Book Review - Code Dependent: Living In The Shadow Of AI

Ganesh Sreeramulu
Jun 16
2 min read

They say one good turn deserves another. Well, the same applies to books. Fresh off reading The Economy of Algorithms, I kept the momentum alive by picking up Code Dependent.

If I had to summarize it in one line — this book is less about AI’s technological might and more about its human consequences. The author weaves together personal stories to explore how AI, when deployed without guardrails, impacts lives in ways often invisible to those affected.

Opaqueness — The Black Box Problem

A core challenge with these shiny, modern AI systems is their inherent opaqueness. Models connect dots, infer patterns, and make decisions — but even their creators often struggle to fully explain how. The people impacted? Many don’t even realize their lives are being nudged, shaped, or outright altered by algorithmic judgments.

The Ethical Dilemmas Behind the Data

We all know the cliché: "Data is the new oil." But raw data doesn’t fuel AI directly — it needs to be curated, labeled, and refined (Data ETL anyone ? ) . Enter the global data-labeling workforce — thousands labeling images, categorizing videos, moderating content — often sold as glamorous AI jobs, but in reality, highly repetitive work farmed out to economically struggling regions.

Is it exploitation? Or opportunity? For many, these jobs provide a path out of poverty — paying for education, housing, and a better future. It’s not a simple narrative — hence, the ethical dilemma.

Governance — The Rules Can’t Keep Up

Governing these technologies isn’t just about eliminating bias in datasets. It’s about who bears responsibility for outcomes. Deepfakes aren’t accidental byproducts; they’re deliberate tools used to cause harm. And the effects aren’t limited to cyberspace — real lives get scarred. Yet regulations and oversight struggle to keep pace with the speed of innovation.

Your Identity Under Constant Scrutiny

With AI’s reach expanding, every movement, choice, and association can be tracked. From oppressive regimes monitoring dissenters to flawed facial recognition systems tagging innocent individuals — even a 1% error rate, applied at scale, can be catastrophic. And unsurprisingly, underrepresented communities often bear the brunt of these inaccuracies.

The Duality of AI’s Impact

But it’s not all dystopian. The same image recognition systems, even if imperfect, can revolutionize healthcare — like early TB detection in rural India, where patients can’t afford to lose a day’s wage traveling for medical checks. The same technology that risks harm can also deliver life-changing benefits — and therein lies the dilemma.

Scaling the Slippery Slope

Yet, as these systems evolve, so do their complexities. AI-powered healthcare tools may become premium services in metro hospitals; predictive policing starts resembling Minority Report, judging not just people but their networks. And with each intervention, the system feeds itself more data — reinforcing biases and creating self-fulfilling prophecies.

The Crossroads: Digital Welfare or Surveillance State?

At the heart of it all lies the bigger question: Is this grand march of datafication and AI leading us toward a digital welfare state that uplifts? Or toward a surveillance apparatus that controls? The answers remain tangled — and Code Dependent does a brilliant job of making you sit with the discomfort (an uncomfortable discomfort, if I may add).