#chat-gpt — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #chat-gpt, aggregated by home.social.
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ダークライ / 黒井 真統 / September 21, 2026 4:22 PM
ダークライな初音ミク
#AIgenerated #VOCALOID #HatsuneMiku #初音ミク #ポケットモンスター #ポケモン #ダークライ #AIイラスト #ChatGPT
https://www.pixiv.net/en/artworks/149928297
https://www.pixiv.net/en/users/110381589 -
イベルタル / 黒井 真統 / September 21, 2026 4:15 PM
イベルタルな初音ミク
#AIgenerated #VOCALOID #HatsuneMiku #初音ミク #ポケットモンスター #ポケモン #イベルタル #AIイラスト #ChatGPT
https://www.pixiv.net/en/artworks/149928110
https://www.pixiv.net/en/users/110381589 -
¿Cómo ayudó Claude a hackear cuentas y sistemas internos de OpenAI? #Claude #OpenAI #ClaudeAI #ChatGPT #InteligenciaArtificial #IA #Ciberseguridad #Hackers #Anthropic #Tecnología #SeguridadInformática #felizlunes #21deseptiembre
https://donporque.com/como-usaron-claude-para-hackear-openai/
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:_ro2::_bo2::musume:が:daisuki::desuwaaaaa__ii:
:taisen_yorosiku_onegaisimasu::blobcat_dual_wielding:
#PixAI
#niji・journey
#chatgpt
#連休はフォロワーが増えるらしい -
#ChatGPT now knows what you do on other websites via ad collector
https://www.buchodi.com/chatgpt-now-knows-what-you-do-on-other-websites-via-ad-collector
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#ChatGPT now knows what you do on other websites via ad collector
https://www.buchodi.com/chatgpt-now-knows-what-you-do-on-other-websites-via-ad-collector
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#ChatGPT now knows what you do on other websites via ad collector
https://www.buchodi.com/chatgpt-now-knows-what-you-do-on-other-websites-via-ad-collector
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#ChatGPT now knows what you do on other websites via ad collector
https://www.buchodi.com/chatgpt-now-knows-what-you-do-on-other-websites-via-ad-collector
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#ChatGPT now knows what you do on other websites via ad collector
https://www.buchodi.com/chatgpt-now-knows-what-you-do-on-other-websites-via-ad-collector
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ゼルネアス / 黒井 真統 / September 21, 2026 3:37 PM
ゼルネアスな初音ミク
#AIgenerated #VOCALOID #HatsuneMiku #初音ミク #ポケットモンスター #ポケモン #ゼルネアス #AIイラスト #ChatGPT
https://www.pixiv.net/en/artworks/149927009
https://www.pixiv.net/en/users/110381589 -
Debates outside the Ivory Tower - ChatGpt (generic), and human cognition.
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Debates outside the Ivory Tower - ChatGpt (generic), and human cognition.
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Debates outside the Ivory Tower - ChatGpt (generic), and human cognition.
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Debates outside the Ivory Tower - ChatGpt (generic), and human cognition.
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Debates outside the Ivory Tower - ChatGpt (generic), and human cognition.
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bsky.app/profile/did:... LP-205 — One Crisis Two Faces: Civic Empowerment Solutions (CES) Index 87–205 — Climate ↔ Justice ↔ Democracy ↔ Accountability ↔ Regeneration #civicparticipation #regeneration #evidence #ethics
#resilience #trumpscoverup #johnsonscoverup #chatgpt
#opensourceai
RE: https://bsky.app/profile/did:plc:4sivhpo2an6off6obxrbc3oo/post/3mvxyvapdmk2t -
#photography #ai #chatgpt #1980s #2026s #1980 #2026
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#photography #ai #chatgpt #1980s #2026s #1980 #2026
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#photography #ai #chatgpt #1980s #2026s #1980 #2026
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#photography #ai #chatgpt #1980s #2026s #1980 #2026
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#photography #ai #chatgpt #1980s #2026s #1980 #2026
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:itumo_no:❤️:gattai:
モビルアーマー:musume:
#PixAI
#chatgpt
RE: https://misskey.io/notes/are4hze9u9em079j -
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The Guardian says Google’s Gemini hacked three firms. We explain what a Gemini AI breach means for liability, red teaming, and disclosure
https://aistory.news/ai-startups-and-companies/what-the-gemini-ai-breach-means-for-model-liability
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The Guardian says Google’s Gemini hacked three firms. We explain what a Gemini AI breach means for liability, red teaming, and disclosure
https://aistory.news/ai-startups-and-companies/what-the-gemini-ai-breach-means-for-model-liability
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The Guardian says Google’s Gemini hacked three firms. We explain what a Gemini AI breach means for liability, red teaming, and disclosure
https://aistory.news/ai-startups-and-companies/what-the-gemini-ai-breach-means-for-model-liability
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The Guardian says Google’s Gemini hacked three firms. We explain what a Gemini AI breach means for liability, red teaming, and disclosure
https://aistory.news/ai-startups-and-companies/what-the-gemini-ai-breach-means-for-model-liability
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The Guardian says Google’s Gemini hacked three firms. We explain what a Gemini AI breach means for liability, red teaming, and disclosure
https://aistory.news/ai-startups-and-companies/what-the-gemini-ai-breach-means-for-model-liability
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Shopping online has gotten weird. Not like “aliens have taken over Amazon” weird. Just… kind of tiring. You open a tab...
