Automatic Speech Recognition (ASR) transcription errors are commonly assessed using metrics that compare them with a reference transcription, such as Word Error Rate (WER), which measures spelling deviations from the reference, or semantic score-based metrics. However, these approaches often overlook what is understandable to humans when interpreting transcription errors. To address this limitation, a new evaluation is proposed that categorizes errors into four levels of severity, further divided into subtypes, based on objective linguistic criteria, contextual patterns, and the use of content words as the unit of analysis. This metric is applied to a benchmark of 10 state-of-the-art ASR systems on French language, encompassing both HMM-based and end-to-end models. Our findings reveal the strengths and weaknesses of each system, identifying those that provide the most comfortable reading experience for users.

In recent years, the rapid development of AI systems has brought about the benefits of intelligent services but also concerns about security and reliability. By fostering appropriate user reliance on an AI system, both complementary team performance and reduced human workload can be achieved. Previous empirical studies have extensively analyzed the impact of factors ranging from task, system, and human behavior on user trust and appropriate reliance in the context of one-step decision making. However, user reliance on AI systems in tasks with complex semantics that require multi-step workflows remains under-explored. Inspired by recent work on task decomposition with large language models, we propose to investigate the impact of a novel Multi-Step Transparent (MST) decision workflow on user reliance behaviors. We conducted an empirical study (N = 233) of AI-assisted decision making in composite fact-checking tasks (i.e., fact-checking tasks that entail multiple sub-fact verification steps). Our findings demonstrate that human-AI collaboration with an MST decision workflow can outperform one-step collaboration in specific contexts (e.g., when advice from an AI system is misleading). Further analysis of the appropriate reliance at fine-grained levels indicates that an MST decision workflow can be effective when users demonstrate a relatively high consideration of the intermediate steps. Our work highlights that there is no one-size-fits-all decision workflow that can help obtain optimal human-AI collaboration. Our insights help deepen the understanding of the role of decision workflows in facilitating appropriate reliance. We synthesize important implications for designing effective means to facilitate appropriate reliance on AI systems in composite tasks, positioning opportunities for the human-centered AI and broader HCI communities.

Large Language Models (LLMs) have revolutionized the process of customer engagement, campaign optimization, and content generation, in marketing management. In this paper, we explore the transformative potential of LLMs along with the current applications, future directions, and strategic recommendations for marketers. In particular, we focus on LLMs major business drivers such as personalization, real-time-interactive customer insights, and content automation, and how they enable customers and business outcomes. For instance, the ethical aspects of AI with respect to data privacy, transparency, and mitigation of bias are also covered, with the goal of promoting responsible use of the technology through best practices and the use of new technologies businesses can tap into the LLM potential, which help growth and stay one step ahead in the turmoil of digital marketing. This article is designed to give marketers the necessary guidance by using best industry practices to integrate these powerful LLMs into their marketing strategy and innovation without compromising on the ethos of their brand.

Apple has pulled a new iPhone feature released just three months ago after users slammed it for spreading misinformation. The tech giant removed its AI notification summaries for news and entertainment apps after the system falsely reported a news article. The summary of the BBC article suggested that Luigi Mangione, 26, the alleged assassin of the CEO of UnitedHealthcare, had shot himself. It read: 'Luigi Mangione shoots himself; Syrian mother hopes Assad pays the price; South Korea police raid Yoon Suk Yeol's office,' in reference to three articles that had supposedly been published by the BBC. Mangione has been accused of shooting Brian Thompson, 50, at point-blank range as he was walking to a Manhattan hotel where his company was holding an investor conference on December 4. He is currently being held in a Brooklyn federal jail.

A groundbreaking chatbot created in the 1960s has been painstakingly reconstructed from archived records and run for the first time in over half a century, as part of an effort to preserve one of the earliest examples of artificial intelligence. ELIZA was written by computer scientist Joseph Weizenbaum at MIT in just 420 lines of code. The AI model is extremely rudimentary in comparison to today's large language models (LLMs) like ChatGPT but wowed researchers at the time with…

AgiBot promises to reshape our understanding of robotic learning and adaptation. AgiBot, a pioneering Chinese artificial intelligence and robotics company, has introduced a transformative open-source dataset called AgiBot World Alpha. This comprehensive collection represents a significant milestone in humanoid robot training, capturing intricate data from over 100 robots across diverse real-world scenarios. By providing an unprecedented window into robotic movement and interaction, AgiBot has created a multidimensional resource that promises to reshape our understanding of robotic learning and adaptation. The AgiBot World Alpha dataset is more than a simple data collection.

Squid Game is not a subtle show. It is impossible to misinterpret its very obvious message that the games are bad, and people should NOT be driven to such desperation by a merciless capitalist system that they will murder each other for rich people's entertainment. I would not be the first to point out that there is some conflict in the fact that we, the viewers, are watching all these competitors get killed for our entertainment, but still: despite the violence, despite the shock value, there is no ambiguity around the narrative intention. In this spin-off video game from Netflix, by contrast, the games are not bad. They are supposed to be fun.

Jon Voight spoke to Fox News Digital while promoting his film "Reagan" and weighed in on the family drama between his daughter, Angelina Jolie, and her ex, Brad Pitt. A happily-ever-after with whom a woman assumed to be Hollywood hunk Brad Pitt quickly turned into a living nightmare. On Jan. 12, the French television channel TF1 aired an episode of its show "Sept à Huit," which told the story of a 53-year-old interior designer named Anne who revealed that she had lost 830,000 euros (approximately 850,000) in personal funds because she thought she was sending money to a cancer-ridden Pitt. Through falsified documents and images as well as artificial intelligence, Anne believed she was speaking to, and eventually in a relationship with, the 61-year-old actor. WHAT IS ARTIFICIAL INTELLIGENCE (AI)? A woman was conned into believing she was in a relationship with Brad Pitt after being contacted by someone claiming to be the actor on Instagram.

Keir Starmer this week announced a 50-point plan that aims to give the UK world leader status in artificial intelligence and grow the economy by as much as 47bn a year over a decade. The multibillion-pound investment, which seeks to create a 20-fold increase in the amount of AI computing power under public control by 2030, has been framed as a gamechanger for businesses and public organisations. The reaction to the announcement has been mixed, given it is far from clear that the much-hyped potential of AI will result in the level of economic benefit forecast. Many are concerned that the technology could lead to widespread job cuts, while others fear a destruction in the value and growth of the creative industries after learning of proposals to make it easier for AI companies to mine artistic works for data, for no cost. Despite such concerns, for many in the world of business the AI revolution is already here and transforming their industries.

Unmanned Aerial Vehicles (UAVs), commonly known as Drones, are one of 21st century most transformative technologies. Emerging first for military use, advancements in materials, electronics, and software have catapulted drones into multipurpose tools for a wide range of industries. In this paper, we have covered the history, taxonomy, architecture, navigation systems and branched activities for the same. It explores important future trends like autonomous navigation, AI integration, and obstacle avoidance systems, emphasizing how they contribute to improving the efficiency and versatility of drones. It also looks at the major challenges like technical, environmental, economic, regulatory and ethical, that limit the actual take-up of drones, as well as trends that are likely to mitigate these obstacles in the future. This work offers a structured synthesis of existing studies and perspectives that enable insights about how drones will transform agriculture, logistics, healthcare, disaster management, and other areas, while also identifying new opportunities for innovation and development.