Waiting for Robots exposes the hidden human labor that powers AI and digital platforms, challenging the widespread myth that automation is purely machine-driven. While companies often present images of intelligent systems and seamless algorithms, the reality is that digital technologies still rely on the work of millions, often underpaid, invisible, and operating under precarious conditions. The book is organized into three parts, each offering a critical lens on the digital economy. The first part, Understanding Automation, unpacks the political, economic, and cultural foundations of automation, showing how AI is inseparable from platform capitalism and broader social forces. The second part, Types of Digital Labor, maps the many forms this labor takes, from gig work to microwork and social media participation, examining how these roles are structured and who performs them. The third part, Rethinking Labor and Resistance, explores the political implications of digital labor and offers new ways to support and organize workers, from unions and cooperatives to alternative models of data governance and collective action. These three parts critique the inequalities shaping the digital economy and argue that digital labor is real labor, demanding recognition, protection, and empowerment for those who make today’s technologies possible.

Part 1: What Automation?

Will Humans Replace Robots?

This section challenges the idea that robots and AI will take over all human jobs. While machines seem smart, they can only do what humans teach them. They do not truly understand what they are doing. In fact, behind most AI tools are real people doing small, often hidden jobs, like labeling data or checking results. So, machines are not replacing humans; instead, human labor is being broken into smaller parts and made less visible. There is a debate: some believe automation means machines are doing everything now, but others say that is misleading; people are still doing the hard work behind the scenes. These hidden workers are often underpaid or unpaid, working from home or in low-income countries.
Instead of jobs disappearing, work is changing. Tasks are split up and spread across people through platforms. Sometimes, companies even shift the work to users, like self-checkouts or online forms, called consumer labor. It is real work, just not recognized or paid like traditional jobs. The idea that robots will replace humans is not new but is often overblown. Studies show that most jobs will not vanish, though parts of them might change. Automation tends to shift tasks, not erase them entirely. Even creative jobs are not safe from being reshaped by technology. What is happening is a shift from stable jobs to fragmented, invisible tasks, called digital labor. This includes gig work, micro-jobs, unpaid online activity, and user-generated content. It's work that helps platforms run, but without the protections of a normal job.
Ultimately, the idea of full automation is more of a myth. Big tech companies rely on people to keep things working, but hide this labor to cut costs and increase control. Automation is less about replacing workers and more about reshaping work to benefit platforms while keeping the workers in the background.

What's in a Digital Platform?

Digital platforms like Uber, Amazon, YouTube, and Google have reshaped how we work, interact, and create value. These systems connect different user groups, such as workers, customers, and advertisers, using algorithms and vast amounts of personal data. Unlike traditional companies that produce goods or offer services directly, platforms act as intermediaries that profit from users' interactions, contributions, and behaviors. Everyday actions like posting content, giving ratings, or even just browsing generate value for these companies, often without users being paid or even aware of their role in this process.
While platforms are often presented as neutral, efficient, and open systems, they are carefully designed to concentrate power and profit. They hide labor behind automation, reduce costs by outsourcing tasks to users, and shape digital spaces through algorithms that serve corporate goals. This model relies on a process called taskification, breaking work into small, simple tasks distributed to a flexible crowd and blurring the lines between workers, consumers, and data sources. As a result, users often perform invisible labor, with little recognition or compensation, while platform owners capture the bulk of the value.
This way of organizing work and value has spread far beyond tech companies. Traditional industries, from transport and energy to media and even government services, adopt platform-like models. These systems rely on user participation, data collection, and flexible labor to reduce costs and increase efficiency. But in doing so, they often undermine job stability, shift responsibility onto individuals, and make social systems more dependent on private digital infrastructure.
In short, platforms are not just tools or businesses; they represent a powerful shift in how economic and social life is organized. To understand and respond to this shift, we must pay attention to the invisible labor, data extraction, and political structures that make platforms work. They are built on people, their time, their knowledge, their clicks, and yet those people are rarely in control of the systems they sustain.

Part 2: Three Types of Digital Labor

On-Demand Digital Labor

On-demand platform work, like food delivery, ride-hailing, or cleaning, is often advertised as flexible and modern. However, many of these jobs come with low pay, no job security, and little legal protection. While workers are labeled as "independent contractors", they often don't have the freedom or benefits that the title suggests. The number of platform workers has grown rapidly, especially during the pandemic, but this hasn't led to better wages or conditions. In fact, many workers struggle with unstable hours and must cover their own costs, like fuel or vehicle repairs. Legal debates continue around whether these workers should be classified as employees to gain rights like sick leave, minimum wage, and pensions.
Platforms also collect and use massive amounts of personal data from both workers and users. This includes location tracking, performance data, and even names and photos, which can lead to biased treatment or discrimination. Workers are often under pressure to maintain high ratings and "professional" behavior while also doing unpaid work like waiting for tasks or managing apps. Users, too, are part of this system; their clicks and ratings help platforms decide prices, match services, and collect more data. Even customers are expected to behave in ways that keep the system running smoothly, doing emotional labor to keep good ratings.
Finally, even in highly automated services like self-driving cars, human labor is still essential. Passengers often do unpaid work like monitoring the car or handling unexpected problems. Behind the scenes, thousands of low-paid workers label images and data to train AI systems. Despite the image of a high-tech, self-running future, these platforms still depend heavily on hidden human labor, both online and offline, to function. In the end, what looks like innovation often builds on old problems: insecure jobs, invisible work, and power in the hands of a few companies.

