse when challenging powerful commercial interests. Media outlets that rely on advertising revenue from big tech companies can face conflicts of interest, potentially limiting the scope or frequency of their investigations.

Nevertheless, recent years have seen a rise in collaborative, cross-border journalism initiatives that pool resources and expertise, aiming to track supply chains from end to end. Such collaborations can create a more complete picture of how exploitation in the mining sector connects to the final product in a Silicon Valley-based startup. As revelations reach wider audiences, consumer consciousness grows, compelling companies to respond—at least superficially—with statements and pledges. Therein lies the delicate dance: it’s relatively easy to secure a public apology or corrective promise, but far harder to guarantee a meaningful transformation in labor practices. Sustained coverage and continuous activist pressure are critical in maintaining momentum.

Grassroots movements also have a powerful role to play, especially in shaping public opinion and lobbying for legislation. From student groups protesting iPhone labor practices to local communities blocking environmentally harmful mining expansions, activism can exert pressures from multiple directions. Even so, activists face resource limitations and can struggle to sustain engagement over the long term. Tech issues might appear abstract, making it challenging to maintain awareness and urgency around problems that feel geographically distant. This is where alliances with labor unions, environmental groups, and human rights organizations can amplify impact, translating local grievances into global action.

Confronting the Cultural Mindset of Instant Gratification

The lightning pace at which AI technologies advance fosters a culture of constant upgrades—new GPUs, faster processors, more capable devices. This perpetuates a cycle in which supply chains are stretched to their limits, always chasing higher profits, and always looking for new ways to cut corners. Many of us have grown accustomed to instant gratification: we want our gadgets delivered overnight, our AI-driven apps to work flawlessly, and our online content curated just for us. This endless appetite pressures companies to prioritize speed and cost-effectiveness over ethical sourcing and labor welfare.

It’s easy to compartmentalize. We rationalize our consumer habits by focusing on the tangible benefits AI provides: better healthcare diagnostics, smart traffic systems, streamlined communications. These are real gains, and they shouldn’t be trivialized. But ignoring the moral implications attached to them is no longer justifiable. In a liberal framework, where solidarity and equitable treatment are core values, unchecked consumerism that systematically exploits vulnerable communities is antithetical to the future we aim to build. If technology is truly meant to uplift humanity, it must do so without sacrificing the well-being of those in precarious economic conditions.

We can talk about corporate social responsibility, yet for every glossy sustainability report, there’s often a mismatch between rhetoric and reality. While some tech executives voice concerns about ethics, the focus remains predominantly on the more palatable topics of algorithmic bias and data privacy, rather than the ugly truth of exploited labor. Shining a light on cobalt mines or underpaid content moderators is less glamorous and risks tarnishing the brand image. But turning away from the problem doesn’t eliminate it. It only perpetuates a vicious cycle.

Shaping a Regulatory Future

The rise of ethical consumerism and socially conscious investment offers a glimmer of hope. If shareholders start demanding responsible practices—like comprehensive labor audits, transparent supply chains, and fair wages—companies may find it less financially viable to continue exploitative models. Legislative bodies can also tip the scales by instituting stricter requirements, such as mandating corporate disclosures on labor practices or penalizing companies that fail to meet baseline ethical standards. A well-crafted policy regime could coordinate global efforts, making it harder for corporations to simply relocate exploitative operations to more permissive jurisdictions.

However, such legislative frameworks must be robust enough to address the complexities of a transnational supply chain. One challenge is the reality of different legal systems with inconsistent or nonexistent protections for workers. A patchwork of laws allows corporations to play jurisdictions against one another. Standardizing regulations through international treaties or trade agreements could close some of these loopholes. But progress on that front has historically been slow and fraught with competing national interests.

Another avenue is consumer-driven boycotts or endorsement of products certified as ethically sourced. While some might be skeptical that consumer actions alone can dismantle a billion-dollar industry’s entrenched exploitation, public awareness has spurred transformations in other sectors. For instance, “fair trade” certifications in the coffee and chocolate industries didn’t solve all problems, but they did create pockets of more equitable labor relationships. A similar push in the tech sector—aiming for “fair-mined cobalt” or “ethically produced GPUs”—could be a step forward, even if it’s partial. The challenge is forging a certification process that can’t be easily manipulated. Transparency and accountability, again, remain central.

