The growing development of robots with artificial emotional expressiveness raises important questions about their persuasive potential in children's behavior. While research highlights the pragmatic value of emotional expressiveness in human social communi cation, the extent to which robotic expressiveness can or should influence empathic responses in children is grounds for debate. In a pilot study with 22 children (aged 7 - 11) we begin to explore the ways in which different levels of embodied expressiveness (body only, face only, body and face) of two basic emotions (happiness and sadness) displayed by an anthropomorphic robot (QTRobot) might modify children's behavior in a child - robot cooperative turn - taking game. We observed that children aligned their beh avior to the robot's inferred emotional state. However, higher levels of expressiveness did not result in increased alignment. The preliminary results reported here provide a starting point for reflecting on robotic expressiveness and its role in shaping c hildren's social - emotional behavior toward robots as social peers in the near future .

Robots are fast becoming a part of everyday life. Indeed, robots are now deployed in retail stores (see Figure 1), warehouses, hospitals, factories, and so on to perform tasks conventionally done by humans. Nestlé uses a humanoid robot "Pepper" to sell coffee makers in department stores in Japan; people buy ice cream from a fully automated ice cream franchise, RoboFusion; Cobalt's KnightScope security robots patrol streets in New York City. Such encounters will only increase as the global market for service robots has grown exponentially, from 36.2 billion in 2022 to 103.3 billion by 2026.26 Humanoid'Pepper' has been deployed in many retail stores throughout Japan.20 According to a survey from McKinsey Global Institute, 15% of the global workforce, or 400 million workers, will be displaced by 2030.14

When a gait of a bipedal robot is developed using deep reinforcement learning, reference trajectories may or may not be used. Each approach has its advantages and disadvantages, and the choice of method is up to the control developer. This paper investigates the effect of reference trajectories on locomotion learning and the resulting gaits. We implemented three gaits of a full-order anthropomorphic robot model with different reward imitation ratios, provided sim-to-sim control policy transfer, and compared the gaits in terms of robustness and energy efficiency. In addition, we conducted a qualitative analysis of the gaits by interviewing people, since our task was to create an appealing and natural gait for a humanoid robot. According to the results of the experiments, the most successful approach was the one in which the average value of rewards for imitation and adherence to command velocity per episode remained balanced throughout the training. The gait obtained with this method retains naturalness (median of 3.6 according to the user study) compared to the gait trained with imitation only (median of 4.0), while remaining robust close to the gait trained without reference trajectories.

With the rapid advancement of Artificial Intelligence (AI) technology, robots equipped with Artificial Intelligence (AI) are becoming more sophisticated and capable. Neurons are like hardware and the brain is like software. People often compare the human brain to a computer. The growth of artificial intelligence and the advent of anthropomorphic robots make this metaphor even more beautiful to look at. However, Lisa Feldman-Barrett, a professor of psychology at Northeastern University in the United States, believes this similarity is problematic and may lead to misconceptions.

Recently, I was walking in a little park in downtown Mountain View, right in the heart of Silicon Valley, when I saw something unexpected. They were little robots, well little "automated carts", really, with a flag on top and there were a few of them lined up near the library. Every now and then, one of them would leave the line and navigate the sidewalks and crosswalks of downtown. Being in what is essentially ground zero of Silicon Valley, I guess I shouldn't have been that surprised. When I moved to Mountain View in 2007, I remember being surprised at seeing Google's fleet of autonomous cars driving around (now called Waymo). This was a precursor to the boom in self-driving car companies that happened over the past decade, and which has yet not quite borne fruit.

Philip K. Dick was living a few miles north of San Francisco when he wrote Do Androids Dream of Electric Sheep?, which envisioned a world where artificially intelligent androids are indistinguishable from humans. The Turing Test has been passed, and it's impossible to know who, or what, to trust. A version of that world will soon be a reality in San Francisco. Google announced this week that Duplex, the company's phone-calling AI, will be rolled out to Pixel phones in the Bay Area and a few other US cities before the end of the year. You might remember Duplex from a shocking demonstration back in May, when Google showed how the software could call a hair salon and book an appointment.

In 2010, a group of students and faculty members at Carnegie Mellon University in Doha, Qatar, introduced their campus to Hala, the latest in a line of what the school termed "roboceptionists." Consisting of a truncated torso and an LCD screen featuring a blue-skinned female CGI head, Hala was designed to provide students and visitors with instructions, directions, and anecdotes in either formal Arabic or American English. In addition to educating visitors about Qatar, Hala's purpose was to explore human-robot interaction (HRI) in a multicultural setting. The population of Doha is a demographic mosaic; the city is primarily inhabited by expatriates from all over the world (most of whom speak Arabic and/or English). Because of this relative diversity, Hala interacted with visitors from a slew of countries, using features like natural language understanding and facial expressions to conduct, in Carnegie Mellon's words, "culturally appropriate" exchanges.

Everybody knows that anthropomorphic robots that try to look and act like people are creepy. There's been a bunch of research into just what it is about such androids that we don't like (watch the video below to get an idea of what we're talking about), and many researchers think that we get uncomfortable when we begin to lose the ability to confidently distinguish between what's human and what's not. This is why zombies are often placed at the very bottom of the Uncanny Valley: in many respects, they directly straddle that line, which is why they freak us out so much. The tricky part about robots, however, is that they can manifest "human-ness" in ways that are more than just physical. When robots start acting like humans, as opposed to just looking like them, things can get much more complicated.