The Human Computer | What Automation Teaches Us about Surviving AI
Ivan Daunis
Sold by preigu, Osnabrück, Germany
AbeBooks Seller since August 5, 2024
New - Soft cover
Condition: New
Ships from Germany to U.S.A.
Quantity: 5 available
Add to basketSold by preigu, Osnabrück, Germany
AbeBooks Seller since August 5, 2024
Condition: New
Quantity: 5 available
Add to basketThe Human Computer | What Automation Teaches Us about Surviving AI | Ivan Daunis | Taschenbuch | Englisch | 2025 | Slavinsky | EAN 9798218902490 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Seller Inventory # 134453625
They said electronic computers would eliminate human computers. They were wrong.
In 1946, ENIAC could calculate in seconds what took human computers weeks. Everyone predicted mass unemployment. Instead, those "obsolete" workers became the world's first programmers—and launched the entire software industry.
History is repeating itself. Most people are missing the pattern.
I'm literally building the automation that's supposed to replace you.
I'm Ivan Daunis. I lead agentic AI development at PayPal—systems that write code, agents that make decisions. I've filed patents on AI systems, published research on agent orchestration, and earned my Master's in AI/ML at 48 while building the automation everyone worries about.
Here's what I've learned from the inside: AI won't replace you. But engineers who use AI will replace engineers who don't.
In my 30-year career, I've lived through four waves of "obsolescence":
Each time: panic, adaptation, transformation. Each time, humans who adapted didn't just survive—they thrived.
This book reveals the pattern and gives you the playbook.
Inside you'll discover:
I'm not a consultant writing about AI's potential. I'm an engineer who sees what works in reality, not just in demos.
If you're doing knowledge work—software engineering, data science, product management, or anything in between—you're facing the same choice the human computers faced in 1946.
The good news? The pattern is reliable. Those who recognize it early have enormous advantages.
This isn't about surviving AI. It's about using AI to become irreplaceable.
"About this title" may belong to another edition of this title.
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