Let’s admit it: most professionals aren’t “embracing AI.” They’re stress-testing it with the emotional stability of a man holding a glass of water on a London bus. Publicly, we’re all: Sharing “AI will 10x your productivity” thinkpieces Saying “prompt engineering” with a straight face Pretending we’re one weekend away from building Skynet in Excel Privately, we’re using ChatGPT to: Rewrite emails so they sound “firm but friendly” Turn “this is wrong” into “quick clarification” Make meeting notes look like we actually listened And the main growth strategy behind all of this is not innovation. It’s career insecurity , packaged as a lifestyle . And I’m looking at you behind all this, you Silicon Valley billionaires! Take an example: architects. To be competent today, they already juggle: Design + physics + real constraints A zoo of clunky software Clients, budgets, deadlines, liability A dictionary of local building codes Now add the new requirement: “ Learn AI or you’ll be obsolete .” But what does “ Learn AI ” mean for most people in 2026? It rarely means understanding neural nets. It mostly means collecting SaaS subscriptions like Pokemon cards: $20/month here, $20/month there, $20/month everywhere. Soon your entire job becomes “ managing tools that manage tools. ” Even software engineers are being told: “ You won’t be doing real coding much longer .” Which is a wild message, because “ upskilling ” is starting to sound like: Pay a premium to watch a bot do your work faster than you can. Then there’s the energy angle. Sam Altman recently defended AI’s resource use with the argument that if you’re going to count the energy to train AI, you should also count the energy it takes to “ train ” a human for 20 years (food, life, the whole deal). Fair enough as a provocation, but here’s the uncomfortable part: Data centres already used about 1.5% of global electricity in 2024 (around 415 TWh), and the IEA expects demand to grow roughly 15% per year to 2030 , with total data-centre electricity consumption projected to roughly double to about 945 TWh (just under 3% of global electricity). So the near-future vibe is: Humans sitting still, paying bots to do their jobs, while they scroll short-form videos that bots also generated. Basically, WALL-E , but with monthly billing. Genuine questions for this sub: What does “ learning AI ” mean that isn’t just “buy more tools”? Where’s the line between “useful assistant” and “ subscription treadmill ”? If the productivity gains are real, why does it feel like everyone is more anxious, not less? submitted by /u/Fit_Wishbone8012
Originally posted by u/Fit_Wishbone8012 on r/ArtificialInteligence