Educational Imperatives

It’s not enough for policymakers and corporate boards to engage in high-level dialogues. Education about the human cost of AI must reach universities, where tomorrow’s engineers, data scientists, and entrepreneurs are molded. A comprehensive understanding of supply chain ethics should be integrated into the curricula of technical fields. Future tech leaders should grapple with the moral ramifications of their work, not just the code they write or the models they train. If we encourage a generation of socially conscious technologists, we might see more startups adopting fair labor practices as a core principle, rather than as a grudging afterthought.

This approach could be bolstered by cross-disciplinary collaborations—combining data science with social sciences, business management with human rights studies. Students in these programs would encounter real stories of exploitation, forcing them to confront the discrepancy between AI’s promise and its moral pitfalls. As they emerge into the workforce, this broader perspective can inform both technical decisions and corporate strategies. Change will not be immediate, but embedding ethics into the DNA of innovation can foster a generation less tolerant of exploitation.

The Intersection of AI and Global Justice

We often talk about AI as a powerful tool for addressing social problems—predicting climate patterns, diagnosing diseases, optimizing resource distribution. These aspirations are valid. But if the backbone of AI development is tainted by unethical labor practices, can we claim real progress? The contradiction is stark: on one hand, we herald AI’s potential to create a fairer, more equitable world. On the other, we ignore the injustices at the core of its supply chain.

A liberal viewpoint urges us to scrutinize the entire ecosystem in which AI operates. It’s not merely about achieving the next technological milestone, but about ensuring that the journey there is just and humane. If we fail to hold companies accountable, if we continue to prize short-term gains over long-term social welfare, the dream of AI as a democratizing force will ring hollow. We risk repeating the same cycles of exploitation that have marred human progress for centuries, only now under the sophisticated guise of algorithms and machine learning.

Toward a More Just Tech Future

The fight against modern slavery in AI’s supply chain requires collective moral clarity and tangible policy changes. When we discuss the ethics of AI, we must move beyond the standard talking points of data bias and privacy to include labor conditions and economic justice. This starts with acknowledging that every shining gadget, every advanced algorithm, may carry within it the weight of human struggle. Closing our eyes to that burden does not absolve us from responsibility. Rather, it deepens our complicity.

Organizations committed to fair labor practices are already showing that a more just model is possible. Some companies are beginning to invest in local communities to ensure educational opportunities and safer working conditions for miners. Others are restructuring contracts with content moderators, offering mental health support and improved wages. These are promising steps, but they remain sporadic and relatively small in scale. The question is whether these initial efforts can catalyze a broader movement that realigns the tech world’s priorities.

Legislators, journalists, activists, tech professionals, and everyday consumers all have roles to play. Each can bring distinct pressure to bear—through advocacy, through ethical purchases, through reformed legislation, and through conscientious innovation. This is not an easy fight. The financial interests protecting exploitative structures are enormous. Yet, the moral stakes are too high to dismiss. We stand at a crossroads where the promise of AI can either be realized through oppression or championed with respect for human dignity.

The next wave of AI advancements—quantum computing, advanced robotics, generative models—will demand even more resources, both material and human. If we don’t address the systemic labor abuses now, the exploitation will likely intensify. Alternatively, if we seize this moment to implement reforms, we might steer AI’s trajectory toward a genuinely equitable future. This is not about stifling innovation; it’s about aligning progress with the values of human rights and social justice. Only then can we truly celebrate AI’s capacity to uplift lives around the globe.

Elevating Human Rights in Our Digital Priorities

One of the most persistent obstacles to combating modern slavery is the public’s limited awareness and the tech sector’s own reluctance to highlight uncomfortable realities. Public figures who do speak out risk accusations of undermining progress or stifling innovation. But the point isn’t to halt AI development; it’s to develop AI responsibly. Without a major shift in mindset—one that treats human rights as non-negotiable—exploitation will continue to lurk behind every milestone, every new application, and every device that lands on store shelves.

A liberal perspective insists on the indivisibility of rights. The right to not be forced into exploitative labor is as fundamental as the right to privacy or freedom from discrimination—yet it garners far less media attention in the AI discourse. We can talk about the wonders of smart assistants and autonomous vehicles, but we must also talk about ensuring that no child is forced to wield a shovel in a toxic cobalt mine to keep production costs down. We must make certain that no vulnerable individual is exploited in a data-labeling sweatshop so we can indulge in more targeted ads or more streamlined user experiences.

A transformation in values is challenging but not impossible. Social attitudes toward fair trade, ethical sourcing, and sustainable consumerism have shifted in other industries. The emergence of “green tech” is evidence that a portion of the market seeks products aligned with environmental stewardship. Why not also “fair tech,” where consumers demand and corporations strive for ethically sourced raw materials and equitable labor practices? The more we ask questions, the less comfortable companies will be operating behind veils of ignorance.

