Automating Her Own Job: An Ethics Case Study in Workplace Automation

June 05, 20258 min read

This is Part 1 of a two-part series examining the ethical complexities of workplace automation. Read Part 2: Solutions and Modern Implications for implementation guidance and contemporary relevance.

Introduction: The Automation Ethics Dilemma

Imagine this: you land a new job. The pay is decent, the hours are steady, and the work… well, it’s the kind of repetitive grind you could do in your sleep. At first, you accept it. After all, stability counts for something. But as the weeks go by, you start wondering, Couldn’t a computer do this for me?

Now imagine you not only figure out how to automate it, you do it so well that a month’s worth of work gets done in minutes. No one notices. You even add a few fake mistakes so it still looks like a human is behind it all.

This is not a complete hypothetical. It's probably happening at your workplace. Let’s call the hypothetical person at the center of this Eve. She found herself walking a tightrope between innovation and deception, between personal freedom and professional trust. This is her story, but it’s also about something bigger: the ethical fault lines that are starting to open up in the age of AI and workplace automation. Fault lines you might find yourself standing on one day.

The Hidden Code Behind the Day Job

Let's set the scene. Eve’s job was in data entry for a mid-sized financial services company. Her days were filled with processing transaction files from banks, cleaning up messy data formats, updating an aging database, generating reports, and answering questions from other departments. Eight hours a day. Five days a week. Over and over.

Six months in, the monotony got to her. She knew it could be automated, not with a simple spreadsheet macro, but with real, industrial-strength code. So she built it. Her system could parse CSV, XML, and JSON files, detect and fix inconsistencies, validate against complex business rules, and even leave behind a perfectly believable audit trail. It handled bulk SQL updates, managed rollbacks, and kept the database squeaky clean.

And then came the clever part. It pretended to be human. Random pauses. Occasional typos. Processing speeds that looked slow enough to be believable. She even inserted realistic “human errors” so her work wouldn’t look too perfect.

The result? Eve’s workday went from hours to minutes. And nobody knew.

The Ethical Crossroads

On paper, Eve did what the job asked, the work got done. In practice, she rewrote the rules of the game without telling anyone. That gap, between what looks like work and what actually happened, is where the ethical tension lives.

Put yourself in her chair for a minute. You have just built something that turns eight hours into eight minutes. What do you do next? Do you hand the code to your manager and watch them turn it into a corporate standard, possibly making your role redundant, or do you keep it private, quietly reclaiming hours of your life while the company continues to pay you for eight-hour days? Neither choice is purely technical and both are loaded with consequences.

There are immediate, human scale dilemmas. If Eve confesses, she might be praised and promoted for innovation, or she might be sidelined and regarded as a threat because her solution exposes how brittle legacy processes were. If she stays silent, she wins spare time and perhaps a better quality of life, but she also assumes the risk of discovery: termination, damaged reputation, even legal or contractual trouble depending on what her employment agreement says.

There is a social angle as well. When one person quietly pockets the gains from automation, coworkers feel it even if they do not know the cause. Fewer visible tasks can mean fewer opportunities for others to demonstrate competence, fewer chances for collaborative problem solving, and an erosion of shared purpose. Concealment breeds suspicion. Colleagues who notice discrepancies may mistrust each other, morale can dip, and the culture of cooperation that organizations prize begins to fray. Over time, if private automation becomes common, you get a patchwork of shadow systems, brittle, inconsistent, and impossible for leadership to govern.

Power and value also get redistributed in ways that matter. Who captures the upside of automation? If companies automatically claim ownership of anything built on company time or infrastructure, employees who innovate face an incentive problem: disclose and possibly lose the source of their advantage, or hide and risk serious fallout if discovered. This tension fuels a quiet black market of workplace ingenuity, a shadow automation economy where value is privatized and innovation is not shared for fear of being exploited or penalized.

