Machine learning-based behavioral models rely on features extracted from audio-visual recordings. The recordings are processed using open-source tools to extract speech features for classification models. These tools often lack validation to ensure reliability in capturing behaviorally relevant information. This gap raises concerns about reproducibility and fairness across diverse populations and contexts. Speech processing tools, when used outside of their design context, can fail to capture behavioral variations equitably and can then contribute to bias. We evaluate speech features extracted from two widely used speech analysis tools, OpenSMILE and Praat, to assess their reliability when considering adolescents with autism. We observed considerable variation in features across tools, which influenced model performance across context and demographic groups. We encourage domain-relevant verification to enhance the reliability of machine learning models in clinical applications.

The annual meeting of the International Society for Autism Research took place in Seattle this week. The field's premiere scientific conference was scheduled to be held in the Emerald City five years ago, until COVID-19 dashed those plans. This time, U.S. autism researchers face a very different kind of crisis: massive cuts to federal funding, Cabinet members making false statements about the complex neurological condition they study, and a series of confusing and potentially worrisome policy announcements about autism research. In April, the U.S. Department of Health and Human Services disclosed that it's planning a 50-million "comprehensive research effort aimed at understanding the causes of [autism spectrum disorder] and improving treatments," a department spokesperson said. The effort was spurred by Secretary Robert F. Kennedy Jr.'s stated goal of determining the cause of autism, a neurological and developmental condition whose symptoms cluster around challenges with communication, social interaction and sensory processing.

Previous work has observed how Neurodivergence is often harmfully pathologized in Human-Computer Interaction (HCI) and Human-Robot interaction (HRI) research. We conduct a review of autism robot reviews and find the dominant research direction is Autistic people's second to lowest (24 of 25) research priority: interventions and treatments purporting to 'help' neurodivergent individuals to conform to neurotypical social norms, become better behaved, improve social and emotional skills, and otherwise 'fix' us -- rarely prioritizing the internal experiences that might lead to such differences. Furthermore, a growing body of evidence indicates many of the most popular current approaches risk inflicting lasting trauma and damage on Autistic people. We draw on the principles and findings of the latest Autism research, Feminist HRI, and Robotics to imagine a role reversal, analyze the implications, then conclude with actionable guidance on Autistic-led scientific methods and research directions.

Imagine activating new robots meant to aid staff in an elder care facility, only to discover the robots are counterproductive. They undermine the most meaningful moments of the jobs and increase staff workloads, because robots demand care too. Eventually, they're returned. This vignette captures key elements of James Adrian Wright's ethnography, "Robots Won't Save Japan", an essential resource for understanding the state of elder care robotics. Wright's rich ethnographic interviews and observations challenge the prevailing funding, research, and development paradigms for robotics. Elder care residents tend to be Disabled, so this review article augments Wrights' insights with overlooked perspectives from Disability and Robotics research. This article highlights how care recipients' portrayal suggests that Paro, a plush robot seal, might perform better than the care team and author indicated -- leading to insights that support urgent paradigm shifts in elder care, ethnographic studies, and robotics. It presents some of the stronger technical status quo counter-arguments to the book's core narratives, then confronts their own assumptions. Furthermore, it explores exceptional cases where Japanese and international roboticists attend to care workers and recipients, justifying key arguments in Wright's compelling book. Finally, it addresses how "Robots won't save Japan" will save Robotics.

Autism is a serious developmental disorder that impairs the ability to communicate and interact. Autism spectrum disorder impacts the nervous system and affects the overall cognitive, emotional, social and physical health of the affected individual. According to a new study from the Stanford University School of Medicine, brain organisation differs between boys and girls with autism. The study was published in'The British Journal of Psychiatry'. The differences, identified by analyzing hundreds of brain scans with artificial intelligence techniques, were unique to autism and not found in typically developing boys and girls.