Large Language Models (LLMs) increasingly exhibit \textbf{anthropomorphism} characteristics -- human-like qualities portrayed across their outlook, language, behavior, and reasoning functions. Such characteristics enable more intuitive and engaging human-AI interactions. However, current research on anthropomorphism remains predominantly risk-focused, emphasizing over-trust and user deception while offering limited design guidance. We argue that anthropomorphism should instead be treated as a \emph{concept of design} that can be intentionally tuned to support user goals. Drawing from multiple disciplines, we propose that the anthropomorphism of an LLM-based artifact should reflect the interaction between artifact designers and interpreters. This interaction is facilitated by cues embedded in the artifact by the designers and the (cognitive) responses of the interpreters to the cues. Cues are categorized into four dimensions: \textit{perceptive, linguistic, behavioral}, and \textit{cognitive}. By analyzing the manifestation and effectiveness of each cue, we provide a unified taxonomy with actionable levers for practitioners. Consequently, we advocate for function-oriented evaluations of anthropomorphic design.

Robots, AI and autonomous systems are increasingly being used in hospitals around the world. They help with a range of tasks, from surgical procedures and taking vital signs to helping out with security. Such "medical robots" have been shown to help increase precision in surgeries and even reduce human error in drug delivery through their automated systems. Their deployment into care homes has also shown they have the capability to help reduce loneliness. Many people will be familiar with the smiling face of the Japanese Pepper robots (billed in 2014 as the world's first robot that reads emotions).

I've been writing a few articles in the last months where I've tackled the subject of artificial intelligence (AI) and its incorporation into digital business processes and our daily life. As I was carrying out my search, I came across some resources about the usage of AI to produce art, like painting and music. By letting machines learn from the human artistic work, Artificial Intelligence Virtual Artists like AIVA can compose classical and symphonic music. Today, AIVA's YouTube channel has over 18K subscribers. In her post "Top 10 AI Music Composers in 2021," Lisa Brown has listed more examples of non-human music composers.

The concept of artificial intelligence has provided fodder for science fiction writers for decades. Today, narratives that we will soon see a malevolent super-intelligence like Skynet from "Terminator" have become commonplace. But a dark future with a fight against monsters like the Terminator seems a bit far-fetched. Yet if you've been reading up on artificial intelligence recently, you've come across plenty of myths almost as scary as the Terminator: All our jobs are going to disappear! Robots are going to take over our business activities!

Human moving path is an important feature in architecture design. By studying the path, architects know where to arrange the basic elements (e.g. structures, glasses, furniture, etc.) in the space. This paper presents SimArch, a multi-agent system for human moving path simulation. It involves a behavior model built by using a Markov Decision Process. The model simulates human mental states, target range detection, and collision prediction when agents are on the floor, in a particular small gallery, looking at an exhibit, or leaving the floor. It also models different kinds of human characteristics by assigning different transition probabilities. A modified weighted A* search algorithm quickly plans the sub-optimal path of the agents. In an experiment, SimArch takes a series of preprocessed floorplans as inputs, simulates the moving path, and outputs a density map for evaluation. The density map provides the prediction that how likely a person will occur in a location. A following discussion illustrates how architects can use the density map to improve their floorplan design.

Year after year, blockbuster films are replete with Turing-test-passing examples of AI -- and this past year was no exception. From Blade Runner 2049 to Marjorie Prime to Star Wars: The Last Jedi, it seems the public's appetite for depictions of truly intelligent AI is insatiable. This tendency to dream of overly optimistic futures when it comes to technology is hardly relegated to the movies. In 2016, publications including Wired, Forbes, and, yes, VentureBeat, eagerly predicted a year where "machines will win" and AI will spark "the beginning of a new internet." However, while there have been massive advances in AI this year, particularly in semantic recognition, the future the media predicted is far from realized.

Three men deliver an endless assault of kicks as the victim lies motionless on the grass. With venom in their eyes, one of the perpetrators delivers a crushing blow with a wooden bat. Another gets down on his knees and delivers a flurry of fists. Plastic parts and microchips are strewn across the ground. So goes the scene in Mike Judge's cult classic film Office Space, which is a cathartic release from the constant indignities of the modern worker.

Robert Morley, chief operating officer at Excello Law, examines the use of AI in the legal industry. Alongside Brexit and Donald Trump, artificial Intelligence (AI) kept headline writers working overtime in 2016 – each competing for our attention in a world of increasing uncertainty. Online, a clear winner has emerged from this unlikely trio of scary topics: AI returns nearly two billion results in Google search, whereas'The Donald' scores a more modest 368 million and Brexit a mere 108 million. Among articles and blogs about the future of law firms, AI has similarly dominated attention as the number one theme. Underpinned by dystopian visions of lawyers being replaced by robots and the growing ranks of tech companies dedicated to replacing the human element from much of day-to-day legal practice, the future for the lawyer has seemed bleak.

Students mostly couldn't tell'Jill Watson' wasn't human; 'Yep!' One day in January, Eric Wilson dashed off a message to the teaching assistants for an online course at the Georgia Institute of Technology. "I really feel like I missed the mark in giving the correct amount of feedback," he wrote, pleading to revise an assignment. Thirteen minutes later, the TA responded. "Unfortunately, there is not a way to edit submitted feedback," wrote Jill Watson, one of nine assistants for the 300-plus students. Last week, Mr. Wilson found out he had been seeking guidance from a computer.