--From dating to job interviews, making new friends or simply chatting with the cashier at checkout, engaging in small talk is a vital, everyday social skill. For adults with Autism Spectrum Disorder (ASD), small talk can be particularly challenging, yet it is essential for social integration, building relationships, and accessing professional opportunities. In this study, we present our development and evaluation of an in-home autonomous robot system that allows users to practice small talk. Results from the week-long study show that adults with ASD enjoyed the training, made notable progress in initiating conversations and improving eye contact, and viewed the system as a valuable tool for enhancing their conversational skills. Imagine a scene where three coworkers are engaging in small talk at the beginning of their workday. One of them is Alex, who has Autism Spectrum Disorder (ASD), a neu-rodevelopmental condition that often makes it challenging to understand and interpret social cues [2]. Not bad... just trying to power through this Monday. How about you, Alex? A: Monday is okay. Anything exciting happen this weekend? B: Y eah, I finally tried that new restaurant. It was fantas-- A: I watched a movie. C: Glad you liked the restaurant, Ben. It's my kids' favorite spot these days... What movie did you watch, Alex? A: "The Martian." At first glance, this brief example of a typical interaction appears unremarkable. It represents the everyday small talk that occurs regularly in many workplaces. For workers with ASD, however, such apparently "easy" interactions may present a real challenge. In this example, while Alex responds to direct questions, the responses are brief and lack elaboration. Alex's responses provide minimal information rather than actively participating in the flow of the conversation. Additionally, Alex's lack of response to the last prompt may suggest difficulty in extending or sustaining the dialogue. Although workers with ASD are often highly trained and skilled in job-specific tasks, they frequently face challenges with social interactions in the workplace.

Small talk can foster rapport building in human-human teamwork; yet how non-anthropomorphic robots, such as collaborative manipulators commonly used in industry, may capitalize on these social communications remains unclear. This work investigates how robot-initiated small talk influences task performance, rapport, and interaction dynamics in human-robot collaboration. We developed an autonomous robot system that assists a human in an assembly task while initiating and engaging in small talk. A user study ($N = 58$) was conducted in which participants worked with either a functional robot, which engaged in only task-oriented speech, or a social robot, which also initiated small talk. Our study found that participants in the social condition reported significantly higher levels of rapport with the robot. Moreover, all participants in the social condition responded to the robot's small talk attempts; 59% initiated questions to the robot, and 73% engaged in lingering conversations after requesting the final task item. Although active working times were similar across conditions, participants in the social condition recorded longer task durations than those in the functional condition. We discuss the design and implications of robot small talk in shaping human-robot collaboration.

As foundation models increasingly permeate sensitive domains such as healthcare, finance, and mental health, ensuring their behavior meets desired outcomes and social expectations becomes critical. Given the complexities of these high-dimensional models, traditional techniques for constraining agent behavior, which typically rely on low-dimensional, discrete state and action spaces, cannot be directly applied. Drawing inspiration from robotic action selection techniques, we propose the grounded observer framework for constraining foundation model behavior that offers both behavioral guarantees and real-time variability. This method leverages real-time assessment of low-level behavioral characteristics to dynamically adjust model actions and provide contextual feedback. To demonstrate this, we develop a system capable of sustaining contextually appropriate, casual conversations ("small talk"), which we then apply to a robot for novel, unscripted interactions with humans. Finally, we discuss potential applications of the framework for other social contexts and areas for further research.

Beyond mere formality, small talk plays a pivotal role in social dynamics, serving as a verbal handshake for building rapport and understanding. For conversational AI and social robots, the ability to engage in small talk enhances their perceived sociability, leading to more comfortable and natural user interactions. In this study, we evaluate the capacity of current Large Language Models (LLMs) to drive the small talk of a social robot and identify key areas for improvement. We introduce a novel method that autonomously generates feedback and ensures LLM-generated responses align with small talk conventions. Through several evaluations -- involving chatbot interactions and human-robot interactions -- we demonstrate the system's effectiveness in guiding LLM-generated responses toward realistic, human-like, and natural small-talk exchanges.