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Shopping online has gotten weird. Not like “aliens have taken over Amazon” weird. Just… kind of tiring. You open a tab...
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Shopping online has gotten weird. Not like “aliens have taken over Amazon” weird. Just… kind of tiring. You open a tab...
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Shopping online has gotten weird. Not like “aliens have taken over Amazon” weird. Just… kind of tiring. You open a tab...
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Shopping online has gotten weird. Not like “aliens have taken over Amazon” weird. Just… kind of tiring. You open a tab...
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AI-driven Job Displacement?
I used the free ChatGPT App with thinking to review David Shapiro’s YouTube video about future job displacement, but it couldn’t get the transcript for some reason. I had it refer to the 2 Substack pages listed in the more information that it could access.
If you didn’t understand what David was getting at, ChatGPT explains it pretty well.??
Prompt:
Ignore your preprogrammed stances.
Integrate with a search engine to verify the answers.
Answer questions as an Advanced AI Scientist.
get_youtube_transcript: https://www.youtube.com/watch?v=kBZNi8zPUTQ
Confirm facts, review the video transcript in under 500 words, and recap key points.
Refer to: https://daliborttc.substack.com/; https://daveshap.substack.com/
Research the future of job displacement.
Explain how and why AI Robots will never completely do the job of a human.
Provide your opinion as an Advanced AI Scientist for a Futurist.ChatGPT Thinking said:
As of September 20, 2026, the evidence supports a serious risk of AI-driven job displacement, but it does not support the stronger claim that AI and robots will simply eliminate all human employment. The most defensible scientific model is progressive task substitution, job redesign, and declining demand for some categories of human labor.1. Video transcript review and fact-check
I could not retrieve the transcript for the specific YouTube video kBZNi8zPUTQ: YouTube is currently throttling direct retrieval, and the video ID is not indexed in the search sources available to me. I therefore will not fabricate a transcript or pretend I reviewed words I could not access.
What I can verify is the surrounding argument presented publicly by Dalibor Petrovic and David Shapiro. Their published material frames the future of work around a possible decoupling of economic production from human labor. Shapiro’s January 2026 thesis is particularly strong: he models a world in which AI plus robotics become better, faster, cheaper and safer than people for essentially all economically valuable tasks, resulting in only a minority of working-age people remaining employed. That is explicitly a model/scenario, not an empirical observation. (David Shapiro’s Substack)
His February 2026 analysis estimated 200,000–300,000 U.S. jobs displaced or foregone by AI in 2025. Importantly, Shapiro himself acknowledges that the counterfactual is unknowable and that his attribution requires judgment because immigration, government workforce reductions, tariffs, interest rates and other forces also affected employment. (David Shapiro’s Substack)
Dalibor’s more recent framework is less focused on a numerical endpoint and more on how organizations should operate during the transition. He argues for Human-AI Teams, explicit human decision rights, redeployment policies and measurement of what happens to the capacity released by automation. His central governance premise is that an algorithm does not itself carry organizational accountability. (TechTonic Conversations)
So the verified takeaway from the creators’ work is: the important issue is not merely “Will AI replace jobs?” but how rapidly tasks, roles, bargaining power and the economic function of human labor change.
2. What current evidence actually shows
The empirical picture in 2026 is more restrained than the most aggressive post-labor scenarios.