Microwork

Amazon Mechanical Turk (MTurk) is a platform where people worldwide do small digital tasks like tagging images or checking text to help train AI systems. These workers, called "Turkers", are often paid very little, even though many of them are well-educated and rely on this work as their main source of income. Tasks may seem simple, but they require focus and digital skills. Despite being called "independent contractors", Turkers lack job security, benefits, and clear protections. Women, especially those with children, tend to earn even less, and workers risk being penalized if they work too fast or don't meet unclear standards.
MTurk and similar platforms try to make the work seem fun or casual by using games, badges, and rankings, a strategy called gamification. However, in reality, it's competitive and stressful. Workers must spend unpaid time qualifying for better tasks, hunting for work, and maintaining high ratings. If the requester rejects a task, workers don't get paid, and their scores may drop. Amazon profits quietly in the background by taking a cut from every task and collecting data from both workers and clients, while avoiding responsibility as an employer.
This type of microwork is now used across many tech companies like Google and Microsoft, which rely on hidden human labor to improve their AI. Even when AI seems automated, humans are behind the scenes checking results, labeling data, and fixing mistakes. Often, these workers are underpaid, invisible, and disconnected from each other, making it hard to organize for better treatment. In some cases, experienced freelancers break up their large contracts into smaller pieces and pass them to other workers for less pay, creating layers of hidden labor within freelance platforms, too.
Microwork has also become a global phenomenon, with workers in poorer countries doing tasks for companies in wealthier ones. This "one-click offshoring" mirrors old patterns of outsourcing but on a faster, more digital scale. Sometimes users aren't even paid at all, like when people use Google tools or solve reCAPTCHAs, they're unknowingly helping train AI for free. Whether paid or unpaid, this human labor powers AI systems around the world, but workers often remain unrecognized, underpaid, and excluded from the benefits of the technology they help build.

Social Media Labor

Many people don't think of using social media as work, but it actually is. Even when users just post, like, or comment, they're helping platforms like Facebook, Instagram, and YouTube grow and make money. While influencers or content creators are sometimes paid, most users are not. Still, their actions generate valuable data and content for the platform. This unpaid effort is often called "free digital labor", and although it feels casual or fun, it's a hidden kind of work that keeps the digital economy running.
Platforms benefit from this by turning users into both creators and consumers, sometimes called "produsers". They blur the line between play and labor, encouraging people to share content while hiding how much value that activity creates. Platforms also avoid calling this work and instead reward users with likes, visibility, or symbolic badges. A few creators may earn money, but most are unpaid and face constant pressure to stay active, especially young or low-income users hoping to turn their content into a job, a trend known as "hope labor".
Behind the scenes, other workers, like content moderators, click-farmers, and microworkers, are paid small amounts to label images, train AI, or keep platforms "safe". This labor is often done in poorer countries, and while it's essential to how platforms function, it's underpaid and invisible. Even unpaid users contribute to this system by tagging posts, flagging content, or interacting in ways that train algorithms. Whether done for fun or money, all of this activity feeds into the platform's profit model.
In the end, social media platforms rely on a mix of unpaid user labor, low-paid microtasks, and data collection to make money. They present themselves as free and fun, but they are powered by human effort, much hidden, underpaid, or completely unrecognized. The line between work and play has become increasingly blurred, and understanding this is key to seeing how the digital world really operates.

Part 3: The Horizons of Digital Labor

Work Outside Work

Digital platforms rely on all kinds of hidden labor that often isn't recognized as real work. Whether it's people leaving reviews, tagging photos, helping train AI, or moderating content, many users are doing valuable tasks without pay. Platforms blur the line between work and play, calling users "consumers" or "creators" instead of workers, even though their actions help platforms grow and make money. This kind of unpaid or underpaid labor includes everything from social media activity to gig work, and it often goes unnoticed.
Some of this labor involves emotional care, like chatting with followers, managing online communities, or organizing video calls. Platforms also use gamification, e.g., points, badges, and rankings, to make work feel fun, encouraging people to keep engaging without realizing they're working. This is called "playbor", a mix of play and labor. Because it's spread throughout the day and tied to entertainment or social life, people end up working constantly, even when they think they're just relaxing online.
Even though this work happens online, it's not "immaterial". It takes real time, focus, and energy and often includes repetitive or stressful tasks like moderating harmful content or fixing software issues. Much of this labor is hidden, what some call "ghost work", and it's essential to how platforms function. People all over the world are involved, but the work is often isolated, poorly paid, and invisible.
Finally, hyperemployment describes how people today are often overworked without realizing it. Digital tools like email, messaging apps, and gig platforms make it easy for work to spill into every part of life: during dinner, late at night, or on weekends. Whether you're a gig worker or a salaried employee, digital labor is creeping into your daily life in ways that feel normal but are slowly taking up more time, often without any extra pay or recognition.

