How AI harms technology
AI kills, harms, delays or imposes higher prices on a wide range of technologies and technology products and services. The AI industry is:
- Create catastrophic chip shortages. Major RAM makers Samsung, SK Hynix and Micron have shifted their production to focus on the high-bandwidth memory (HBM) needed for AI. This has led to a shortage of standard DRAM and NAND chips used in smartphones, laptops and medical devices.
- Raising equipment prices. Due to lack of memory, building electronic components without AI becomes expensive. By early 2026, prices for standard computer memory and storage drives (SSDs) had increased because the industry prioritized high-margin AI chips over consumer parts. There is even a tendency to more and more people are buying used laptops because they can’t afford to buy new ones.
- Delaying GPUs and the devices that use them. The demand for AI computing power, which typically relies on graphics processing units (GPUs), has created a huge backlog for processors and with it, the devices that use them to, you know, process graphics.
- Create COVID-like shortages. Diverting chips to AI infrastructure poses problems for non-AI hardware launches. Shortages of basic energy and automotive chips are affecting industries from automakers to appliance makers. It’s like COVID all over again.
- Divert investments towards startups. Non-AI startups struggle to raise funds. Investors are investing their cash almost exclusively in AI projects, forcing non-AI founders to pivot or adopt “AI first” aspects (called “AI washing”), even when this is not necessary.
- Drain brains from research laboratories. There has always been a relationship between technology-related university research laboratories and technology. Today this is distorted by AI. Private AI companies are hiring top university researchers and engineers with huge salaries. This hollows out academic departments and research labs not specializing in AI, threatening the future talent pool in critical fields like traditional software engineering.
- Discourage graduates from entering technology fields. As companies shift to AI, they are cutting entry-level jobs in other areas. In the United States, job postings for entry-level positions fell by 35% between 2023 and 2025. This is disrupting career progression and discouraging young people from pursuing careers in technologies other than AI.
- Weaponize cyberattacks. Malicious actors are using AI to attack non-AI systems. AI allows even moderately skilled hackers to launch sophisticated attacks. Tools that clone voices and generate false identities violate traditional security protocols, overwhelming standard IT infrastructure defenses.
- Create a new digital divide. Technicians, developers, and those adopting AI for ambiance coding and other tasks are moving away from people who are less technical or less inclined.
- Turning the public against the tech industry. Public admiration for Silicon Valley is deteriorating in part because of the excesses of the AI industry’s toxic “996” work culture, job threats, AI waste, ridiculously high salaries, skyrocketing electricity bills, and environmental damage from new data centers. There’s also the unauthorized theft of personal data and copyrighted artwork to train models, as well as the flood of deepfakes, misinformation and AI slop that people see on social networks like Facebook.
- Destroy application request. The usual software market is moving toward “vibe-coding,” where people abandon paid app subscriptions to create their own custom, disposable apps using AI platforms like Replit, Lovable, and Cursor. Gartner predicts that consumers will reduce their use of mobile apps by 25% as they rely on generative AI assistants to handle tasks rather than scrolling through separate apps, even without ambiance coding. Either way, the app development ecosystem is under strain.
- Threatening the Future of Facts. AI chatbots are transforming search engines by providing direct answers instead of lists of links, a change that deprives publishers of the website traffic and revenue they need to survive. This reduces the incentives and finances needed to produce and publish new facts (for lack of a better term) while frequently presenting false information as fact. This hurts technology, an industry that depends on education, new knowledge and training.
This all seems disastrous. And in the short term, that’s not good. What we don’t yet know is the long-term impact of the AI revolution and whether it will prove to be a net benefit or harm to the non-AI people, businesses, projects, culture, and communities we’ve loved for decades.