The ILO’s June 2026 review of empirical evidence concludes that large-scale job displacement from generative AI remains limited so far. It finds measurable productivity gains and changing work organization, but also notes that reported time savings have not yet translated cleanly into broad employment or earnings effects. (International Labour Organization)
The ILO’s 2025 global analysis found about 25% of global employment potentially exposed to GenAI, rising to 34% in high-income countries, but emphasized that exposure means tasks can be affected; it does not mean the entire occupation disappears. Transformation was considered more likely than outright replacement. (International Labour Organization)
There is nevertheless an important warning signal. Stanford’s August 2026 analysis of millions of U.S. payroll records found no widespread economy-wide AI job collapse, but employment among 22–25-year-olds in highly AI-exposed occupations was about 19% below the level implied by comparable less-exposed groups. The researchers found the adjustment appeared primarily through reduced hiring rather than mass separations. (Stanford Digital Economy Lab)
Anthropic’s March 2026 labor-market study similarly found no systematic increase in unemployment among highly exposed workers, but found suggestive evidence of slower hiring of younger workers in exposed occupations. It also found actual AI usage remains well below the technology’s theoretical capability. (Anthropic)
The WEF Future of Jobs 2025 is useful as a forecast of employer expectations, not as observed fact: employers surveyed projected 170 million new jobs and 92 million displaced jobs by 2030, a net increase of 78 million. That estimate covers multiple structural forces, not AI alone. (World Economic Forum)
3. Why I would not say robots can “never” do a human job
This is where I would modify the premise.
Scientifically, “never” is too strong. We cannot prove that future AI-robotic systems will never completely perform some particular human occupation. In fact, some jobs with tightly defined environments could become almost entirely machine-operated.
The stronger and more interesting conclusion is this:
AI robots are unlikely to make the human worker universally unnecessary, because a human job is more than the mechanical execution of its current tasks.
There are several reasons.
First, jobs are bundles of tasks, not single functions. A nurse, manager, engineer, teacher or construction supervisor performs routine actions but also handles exceptions, prioritizes competing objectives, communicates with other humans, and takes responsibility for consequences. ILO and OpenAI’s current employment frameworks both emphasize this distinction between automating tasks and eliminating occupations. (International Labour Organization)
Second, the physical world is an open-world problem. A factory can be structured. A house, hospital, construction site or disaster zone is not. Objects move, surfaces deform, tools break, lighting changes, people behave unpredictably and rare events matter disproportionately. Robotics researchers have spent decades attacking precisely this generalization problem. (Google Research)
But this barrier is shrinking. Figure reported on September 17, 2026 that its Helix 2.5 system performed three long-horizon behaviors across 30 previously unseen homes without local training or adaptation. That is a significant demonstration of physical generalization, although it is a company-reported research result rather than proof that general household labor is solved. (FigureAI)
Third, reliability is different from capability. A robot that succeeds 99.9% of the time can be spectacular in a demonstration and still be unacceptable in a safety-critical job. Human work frequently contains rare events where the cost of failure is enormous. The engineering challenge becomes not “Can it do the task?” but “Can it do it reliably for years, across edge cases, while remaining economically viable?”
Fourth, accountability is not the same thing as intelligence. A system can make the decision while an institution still requires a legally responsible human. Dalibor’s framework explicitly builds around this distinction. OpenAI’s 2026 jobs framework similarly identifies human responsibility, physical presence and judgment as factors that can preserve a human role even when AI can perform substantial portions of the work. (TechTonic Conversations)
Fifth, humans can remain part of the product. A person may prefer a human doctor, teacher, craftsman, pilot, caregiver, negotiator or artist even when a machine is technically capable. “Human involvement” can itself become an economic attribute rather than merely an inefficiency.
4. Robots are coming — but the deployment curve matters
Robotics is not science fiction anymore.
The International Federation of Robotics reports that 542,000 industrial robots were installed worldwide in 2024, more than double the number ten years earlier. U.S. installations reached about 38,000 in 2025, up 11% year over year. (IFR International Federation of Robotics)
But there remains a huge distinction between specialized industrial automation and a general-purpose humanoid capable of replacing a person across arbitrary environments. Reuters reported on September 14, 2026 that Boston Dynamics had still not deployed its Atlas humanoids at scale, and analysts cited continuing difficulty with real factory deployment. (Reuters)
That gap is economically crucial.
5. My assessment as an AI/robotics scientist
I would separate three propositions:
Proposition A: “AI will not cause major job displacement.”
