We’re all in on AI now—full scale, full speed. But once a technology reaches critical mass, society rarely pauses to ask: Should we proceed with caution? Or even how?
I’ve been in this field long enough to see the full arc. I started with punched cards and COBOL on mainframes. Today, I work with IBM on cloud technology and AI. I don’t claim to be an AI expert—but I am a seasoned observer of computing’s evolution.
Before diving into AI, I want to reflect on the broader legacy of computing. Over the past 50 years, I’ve been fortunate to work on complex systems, database architectures, and cloud migrations. I’ve seen firsthand how computing has powered scientific breakthroughs, transformed industries, and reshaped daily life.
Much of this I’m deeply grateful for. But not everything has gone smoothly. Some wreckage deserves acknowledgment—because if we don’t learn from the unintended consequences of past technologies, we risk repeating them with AI.
There’s no denying that computers and AI have empowered us to achieve feats once thought impossible—from decoding genomes to exploring distant planets. But alongside these breakthroughs, a host of unintended consequences have emerged—some subtle, others deeply disruptive.
In this first part of a two-part series, we’ll explore the darker offshoots of our digital age, including how computing has reshaped privacy, security, society, and global wealth distribution.
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