{"id":21070,"date":"2026-04-13T16:09:10","date_gmt":"2026-04-13T16:09:10","guid":{"rendered":"https:\/\/ideainthebox.com\/index.php\/2026\/04\/13\/why-opinion-on-ai-is-so-divided\/"},"modified":"2026-04-13T16:09:10","modified_gmt":"2026-04-13T16:09:10","slug":"why-opinion-on-ai-is-so-divided","status":"publish","type":"post","link":"https:\/\/ideainthebox.com\/index.php\/2026\/04\/13\/why-opinion-on-ai-is-so-divided\/","title":{"rendered":"Why opinion on AI is so divided"},"content":{"rendered":"
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This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first,\u00a0<\/em>sign up here<\/em><\/a>.<\/em><\/p>\n

In an industry that doesn\u2019t stand still, Stanford\u2019s AI Index, an annual roundup of key results and trends<\/a>, is a chance to take a breath. (It\u2019s a marathon, not a sprint<\/a>, after all.)<\/p>\n

This year\u2019s report<\/a>, which dropped today, is full of striking stats. A lot of the value comes from having numbers to back up gut feelings you might already have, such as the sense that the US is gunning harder for AI than everyone else: It hosts 5,427 data centers (and counting). That\u2019s more than 10 times as many as any other country.\u00a0\u00a0<\/p>\n

There\u2019s also a reminder that the hardware supply chain the AI industry relies on has some major choke points. Here\u2019s perhaps the most remarkable fact: \u201cA single company, TSMC, fabricates almost every leading AI chip, making the global AI hardware supply chain dependent on one foundry in Taiwan.\u201d One foundry! That\u2019s just wild.<\/p>\n

But the main takeaway I have from the 2026 AI Index is that the state of AI right now is shot through with inconsistencies. As my colleague Michelle Kim put it today in her piece about the report<\/a>: \u201cIf you\u2019re following AI news, you\u2019re probably getting whiplash. AI is a gold rush. AI is a bubble. AI is taking your job. AI can\u2019t even read a clock.\u201d (The Stanford report notes that Google DeepMind\u2019s top reasoning model, Gemini Deep Think, scored a gold medal in the International Math Olympiad but is unable to read analog clocks half the time.)<\/p>\n

Michelle does a great job covering the report\u2019s highlights. But I wanted to dwell on a question that I can\u2019t shake. Why is it so hard to know exactly what\u2019s going on in AI right now?\u00a0\u00a0<\/p>\n

The widest gap seems to be between experts and non-experts. \u201cAI experts and the general public view the technology\u2019s trajectory very differently,\u201d the authors of the AI Index write. \u201cAssessing AI\u2019s impact on jobs, 73% of U.S. experts are positive, compared with only 23% of the public, a 50 percentage point gap. Similar divides emerge with respect to the economy and medical care.\u201d<\/p>\n

That\u2019s a huge<\/em> gap. What\u2019s going on? What do experts know that the public doesn\u2019t? (\u201cExperts\u201d here means US-based researchers who took part in AI conferences in 2023 and 2024.)<\/p>\n

I suspect part of what\u2019s going on is that experts and non-experts base their views on very different experiences. \u201cThe degree to which you are awed by AI is perfectly correlated with how much you use AI to code,\u201d a software developer posted on X the other day<\/a>. Maybe that\u2019s tongue-in-cheek, but there\u2019s definitely something to it.<\/p>\n

The latest models from the top labs are now better than ever at producing code. Because technical tasks like coding have right or wrong results, it is easier to train models to do them, compared with tasks that are more open-ended. What\u2019s more, models that can code are proving to be profitable, so model makers are throwing resources at improving them.<\/p>\n

This means that people who use those tools for coding or other technical work are experiencing this technology at its best. Outside of those use cases, you get more of a mixed bag. LLMs still make dumb mistakes. This phenomenon has become known as the \u201cjagged frontier\u201d: Models are very good at doing some things and less good at others.<\/p>\n

The influential AI researcher Andrej Karpathy<\/a> also had some thoughts. \u201cJudging by my [timeline] there is a growing gap in understanding of AI capability,\u201d he wrote in reply to that X post. He noted that power users (read: people who use LLMs for coding, math, or research) not only keep up to date with the latest models but will often pay $200 a month for the best versions. \u201cThe recent improvements in these domains as of this year have been nothing short of staggering,\u201d he continued.<\/p>\n

Because LLMs are still improving fast, someone who pays to use Claude Code will in effect be using a different technology from someone who tried using the free version of Claude to plan a wedding six months ago. Those two groups are speaking past each other.<\/p>\n

Where does that leave us? I think there are two realities. Yes, AI is far better than a lot of people realize. And yes, it is still pretty bad at a lot of stuff that a lot of people care about (and it may stay that way). Anyone making bets about the future on either side should bear that in mind.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

This story originally appeared in The Algorithm, our weekly newsletter […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[226],"tags":[],"class_list":["post-21070","post","type-post","status-publish","format-standard","hentry","category-technology"],"acf":[],"_links":{"self":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/posts\/21070","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/comments?post=21070"}],"version-history":[{"count":0,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/posts\/21070\/revisions"}],"wp:attachment":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/media?parent=21070"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/categories?post=21070"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/tags?post=21070"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}