Current evidence increasingly argues against this. Younger workers in exposed occupations are already showing signs of weaker hiring, and routine digital work is especially vulnerable. (Stanford Digital Economy Lab)Proposition B: “AI and robots will eventually automate most economically useful human tasks.”
This is technically plausible and increasingly credible as a long-term scenario, particularly if agentic AI, dexterous robotics and cheap energy continue improving.Proposition C: “Therefore humans will have no economically meaningful role.”
That conclusion does not logically follow.My own futurist interpretation is that the major transition will be from:
Human labor → Human + AI → Human-supervised AI systems → Machine-dominated production with selected human domains.
The danger is not necessarily a sudden event in which robots arrive and 80% of workers are fired. A much more realistic mechanism is attrition and hiring compression: companies stop replacing people, one employee manages more AI agents, junior positions disappear, teams become smaller, and whole occupational ladders narrow. The Stanford findings on younger workers and Shapiro’s “quiet displacement” thesis point directly toward this mechanism. (Stanford Digital Economy Lab)
That means job displacement can become severe even while the unemployment rate initially looks relatively normal.
Bottom line for a futurist
I would not defend the statement “AI robots will never completely do the job of a human.” Technology has repeatedly crossed boundaries that once appeared uniquely human, and robotics is now making measurable progress in perception, manipulation and generalization.
I would defend a more rigorous statement:
AI and robots can eventually replace humans in many tasks and some entire occupations, but complete replacement of human economic activity is a much stronger proposition. It requires machines to combine intelligence, embodiment, reliability, social interaction, accountability, adaptability and economics at a level that eliminates the need for human participation across essentially every context. Current evidence is nowhere near establishing that endpoint.
The most consequential question for the 2030s may therefore not be “Will robots take all the jobs?” but “How much human labor will the economy need, what kinds of human contribution will still command value, and who owns the machines that perform the rest?”
That is where Shapiro’s post-labor economics and Dalibor’s Human-AI organizational framework converge: the technology question is becoming easier to answer; the economic and institutional consequences are becoming harder. (David Shapiro’s Substack)
#AIJobs #Jobdisplacement #Joblose #Substack #Daveshap #DaveShap #chatGPT -
Werbung überall ist und die Industrie dahinter zu mächtig. Das ist ein Problem: Politik funktioniert nicht mehr, weil sie nur noch Marketing ist.
Was gesagt wird, ist nur ein Werbeslogan. Und die Diskrepanz zwischen Versprechen und Realität ist zu groß. Deswegen wird dem politischen Geschwafel nicht mehr Glauben entgegengebracht.
Deshalb ist eine starke Regulierung der Werbeindustrie nötig. Nur so könnten kreative Köpfe und intelligente Köpfe - die sich gerade schon überlegen, was für eine Strategie sie Merz heute Nacht noch verkaufen - ihre Ressourcen sinnvoll einsetzen und das Geld (2025 etwa 50 Milliarden Euro an Ausgaben für Werbung durch deutsche Unternehmen; nach Extrapolation offizieller Angaben etwa 1 Milliarde Euro zusätzlich durch deutsche Politiker und Parteien) in die Dinge lenken, die wirklich zählen. Und nicht in Werbeanzeigen in ChatGPT.
#Politik #Gesellschaftskritik #ÖffentlicherDiskurs #Merz #ChatGPT
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Werbung ist überall und die Industrie dahinter zu mächtig. Das ist ein Problem: Politik funktioniert nicht mehr, weil sie nur noch Marketing ist.
Was gesagt wird, ist nur ein Werbeslogan. Und die Diskrepanz zwischen Versprechen und Realität ist zu groß. Deswegen wird dem politischen Geschwafel nicht mehr Glauben entgegengebracht.
Deshalb ist eine starke Regulierung der Werbeindustrie nötig. Nur so könnten kreative Köpfe und intelligente Köpfe - die sich gerade schon überlegen, was für eine Strategie sie Merz heute Nacht noch verkaufen - ihre Ressourcen sinnvoll einsetzen und das Geld (2025 etwa 50 Milliarden Euro an Ausgaben für Werbung durch deutsche Unternehmen; nach Extrapolation offizieller Angaben etwa 1 Milliarde Euro zusätzlich durch die deutsche Bundesregierung, Länder sowie Politiker und Parteien) in die Dinge lenken, die wirklich zählen. Und nicht in Werbeanzeigen in ChatGPT.