How Do We Classify Digital Labor?

Digital labor means people doing real work through online platforms, like driving, tagging images, posting content, or moderating, often without being recognized or fairly paid. Platforms like Uber, Amazon MTurk, and Upwork avoid hiring people as employees. Instead, they call them freelancers or "partners", so they don't have to provide benefits, job security, or proper wages. Workers are managed by apps and algorithms, which assign tasks, track performance, and decide who gets more work. This makes people feel like they're free and independent, but in reality, they're closely controlled.
While some people choose this work for flexibility, many do it because they have no other choice. Most gig and microworkers face low pay, no job security, and little control over their work. Even skilled workers, like software developers, are starting to face the same problems. Platforms promise opportunity and freedom but often deliver stress, unfair rules, and unstable income. The system favors the platforms, which make money while shifting all the risk onto workers.
Many of these jobs repeat old-fashioned and unfair labor systems, like piecework and informal home-based work. Workers are paid only for specific tasks, not for the time spent waiting, learning, or fixing mistakes. The platforms also trap workers by keeping their ratings and work histories locked inside, making it hard to move to better jobs. Meanwhile, everything they do, from driving to posting to even using social media, is tracked and turned into data. That data is used to train AI or sold to advertisers, bringing in more profits for the platforms, not the workers.
In the end, digital labor is real work, even if it's unpaid or disguised as fun. It takes time, energy, and skill, but platforms often treat it as voluntary or informal. They avoid responsibility by using one-sided rules and calling workers "users" or "creators" instead of employees. This creates a system where people are constantly working while being underpaid, closely watched, and denied the protections they deserve. The digital economy may look modern and free, but for many, it feels more like exploitation in disguise.

Subjectivity at Work, Globalization, and Automation

Digital labor often looks flexible or fun, but it hides a system of deep exploitation. Platforms like Uber, Facebook, or Amazon MTurk depend on millions of people doing small, often invisible tasks without fair pay or recognition. This work is split into tiny parts, isolating workers and making it hard to organize. People doing this work may not even realize they are workers since platforms call it "participation" or "sharing" instead of labor. Meanwhile, a small group of tech elites and companies gain most of the benefits and control the systems.
Many digital workers are alienated from their work. They feel disconnected from the tasks they do, the outcomes of their work, their communities, and even their personal lives. Some may feel empowered by likes or social attention, but that sense of meaning often hides how platforms profit from their activity. While tech culture promises independence and opportunity, in reality, most people face low pay, long hours, and no job security.
Behind the promise of automation and AI lies a workforce that keeps it all running. These systems still need real people to label data, monitor content, and do repetitive tasks. This creates a kind of "digital colonialism", where workers from the Global South help power technologies built and owned by companies in wealthier countries. Even platforms' dream of full automation relies on constant human input. Without millions of people feeding it data, AI simply doesn't work.
In the end, digital labor is essential but undervalued and hidden. Workers provide the data, attention, and judgment that platforms need to grow, yet they remain invisible in the system. Full automation remains a myth, and digital work keeps expanding. However, because it's fragmented and disguised as entertainment, self-expression, or gig work, it's hard for workers to unite or demand better conditions. Until we recognize digital labor as real work, the people behind the screen will keep powering the tech economy without the rights or respect they deserve.

Conclusion: What Is to Be Done?

Digital labor is real work, even if it's invisible, unpaid, or disguised as fun. Millions of people help power platforms like Uber, YouTube, and Facebook by tagging data, moderating content, or doing gig jobs. This work is often fragmented, low-paid, and lacks protections. To fix this, we need to recognize digital workers as real workers and give them rights, benefits, and better treatment. Some progress has been made, especially for drivers and delivery workers, but remote data workers and those in low-income countries are still left out.
One solution is to rethink platforms altogether. Instead of being controlled by tech giants, platforms could be owned and managed by the people who use and work on them, a model called platform cooperativism. Some cooperatives already exist, like courier-owned delivery apps or ethical stock photo platforms. These efforts are small but show that it's possible to build platforms focused on fairness and community rather than profit.
Another idea is to treat data as a shared resource. Everyone who helps create data, by clicking, posting, or labeling, should have a say in how it's used. We could create systems where people collectively manage their digital work and data, with legal protections, shared benefits, and public uses (like cities using ride-share data to improve traffic). Instead of giving users tiny payments for their data, this model focuses on long-term rights and collective ownership.
A bigger vision includes a universal digital income. This would be a regular payment for everyone, funded by taxing platforms and tech companies for the value created by users' digital labor. It wouldn't replace welfare but would fairly redistribute the profits from our online contributions. In short, the future of digital work shouldn't be based on exploitation. With bold ideas and collective action, we can build a more just and people-centered digital economy.