As AI tools increasingly shape how we write, they may also quietly reshape how we perceive ourselves. This paper explores the psychological impact of co-writing with AI on people's locus of control. Through an empirical study with 462 participants, we found that employment status plays a critical role in shaping users' reliance on AI and their locus of control. Current results demonstrated that employed participants displayed higher reliance on AI and a shift toward internal control, while unemployed users tended to experience a reduction in personal agency. Through quantitative results and qualitative observations, this study opens a broader conversation about AI's role in shaping personal agency and identity.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A Stanford University "misinformation expert" has been accused of using artificial intelligence (AI) to craft testimony later used by Minnesota Attorney General Keith Ellison in a politically-charged case. Jeff Hancock, a professor of communications and founder of the vaunted school's Social Media Lab, provided an expert declaration in a case involving a satirical conservative YouTuber named Christopher Kohls. The court case is about Minnesota's recent ban on political deepfakes, which the plaintiffs argue is an attack on free speech.

Deceptive reviews are becoming increasingly common, especially given the increase in performance and the prevalence of LLMs. While work to date has addressed the development of models to differentiate between truthful and deceptive human reviews, much less is known about the distinction between real reviews and AI-authored fake reviews. Moreover, most of the research so far has focused primarily on English, with very little work dedicated to other languages. In this paper, we compile and make publicly available the MAiDE-up dataset, consisting of 10,000 real and 10,000 AI-generated fake hotel reviews, balanced across ten languages. Using this dataset, we conduct extensive linguistic analyses to (1) compare the AI fake hotel reviews to real hotel reviews, and (2) identify the factors that influence the deception detection model performance. We explore the effectiveness of several models for deception detection in hotel reviews across three main dimensions: sentiment, location, and language. We find that these dimensions influence how well we can detect AI-generated fake reviews.

Far from the palm trees of Miami or Austin's taco trucks, Catalin Voss has headquartered his literacy start-up between a cannabis club and pawn shop in the heart of the Mission District. Voss rents a nondescript office building in one of San Francisco's most vibrant neighborhoods as a home base for Ello, a company he co-founded in 2020 that uses speech recognition technology, powered by artificial intelligence, to help struggling students develop their reading skills. The office is within walking distance of his Noe Valley apartment and only steps away from some of the city's best taquerias and cocktail bars. And those are just a few of the perks he recited in explaining why he is headquartered in San Francisco. Voss is part of a sizable cohort of San Francisco loyalists -- old and new -- who say they are flummoxed by the "all is lost" narrative propagated by conservative media hosts and more recently a vocal contingent of tech leaders that includes billionaire entrepreneur-turned-agitator Elon Musk.

The Daily Mail would be horrified if it knew what it had spawned. Back in 2021, when news broke of Matt Hancock's lockdown-breaking affair, the tabloid printed a floorplan of the health secretary's office, complete with details such as "queen painting" and "kiss door". For most people, it was unnecessary detail added to one of the most nauseating moments in modern politics. But for Dan Douglas, a 39-year-old from London, it served as artistic inspiration. "It reminded me of a map from a video game," he says.

In this work, we propose a family of novel quantum kernels, namely the Hierarchical Aligned Quantum Jensen-Shannon Kernels (HAQJSK), for un-attributed graphs. Different from most existing classical graph kernels, the proposed HAQJSK kernels can incorporate hierarchical aligned structure information between graphs and transform graphs of random sizes into fixed-sized aligned graph structures, i.e., the Hierarchical Transitive Aligned Adjacency Matrix of vertices and the Hierarchical Transitive Aligned Density Matrix of the Continuous-Time Quantum Walk (CTQW). For a pair of graphs to hand, the resulting HAQJSK kernels are defined by measuring the Quantum Jensen-Shannon Divergence (QJSD) between their transitive aligned graph structures. We show that the proposed HAQJSK kernels not only reflect richer intrinsic global graph characteristics in terms of the CTQW, but also address the drawback of neglecting structural correspondence information arising in most existing R-convolution kernels. Furthermore, unlike the previous Quantum Jensen-Shannon Kernels associated with the QJSD and the CTQW, the proposed HAQJSK kernels can simultaneously guarantee the properties of permutation invariant and positive definiteness, explaining the theoretical advantages of the HAQJSK kernels. Experiments indicate the effectiveness of the proposed kernels.

Over the past decade, technology and automotive pundits have predicted the "imminent" arrival of fully autonomous vehicles that can drive on public roads without any active monitoring or input from a human driver. Elon Musk has predicted his company Tesla would deliver fully autonomous vehicles by the end of 2021, but he made similar predictions in 2020, 2019, and 2017. Each prediction has fallen flat, largely due to real-world safety concerns, particularly related to how self-driving cars perform in adverse conditions or situations. Despite such proclamations from Tesla, which released its optimistically named Full Self Driving capability for AutoPilot in October 2021, fully automated self-driving cars have not yet arrived. Instead, most manufacturers are offering systems that feature capabilities that generally fall within the first three of the six levels of autonomy defined by the Society of Automotive Engineering (SAE), which range from Level 0 (no driving automation) to Level 5 (full self-driving capabilities under all conditions).

The NHS is set to receive a £36m injection to bolster its AI capabilities across 38 new projects designed to make diagnoses faster. While the NHS has been handling the Covid-19 pandemic, concerns over a diagnoses backlog have emerged, with people more hesitant to go to the GP or hospital for check-ups. The new technology will help detect cancers and provide mental health support and form part of the NHS AI Lab's £140m AI in Health and Care award money pot – which will be dished out over three years. Chief executive of NHS England, Simon Stevens, said: "As the NHS comes through the pandemic, rather than a return to old ways, we're supercharging a more innovative future. "So today our message to developers worldwide is clear – the NHS is ready to help you test your innovations and ensure our patients are among the first in the world to benefit from new AI technologies."

The NHS is set to receive millions of pounds for artificial intelligence upgrades as it works to clear a backlog of millions of cancer patients. It comes after Health Secretary Matt Hancock admitted'some cancer treatment had to stop' and couldn't rule out having to cancel operations again if coronavirus cases surged. The NHS is working to clear a backlog of potentially millions of patients after either operations were cancelled or people were deterred from going to hospital as the UK entered lockdown. Cancer Research UK said as a result of the pandemic there were 2.4 million patients waiting for cancer screening, further treatment or treatment at the end of May. But the Government said a £50 million funding boost to three digital pathology centres, based in London, Coventry and Leeds, would now lead to a'faster and more accurate' diagnosis for millions of cancer patients.

The COVID-19 public health crisis is enriching a murky nexus of technology surveillance firms linked to senior Government officials – at the expense of people's lives. The financial adventures of a former MI5 spymaster and the medical fantasies of Boris Johnson's top advisor point toward an unnerving endgame: an artificially intelligent (AI) corporate super-state, with a special focus on NHS genetic research inspired by eugenics. The tale begins with Britain's security services – and ends with Dominic Cummings. It uncovers the extent to which democracy and public health are now under threat from a series of Government failures rooted in a bankrupt ideology, influenced by the modern relics of scientific racism. On Sunday 12 April, the Government announced that the NHS would be launching a new COVID-19 contact tracing app.