Global Cooperation for Systemic Change

Supply chain abuses in the AI sector reflect deeper structural issues in the global economy. While some might hope that technology itself will provide a magic fix—like blockchain-based tracking of minerals—tools alone can’t solve a crisis fueled by human greed and power imbalances. Systemic change requires cooperation among governments, institutions, and civil society. New international treaties or expansions of existing agreements, like the UN Protocol to Prevent, Suppress and Punish Trafficking in Persons, could be adapted to address the unique challenges of labor in high-tech supply chains.

Simultaneously, the Global North must reconcile its economic privilege with the fact that it often outsources the most harmful elements of production. Policies that incorporate the true cost of labor and environmental impact might be labeled “anti-competitive” by some, but they’re essential for rectifying longstanding injustices. The exploitation fueling AI’s supply chain thrives in environments where there is a race to the bottom, with each supplier competing to provide the lowest labor cost. By establishing global minimum standards and penalties, the race can shift toward better working conditions and ethical transparency.

Cynics might argue that meaningful global enforcement is unrealistic. Yet, consider the strides made against other forms of exploitative labor over time. Although far from perfect, international consensus has been reached on issues like child labor in certain contexts, spurred by powerful advocacy and legislative actions. When the moral imperative is clear, change can happen—if the public’s will and political courage align. Ending the modern slavery behind AI isn’t a pipe dream; it’s a moral responsibility whose fulfillment is possible if we collectively demand it.

What Lies Ahead

As AI further integrates into healthcare, education, finance, and governance, the stakes for getting its foundations right grow ever higher. The fight against modern slavery within tech’s supply chains mirrors broader societal struggles for equality, justice, and dignity. Overcoming these challenges means dispelling the convenient myth that technology is inherently neutral. Algorithms may be neutral in a strict technical sense, but the systems that produce them are steeped in human choices—choices that can either exploit or empower.

In an era marked by intense polarization, forging unity around the imperative to protect human rights might seem daunting. Yet, ensuring fair labor practices is an issue that transcends partisan divides. Regardless of one’s ideological leanings, few would openly defend forced labor or dangerous working conditions. From a liberal vantage point, the emphasis remains on addressing systemic inequalities and prioritizing the well-being of marginalized communities. But people across the political spectrum can rally around the fundamental idea that no technological advancement is worth more than a human life. If we can hold on to that shared value, we can build momentum to enact and enforce meaningful reforms.

The AI revolution will shape our collective future in ways we have yet to fully imagine. It offers incredible possibilities—optimizing healthcare, mitigating climate impacts, revolutionizing education—yet these benefits become hollow if they’re built on an undercurrent of exploited labor. The urgent question is whether we’re willing to look beyond the glitz, hold ourselves and our institutions accountable, and commit to forging a more equitable path forward. Turning away from the hidden foundations of modern slavery in AI might be convenient, but it ultimately undermines our pursuit of true progress.

Raising awareness is just the beginning. Real progress hinges on action—legislative, corporate, and personal. Each smartphone we buy, each data set we create or manage, each product we endorse, reflects a choice. Will we continue to pay lip service to human rights while turning a blind eye to the exploitation sustaining our favorite tech products? Or can we harness the tools of this modern age—social media, digital activism, and global connectivity—to demand accountability from the very forces that shaped these technologies in the first place?

The time has come to recognize that efficiency and progress must not be pursued at any price. It’s within our grasp to insist that AI, a technology that holds the power to transform medicine, education, and governance, doesn’t rest on the suffering of the vulnerable. Forced labor and the systematic underpayment of essential contributors to AI’s pipeline must be addressed with the same urgency that we reserve for other ethical challenges in the tech world.

Change is never easy, and entrenched interests won’t simply melt away. But every movement in history—from the abolition of slavery to the push for labor rights in the industrial era—has faced seemingly insurmountable barriers. If we truly believe AI can enhance the human condition, then we have a responsibility to ensure it does so for everyone involved, not just the privileged few. Through relentless advocacy, informed consumer choices, and political engagement, we can pivot this powerful technology toward a path that values every human life it touches.

Let’s channel our collective voices to demand ethical supply chains, equitable labor practices, and transparency from every company that profits from AI. Refuse to accept a future where digital wonders are built upon invisible suffering. Urge tech giants, policymakers, and fellow citizens to stand firm against modern slavery and economic injustice. By recognizing that our actions have the power to shape an AI landscape grounded in respect for human rights, we commit ourselves to a vision of true progress—one in which technological innovation and social justice finally align.