Gone are the days of simply meeting people in the pub or through friends and when Hinge was merely a joint attached to a door. Instead, we're forced to swipe right endlessly to search for our soulmate. But with two million Brits estimated to be living with undiagnosed ADHD, being unlucky in love online could be a potential sign of the condition, new research suggests. Experts found over a fifth of singletons with the mental health condition are more likely to be feel overwhelmed by dating apps than non-ADHD daters. According to the probe, by dating app Hinge, three in four ADHD daters also report feeling misunderstood using them.

Rapport is known as a conversational aspect focusing on relationship building, which influences outcomes in collaborative tasks. This study aims to establish human-agent rapport through small talk by using a rapport-building strategy. We implemented this strategy for the virtual agents based on dialogue strategies by prompting a large language model (LLM). In particular, we utilized two dialogue strategies-predefined sequence and free-form-to guide the dialogue generation framework. We conducted analyses based on human evaluations, examining correlations between total turn, utterance characters, rapport score, and user experience variables: naturalness, satisfaction, interest, engagement, and usability. We investigated correlations between rapport score and naturalness, satisfaction, engagement, and conversation flow. Our experimental results also indicated that using free-form to prompt the rapport-building strategy performed the best in subjective scores.

VIRAL WORK TREND – "The big talk," a viral career trend, is taking place of the small talk of old as Gen-Zers and millennials focus on showing their vulnerability. 'LIFE AFTER POWER' – A bestselling author is revealing lessons from the life of William Howard Taft. 'MORAL TEACHINGS' – Kirk Cameron has announced a new TV series and says America's parents are "sickened" by woke Hollywood. "Adventures with Iggy and Mr. Kirk" will star Cameron as Mr. Kirk and Leigh-Allyn Baker, who will play the role of Creative Leigh. Iggy the Iguana will be puppeteered by John Kennedy, known for two decades of starring roles in shows like "Sesame Street" and "Muppets."

In this work, we investigate people's engagement and attitudes towards a non-anthropomorphic robot manipulator that initiates small talk with the user during a collaborative assembly task, and explore how the presence of negative team feedback may affect team dynamics and blame attribution. Through an exploratory study with 20 participants, we found that 18 individuals interacted socially with the robot, nine of which initiated questions back to the robot. We report the frequency and length of users' responses in task-oriented and non-task-oriented dialogue, and further elaborate on people's reactions to the negative system feedback and robot-initiated small talk. We discuss the potential for integrating small talk in non-social robots, and propose three design guidelines to enhance human-robot small talk interactions.

Earlier this spring, I took the bus to the Moscone Center, in downtown San Francisco, where almost thirty thousand people had gathered for the annual Game Developers Conference (G.D.C.), which I was attending as a journalist. I had spent the previous few months out on maternity leave, and I was glad to return to work, to have meetings, to temporarily exit the domestic sphere. Participating in public life felt incredible, almost psychedelic. I loved making small talk with the bus driver, and eavesdropping on strangers. "Conferences are back," I heard one man say, sombrely, to another.

Abstract: Chatbots, or bots for short, are multi-modal collaborative assistants that can help people complete useful tasks. Usually, when chatbots are referenced in connection with elections, they often draw negative reactions due to the fear of mis-information and hacking. Instead, in this paper, we explore how chatbots may be used to promote voter participation in vulnerable segments of society like senior citizens and first-time voters. In particular, we build a system that amplifies official information while personalizing it to users' unique needs transparently. We discuss its design, build prototypes with frequently asked questions (FAQ) election information for two US states that are low on an ease-of-voting scale, and report on its initial evaluation in a focus group. Our approach can be a win-win for voters, election agencies trying to fulfill their mandate and democracy at large.