Book Review - The Economy of Algorithms : AI and the Rise of the Digital Minions
- Ganesh Sreeramulu
- May 24
- 3 min read
Updated: Jun 15
Lately, I’ve been hoarding books on AI & Data like they’re going out of style. Enter The Economy of Algorithms. The title alone whisked me back to Weapons of Math Destruction—a classic that throws shade on algorithms gone wild, wreaking havoc at scale (Quick plug - you can find my review here ).
Algorithms—A Quick History Byte
Fun fact: “Algorithm” traces its roots back to Muhammad ibn Musa al-Khwarizmi, the 9th-century Persian math whiz. His Latinized name, Algoritmi, morphed into the word we use today—denoting step-by-step problem-solving techniques. So, yeah, we owe our digital overlords to a guy from Baghdad.
Algorithms on the Loose: Who’s to Blame?
The book kicks off with a punch—yes, that F-word—and dives headfirst into tales of algorithms tormenting students. But wait—are these algorithms inherently evil? Suffering from model drift? Or is it just us humans being lazy, handing over too much control to machines?
Maybe it’s not the algorithms, it’s us—treating them as magical problem solvers instead of the tools they really are.
And speaking of heavy reads, the author tips the hat to The Black Swan. (Note to self: finish that book. I haven't found it in me to finish that book yet)
Rise of the Digital Minions
If algorithms were mere scripts, life would be easy. But they’ve evolved—opaque, unpredictable, and sometimes downright chaotic. They thrive in the economy of corporations, sniffing out inefficiencies and slashing costs like digital bloodhounds.
Case in point: someone asked ChatGPT how to improve sumo wrestling. The answer? Hand out gloves to the audience so they can join in. Genius? Maybe. Madness? Absolutely.
Then there’s #HustleGPT—a wild mashup of creativity and hustle. Algorithms can inspire, too.
The Opaque Box Problem
Modern algorithms are black boxes—we know what goes in, but what comes out often defies logic. Peek under the hood? Good luck decoding the mess. It’s like opening an airplane black box and expecting a manual in plain English.
And no, we can’t get it right 100% of the time. Training on historical data—riddled with human biases—just scales up the mess. What was once a niche problem now has global consequences.
Remember the two sellers with competing pricing algorithms? One pegged their price 99.83% of the other’s. The other, in turn, marked up by 27%. They went to bed, and after two weeks of auto-updating madness, the book’s price soared to an absurd $23,698,655.93. The algorithms were just following orders.
The Promise (and Peril) of Synthetic Data
Could synthetic data be the magic bullet to eliminate bias? Maybe. But what happens when we give these Digital Minions full agency?
Some are already there. HP’s printers, for instance, reorder ink automatically before you run out—a slick model of B2A2C (Business to Algorithm to Customer). The machines really have your back.
Enter DAOs: The Algorithmic Takeover
DAOs—Decentralized Autonomous Organizations—are the next frontier. Every task, every decision, run by algorithms. The author points out they’re not some sci-fi fantasy; they’re already here.
Depending on your perspective, DAOs are either a utopian dream or a dystopian nightmare. Sure, open-source code helps transparency, but bad actors can still jailbreak the system. So, can human ingenuity keep up with these digital creatures we’ve unleashed?
What’s Sticking with Me
RACERS—Revenue Automation, Continuous Evolution, Relationship Saturation. Watkins Steel is the poster child in this book. They didn’t just sell steel; they reimagined themselves as partners in their customers’ construction success. Think laser scanners for site blueprints, VR headsets for remote collaboration, and a mindset shift from selling to solving.
Or, as Sir Arthur C. Clarke put it:"The only way to discover the limits of the possible is to venture a little way past them into the impossible.
Comments