At a systems level, these individual choices have regulatory and market consequences. Regulators and auditors operate on trust and traceability. If automation undermines traceability, organizations may find themselves exposed in ways that invite stricter oversight. Markets, in turn, respond to perceived risks. If an industry is seen as opaque or ungovernable, capital and talent may flow elsewhere. Conversely, companies that proactively design transparent automation policies can gain trust, attract talent, and turn potential disruptions into competitive advantage.

So the crossroads is not a single decision but a network of dominoes. Honesty or concealment, individual benefit or collective gain, innovation or instability. Each path creates a different landscape for careers, corporate cultures, and the public systems that govern work. And the hardest question of all is the most personal: If you had built Eve’s script, what would you value more, preserving your job, reclaiming your time, or reshaping the system so everyone benefits?

That question is exactly the one organizations and societies are going to have to answer together, because Eve’s choice is no longer a rare moral curiosity. It is a template for the future of work.

Why this isn’t just about one programmer

It’s tempting to see this as a quirky one-off story about a clever developer gaming the system. But the reality is more unsettling. With AI and automation tools becoming more accessible, Eve’s scenario could easily become common. Companies are scrambling to modernize their systems. Employees are increasingly tech-savvy and capable of building their own tools. And the rules about what you should share, keep, or monetize yourself? They’re still fuzzy.

Eve’s case is a microcosm of a bigger challenge. How do we create workplace cultures where innovation is encouraged, transparency is valued, and both sides, employee and employer, benefit from the gains automation brings?

Every player in Eve’s story has skin in the game. Eve herself gained freedom, skill development, and a portfolio-worthy project. But she also carried the constant stress of being found out. Her employer kept business running smoothly but missed out on a scalable process improvement that could have saved time and money across the company. The QA team kept checking “her” work, but some of that work was busywork, caused by Eve’s intentionally inserted mistakes.

Zoom out further and you see impacts on the wider workforce (what happens when this becomes the norm?), customers (are their records being handled ethically?), and society at large (who should benefit from efficiency gains?).

So… What should have happened?

There’s no magic formula for handling a situation like Eve’s, but there are roadmaps that companies and individuals could follow to avoid letting innovation turn into a silent cold war between worker and employer. Think of these not as rigid rules, but as possible pathways, each with trade-offs worth wrestling with:

Gradual automation disclosure – Imagine a scenario where Eve introduced her tool in small increments, letting her team adapt and her boss see improvements over time. This avoids the sudden shock of full automation while still moving toward greater efficiency. It’s slower, but it preserves relationships and buys everyone time to adjust.
Cross-functional automation teams – Instead of tech decisions being made in isolation, what if automation projects were guided by mixed groups: engineers, operations managers, and the very people whose work would be automated? This creates shared ownership of change, making it less about “machines replacing people” and more about “machines working with people.”
Skill development programs – In a world where repetitive tasks are disappearing, the most resilient workers are those who can evolve. Forward-looking companies could invest in retraining their employees for higher-value roles, instead of treating automation as a one-way ticket to downsizing.
Value-based contracts – What if pay wasn’t tied to hours in a chair, but to the measurable value a person delivers? This could reward innovation like Eve’s breakthrough, but also opens a Pandora’s box about fairness, competition, and what “value” really means in different jobs.
Open-source innovation – By sharing non-proprietary parts of automation tools, companies can raise the bar for entire industries, spreading the benefits of efficiency. But this also risks giving away competitive advantage and not every leader is ready to take that leap.

None of these paths are perfect. But each forces us to confront the same central question: is automation a threat or an opportunity? Who gets to decide?

Closing Thoughts

Eve’s tale isn’t just a workplace anecdote. It’s a preview of a world we’re already stepping into. A world where the tools we can build for ourselves might outpace the rules we have for using them. The real challenge isn’t whether automation can replace human effort. It’s whether we can build a culture, a set of policies, and a shared understanding that ensures the benefits are fair, transparent, and human-centered.

Because one day, you might find yourself in Eve’s position, staring at a screen, your work done before your coffee’s gone cold, wondering if it’s time to tell someone what you’ve built… or keep the secret a little longer.

The most successful approaches will be those that address all stakeholder concerns while maintaining professional integrity and creating sustainable pathways for technological advancement.

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