This raises the question of whether AI has the potential to shape a fundamental aspect of human culture: the way we speak. Recent analyses revealed that scientific publications already exhibit evidence of AI-specific language. But this evidence is inconclusive, since scientists may simply be using AI to copy-edit their writing. To explore whether AI has influenced human spoken communication, we transcribed and analyzed about 280,000 English-language videos of presentations, talks, and speeches from more than 20,000 YouTube channels of academic institutions. We find a significant shift in the trend of word usage specific to words distinctively associated with ChatGPT following its release. These findings provide the first empirical evidence that humans increasingly imitate LLMs in their spoken language. Our results raise societal and policy-relevant concerns about the potential of AI to unintentionally reduce linguistic diversity, or to be deliberately misused for mass manipulation. They also highlight the need for further investigation into the feedback loops between machine behavior and human culture.

The idea that superintelligent robots are alien invaders coming to "steal our jobs" reveals profound shortcomings in the way we think about work, value, and intelligence itself. Labor is not a zero-sum game, and robots aren't an "other" that competes with us. Like any technology, they're part of us, growing out of civilization the same way hair and nails grow out of a living body. When we "other" a fruit-picking robot – thinking of it as a competitor in a zero-sum game – we take our eyes off the real problem: the human who used to pick the fruit is considered disposable by the farm's owners and by society when no longer fit for that job. This implies that the human laborer was already being treated like a non-person – that is, like a machine.

As future musical AIs adhere closely to human music, they may form their own attachments to particular human artists in their databases, and these biases may in the worst case lead to potential existential threats to all musical history. AI super fans may act to corrupt the historical record and extant recordings in favour of their own preferences, and preservation of the diversity of world music culture may become even more of a pressing issue than the imposition of 12 tone equal temperament or other Western homogenisations. We discuss the technical capability of AI cover software and produce Taylor's Versions of famous tracks from Western pop history as provocative examples; the quality of these productions does not affect the overall argument (which might even see a future AI try to impose the sound of paperclips onto all existing audio files, let alone Taylor Swift). We discuss some potential defenses against the danger of future musical monopolies, whilst analysing the feasibility of a maximal 'Taylor Swiftication' of the complete musical record.

Inspired by foundational studies in classical and quantum physics, and by information retrieval studies in quantum information theory, we prove that the notions of 'energy' and 'entropy' can be consistently introduced in human language and, more generally, in human culture. More explicitly, if energy is attributed to words according to their frequency of appearance in a text, then the ensuing energy levels are distributed non-classically, namely, they obey Bose-Einstein, rather than Maxwell-Boltzmann, statistics, as a consequence of the genuinely 'quantum indistinguishability' of the words that appear in the text. Secondly, the 'quantum entanglement' due to the way meaning is carried by a text reduces the (von Neumann) entropy of the words that appear in the text, a behaviour which cannot be explained within classical (thermodynamic or information) entropy. We claim here that this 'quantum-type behaviour is valid in general in human language', namely, any text is conceptually more concrete than the words composing it, which entails that the entropy of the overall text decreases. In addition, we provide examples taken from cognition, where quantization of energy appears in categorical perception, and from culture, where entities collaborate, thus 'entangle', to decrease overall entropy. We use these findings to propose the development of a new 'non-classical thermodynamic theory' for human cognition, which also covers broad parts of human culture and its artefacts and bridges concepts with quantum physics entities.

From abstract art, digital painting, complex sculpture, architectural visualisation or 5 years old hand drawing, whatever you ask for, the AI makes it, or at least tries its best to. Does that cheapen the value of someone who puts their hands in researching, planning, sketching, developing their artworks; versus an AI just learning that from having studied millions of existing images and figuring out what we humans like to look at, and replicating that in mere minutes? You can create artwork without specifying colour or even form of your subject, and simply allowing the AI to take the reins, while you only provide inspirations and mood you wanted to achieve. It's not perfect though, as you will quickly notice; it can not, at the moment at least, understand nuance interactions between human culture, and everything that is presented in the resulting image is based on learning from what people created. Allowing it to run without supervision will in turn create a visual language in our society that might encourage bigotry and biases, and limit true creativity that inspire progression through diversity.

Our Foundational AI CDT addresses the need for AI workers by training researchers capable of advancing core AI algorithms. Our graduates will help shape the social, scientific and economic landscape through scientific breakthroughs and the creation of companies on the basis of novel AI technology. Current AI machines are largely "dumb" they don't understand their physical environment, nor have enough understanding of human culture to communicate in natural ways. Our vision is that AI is in its infancy and that AI breakthroughs are key to controlling and shaping the future technological landscape. However, creating effective AI is challenging given our limited understanding of how intelligence works.

Well, not literally, not yet anyway -- but that'll be happening soon enough with further advances in the fields of robotics and artificial intelligence to the point that you will no longer be able to distinguish whether or not your sexbot was having an actual simulated orgasm or just faking it. For those of you who haven't made it past first base in the world of sexual machines and are asking, "Sexbot? A "sexbot" is a robot designed for humans to have sexual intercourse with. It is a machine engineered for sexual simulation and stimulation. If this sounds a bit mechanical and crass, it's because, well, it sort of is. That being said, a major facet of human sexual intercourse is mechanical -- so much so that prescribing tool analogies to our descriptions of it have become part of our popular cultural lexicon. But please, don't drill me on the particulars. While there are deep emotional, psychological, and spiritual dimensions to human sexuality, it is, at its core, a very physical action. Most of us were forged in the crucible of that act, excepting the small percentage (about 2 percent in the U.S.) of embryos conceived using in vitro fertilization. My purpose here is not to pass judgement on people's sex lives nor their preferences or fetishes nor wade into the morass of a sexual morality debate. As a technologist, it's my obligation to inform you that sexbots are a rapidly emerging technology that will have a profound impact upon the future of human sexual relations with the integration of increasingly life-like robots into the fabric of everyday human life. While sexbots are a fairly new phenomenon, the existence of man-made sexual devices has been around for tens of thousands of years, beginning with the artificial phallus, the oldest of which was discovered in Germany in 2005. Made of siltstone and measuring in at 7.8" in length, it is estimated to be 28,000 years old.

Artificial neural networks have given AIs the functionality for complex problem solving and pattern recognition, and they have entered the workforce, particularly in areas of big data analysis and global finance. As we begin to interact with and study these new learning machines, interesting questions arise concerning unbiased decisions. Are they going to take on human behavioral and gender distinctions (gender identity), because they have been programmed with data sets that have unconscious bias? Will those who are giving the learning machines feedback to focus their problem solving allow behavioral constraints into the teaching? If we give the AIs a woman's voice, and a woman's name, will we interact with her as if she was a woman?

The recent explosion of interest, hype, and fear about artificial intelligence, data science, machine learning, and robotics has focused a spotlight on software engineers. The business magnate Elon Musk has called for regulation and the President of Russia Vladimir Putin has declared that world domination will result from mastering AI. Are software engineers responsible for these outcomes? Here, I argue that software engineers have less control over their designs than they likely realize. Instead, software technologies are evolving in a Darwinian way, or more precisely, they are co-evolving with human culture.

Family Physics" may be the best episode of Public Radio's long running show, This American Life. Import key concepts from the realms of quantum mechanics and cosmology and use them to illuminate the everyday world of parents, kids, and their interactions. Introducing the show, however, host Ira Glass was quick to point out how much physicists detest this kind of enterprise. "They hate it when non-scientists … apply principles from physics to their petty little lives and petty little relationships." Glass was equally quick to point out that he and his colleagues at the show just did not care.