Conversations about AI has been feeling a lot more loaded lately. I thought this could be a decision bias, because I recently moved to a hub where a lot more people around me talk about AI at work, after work, in social settings and whatnot. But no, I do think this is more about \u201cnow\u201d then \u201cwhere\u201d. I lived in various other hubs in various durations before, and frankly talked a lot more about AI, but it would feel a lot more different. <\/p>\n\n\n\n
I believe it\u2019s because AI conversations not attract simply everyone, many new profiles, backgrounds, points of view\u2026 This is great, but this also means we bring one of the best mental coping mechanisms humans have: our biases. We have a tendency to figure out which \u201cAI camp\u201d the other person is in as quickly as possible. If you\u2019re very excited about AI, you must not be caring about data privacy. If you think we\u2019re in an AI bubble, you\u2019re not AGI-pilled. If you think we should regulate AI as soon as possible, then you never held bitcoin.<\/p>\n\n\n\n
However, most people working in the field of AI, be it policy or engineering or safety or governance (or adjacent, you know) have quite nuanced opinions and probably won\u2019t fit whatever our mental Sorting Hat concludes.<\/p>\n\n\n\n
1. AI capabilities will continue to grow, AND there is also an AI bubble<\/strong><\/p>\n\n\n\n Most people expecting tremendous capability growth also<\/em> think not every startup that got thrown a $100M cheque for doing “AI” will survive. Even though I disagree with certain points that Zitron made in his widely-circulated article<\/a>, I agree with one thing that this article puts out: there are so many dependencies in the market that it is almost impossible to expect a complete \u201cAI takeoff\u201d and there naturally will be some losers. In that nuance, for example, I personally find infrastructure as the most stable part of the ecosystem, and interestingly agree with Bezos\u2019 statements here<\/a>. But returning to Zitron\u2019s examples, many of the new \u201cAI neoclouds\u201d could still fail, not because the market won\u2019t grow, but because some of these companies pivoted from traditional cloud services into AI workloads without the business fundamentals or strategy to claim meaningful market share.<\/p>\n\n\n\n My timelines are a bit longer than the shortest ones out there, for reasons Demis Hassabis\u2019 expressed in this interview<\/a>. I don\u2019t know if it is too long that some returns won\u2019t be generated in expected time. I do believe that timelines are short for society to adapt to the changes it would bring as a whole. So saying \u201cthis is coming fast!\u201d doesn’t make you a bubble-denier (if that\u2019s a phrase).<\/p>\n\n\n\n 2. AI can be great, and AI products can be awful<\/strong><\/p>\n\n\n\n The latest models have been showing remarkable successes. While chatbots seem like the most scalable deployment of general-purpose LLMs, they are definitely suboptimal. It is true that chatbot companies don\u2019t make it intuitive whether they use your data for training and while I tend to enjoy personalization more than others around me, I do think one should have the transparency to learn what\u2019s going on with their data or product usage. I do really hope that the primary monetization of this technology ends up looking very different from social media. Maybe I\u2019m too optimistic, but even though the companies do not have the right incentives, and that the road is rocky, I believe the adoption will evolve with more human and society-compatible ways. <\/p>\n\n\n\n AI development itself is very dynamic, and beyond academic papers, the product releases are a window for us to look into what some of the biggest investors in AI R&D (companies like OpenAI, DeepMind etc.) are doing. I can get just as excited about a chatbot\u2019s improved answers<\/a> after a new model update as I do about a research milestone from a company<\/a> that hasn\u2019t even released a product yet. So, it’s not a mere fascination of these tools or companies themselves. In the meantime, though, I do think intentional users can gain enormous value from chatbots. Speaking from firsthand experience, this doesn\u2019t make me indifferent to child safety, job loss, or other real risks which could indeed affect me as an employee, or my nieces and nephews as they grow up. That\u2019s why I appreciate voices like Givens who emphasize<\/a> the importance of using these tools deliberately and remind us in which ways we can, and should, demand stronger consumer protections and clearer standards.<\/p>\n\n\n\n I could come up with more, but I probably made the point. I hope I don’t do what I’m complaining about here, but if I do, I hope you’re a Ravenclaw.<\/p>","protected":false},"excerpt":{"rendered":" Conversations about AI has been feeling a lot more loaded lately. I thought this could be a decision bias, because I recently moved to a hub where a lot more people around me talk about AI at work, after work, in social settings and whatnot. But no, I do think this is more about \u201cnow\u201d then \u201cwhere\u201d. I lived in various other hubs in various durations before, and frankly talked a lot more about AI, but it would feel a lot more different. I believe it\u2019s because AI conversations not attract simply everyone, many new profiles, backgrounds, points of view\u2026 This is great, but this also means we bring one of the best mental coping mechanisms humans have: our biases. We have a tendency to figure out which \u201cAI camp\u201d the other person is in as quickly as possible. If you\u2019re very excited about AI, you must not be caring about data privacy. If you think we\u2019re in an AI bubble, you\u2019re not AGI-pilled. If you think we should regulate AI as soon as possible, then you never held bitcoin. However, most people working in the field of AI, be it policy or engineering or safety or governance (or adjacent, […]<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_stc_notifier_status":"sent","_stc_notifier_sent_time":"2025-11-25 00:24:09","_stc_notifier_request":false,"_stc_notifier_prevent":false,"_stc_subscriber_keywords":"","_stc_subscriber_search_areas":"","footnotes":""},"categories":[90],"tags":[],"class_list":["post-1515","post","type-post","status-publish","format-standard","hentry","category-future"],"_links":{"self":[{"href":"https:\/\/www.bengusuozcan.com\/en\/wp-json\/wp\/v2\/posts\/1515"}],"collection":[{"href":"https:\/\/www.bengusuozcan.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bengusuozcan.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bengusuozcan.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bengusuozcan.com\/en\/wp-json\/wp\/v2\/comments?post=1515"}],"version-history":[{"count":3,"href":"https:\/\/www.bengusuozcan.com\/en\/wp-json\/wp\/v2\/posts\/1515\/revisions"}],"predecessor-version":[{"id":1530,"href":"https:\/\/www.bengusuozcan.com\/en\/wp-json\/wp\/v2\/posts\/1515\/revisions\/1530"}],"wp:attachment":[{"href":"https:\/\/www.bengusuozcan.com\/en\/wp-json\/wp\/v2\/media?parent=1515"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bengusuozcan.com\/en\/wp-json\/wp\/v2\/categories?post=1515"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bengusuozcan.com\/en\/wp-json\/wp\/v2\/tags?post=1515"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}