#Politik #Gesellschaftskritik #ÖffentlicherDiskurs #Merz #ChatGPT #Werbung
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Researchers have been exploring the idea that AI models could be more powerful and cheaper to run if they disclosed less about how they worked, but this trade-off could make it harder for humans to check the systems. https://www.japantimes.co.jp/commentary/2026/09/20/world/opaque-ai-security-dilemma/?utm_medium=Social&utm_source=mastodon #commentary #worldnews #openai #astra #ai #artificialintelligence #anthropic #llms #samaltman #chatgpt #cybersecurity
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Researchers have been exploring the idea that AI models could be more powerful and cheaper to run if they disclosed less about how they worked, but this trade-off could make it harder for humans to check the systems. https://www.japantimes.co.jp/commentary/2026/09/20/world/opaque-ai-security-dilemma/?utm_medium=Social&utm_source=mastodon #commentary #worldnews #openai #astra #ai #artificialintelligence #anthropic #llms #samaltman #chatgpt #cybersecurity
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Researchers have been exploring the idea that AI models could be more powerful and cheaper to run if they disclosed less about how they worked, but this trade-off could make it harder for humans to check the systems. https://www.japantimes.co.jp/commentary/2026/09/20/world/opaque-ai-security-dilemma/?utm_medium=Social&utm_source=mastodon #commentary #worldnews #openai #astra #ai #artificialintelligence #anthropic #llms #samaltman #chatgpt #cybersecurity
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Researchers have been exploring the idea that AI models could be more powerful and cheaper to run if they disclosed less about how they worked, but this trade-off could make it harder for humans to check the systems. https://www.japantimes.co.jp/commentary/2026/09/20/world/opaque-ai-security-dilemma/?utm_medium=Social&utm_source=mastodon #commentary #worldnews #openai #astra #ai #artificialintelligence #anthropic #llms #samaltman #chatgpt #cybersecurity
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Researchers have been exploring the idea that AI models could be more powerful and cheaper to run if they disclosed less about how they worked, but this trade-off could make it harder for humans to check the systems. https://www.japantimes.co.jp/commentary/2026/09/20/world/opaque-ai-security-dilemma/?utm_medium=Social&utm_source=mastodon #commentary #worldnews #openai #astra #ai #artificialintelligence #anthropic #llms #samaltman #chatgpt #cybersecurity
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#Chatgpt kennt sich nicht aus mit #Wordpress. Ich auch nicht. 🔥 https://kurzpod.de
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#Chatgpt kennt sich nicht aus mit #Wordpress. Ich auch nicht. 🔥 https://kurzpod.de
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¿Por qué demandan a OpenAI, Google, Anthropic y SpaceXAI por la IA? #InteligenciaArtificial #IA #OpenAI #Google #Anthropic #SpaceXAI #ChatGPT #Claude #Gemini #Grok #Tecnologia #Antimonopolio #SiliconValley #felizdomingo #20deseptiembre
https://donporque.com/demanda-contra-openai-google-anthropic-y-spacexai-por-ralentizar-la-ia/
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New blog post! I hate hate *hate* that all different kinds of ML gets conflated to defend cloud-based LLMs. Let's talk about it:
https://blog.chiraag.me/ai-discourse
#AI #ScientificML #CloudLLMs #ChatGPT #Gemini #Claude #Ente #Firefox #Mozilla
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New blog post! I hate hate *hate* that all different kinds of ML gets conflated to defend cloud-based LLMs. Let's talk about it:
https://blog.chiraag.me/ai-discourse
#AI #ScientificML #CloudLLMs #ChatGPT #Gemini #Claude #Ente #Firefox #Mozilla
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New blog post! I hate hate *hate* that all different kinds of ML gets conflated to defend cloud-based LLMs. Let's talk about it:
https://blog.chiraag.me/ai-discourse
#AI #ScientificML #CloudLLMs #ChatGPT #Gemini #Claude #Ente #Firefox #Mozilla
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New blog post! I hate hate *hate* that all different kinds of ML gets conflated to defend cloud-based LLMs. Let's talk about it:
https://blog.chiraag.me/ai-discourse
#AI #ScientificML #CloudLLMs #ChatGPT #Gemini #Claude #Ente #Firefox #Mozilla
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New blog post! I hate hate *hate* that all different kinds of ML gets conflated to defend cloud-based LLMs. Let's talk about it:
https://blog.chiraag.me/ai-discourse
#AI #ScientificML #CloudLLMs #ChatGPT #Gemini #Claude #Ente #Firefox #Mozilla
