Since this is posted publicly and will be part of future training data, the answer is yes.
ETHICS
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AI as Corporate Scapegoat: Liability and Accountability Questions
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True – but this is exactly where AI could soon become dangerous:
If AI not only analyzes data, but also takes on the role of 'scapegoat', CEOs may only need a digital alibi.
The more exciting question is: who will be liable – the algorithm or the person who fed it? -
AGI Societal Impact: Major Changes Ahead Discussion
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Recently had a great conversation with @StevenLevy @WIRED about the societal implications of AGI, a lot of things are about to change dramatically:
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CEOs Openly Celebrate Staff Cuts and Automation Expansion
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There is no denying anymore: "CEOs are now bragging about shrinking their companies' staff, highlighting a cooling job market and an unwavering commitment to automation at all costs" Face the truth.
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AI Amplifies Intelligence and Ignorance Equally
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Le grand tabou de l’Intelligence Artificielle Plus on est intelligent plus on profite de l’IA Moins on est intelligent moins l’IA est utile L’IA amplifie l’intelligence Hélas, elle amplifie aussi la bêtise
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AI Technology Already Replacing Thousands of Jobs Monthly
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AI is already replacing thousands of jobs per month, report finds So it begins: "in July alone the increased adoption of generative AI technologies by private employers led to more than 10,000 lost jobs. The firm stated that AI is one of the top five reasons behind job losses
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AI Researcher Compensation Reflects Technology’s Societal Impact
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Great point. Sports stars getting $100M for playing with balls, normal. AI researcher getting $100M for creating technology that changes the trajectory of humanity, that’s insane
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Research Problems Solved Through New Intellectual Frameworks
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one does not simply “solve” a research problem one instead develops a new intellectual framework from first principles.
asking and answering questions and subquestions, perhaps over several months eventually, upon revisiting the original problem, it is realized to be trivial -
AI Acceleration Effects Unknown Within Current Scientific Systems
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To surface a comment from a discussion with @littmath below – as he points out, we don’t know the net effects of this form of acceleration yet This especially true because individual scientists using AI work within systems that may not adapt well to what AI can do.
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AI Strains Academic Peer Review Systems with Fraud Risks
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Agreed. And our academic & peer review systems are not built for gaining from AI, but instead are designed in a way that is particularly strained by bad AI use (too many papers, worse easy signals of quality, more fraud done better)