The number of sick and disabled people out of work is putting the UK is at risk of an economic inactivity crisis that threatens the country's prosperity, according to a new report. There were 800,000 more people out of work now than in 2019 due to health conditions, costing employers £85bn a year, according to the review by former John Lewis boss Sir Charlie Mayfield. The problem could worsen without intervention, but Sir Charlie, who will lead a taskforce aimed at helping people return to work, said this was not inevitable. The move has been broadly welcomed, but some business groups said Labour's Employment Rights Bill included some disincentives to hiring people with existing illnesses. One in five working age people were out of work, and not seeking work, according to the report, which was commissioned by the Department for Work and Pensions by produced independently.

AI has the potential to empower everyone to become more independent and self-sufficient. The increasing use of artificial intelligence (AI)-based technologies in everyday settings creates new opportunities to understand how disabled people might use these technologies [Glazko, 2023]. It also enables the development of new types of assistive technologies as well as new ways for people with disabilities to interact with technology in ways that are both simpler (for those who need things simpler) and more efficient and effective for those who cannot use the traditional interfaces effectively. AI has been rapidly taken up in almost all accessibility communities [Adnin 2024, Alharbi 2024, Jiang 2024, Bennett 2024, Valencia 2023]. Since becoming widely available to the public, Generative Artificial Intelligence (GAI) has steadily gained recognition for its potential as a valuable tool in the private sector and by government, as well as a tool for accessibility. Studies of blind and visually impaired individuals have found that they use GAI to'offload' cognitively demanding tasks and obtain personal help such as fashion advice (e.g., [Xie 2024]), and to create content or retrieve information [Adnin 2024]. A study of GAI use by neurodiverse users found GAI can both support and complicate tasks like code-switching, emotional regulation, and accessing information [Glazko, 2025]. A study of people who use AAC found it helpful for text input [Valencia 2023]. However there are concerns with a technology that is often based on probability and thus tends toward the most common case rather than those at the margins.

First and foremost, do no harm: algorithms that put a subset of the population at risk should not be deployed. This requires regulatory intervention, algorithmic research (for example, developing better algorithms for handling outliers)9 and applications research (for example, studying the risks that applications might create for disabled people). We must consider "the context in which such technology is produced and situated, the politics of classification, and the ways in which fluid identities are (mis)reflected and calcified through such technology."11 The most important step in avoiding this potential harm is to change who builds, regulates, and deploys AI-based systems. We must ensure disabled people contribute their perspective and expertise to the design of AI-based systems.

Data are the medium through which individuals' identities and experiences are filtered in contemporary states and systems, and AI is increasingly the layer mediating between people, data, and decisions. The history of data and AI is often one of disability exclusion, oppression, and the reduction of disabled experience; left unchallenged, the current proliferation of AI and data systems thus risks further automating ableism behind the veneer of algorithmic neutrality. However, exclusionary histories do not preclude inclusive futures, and disability-led visions can chart new paths for collective action to achieve futures founded in disability justice. This chapter brings together four academics and disability advocates working at the nexus of disability, data, and AI, to describe achievable imaginaries for artificial intelligence and disability data justice. Reflecting diverse contexts, disciplinary perspectives, and personal experiences, we draw out the shape, actors, and goals of imagined future systems where data and AI support movement towards disability justice.

I was headed headed west on 3rd Street from a mid-city senior center with 89-year-old Julie Finger, who showed no sign of fear. Our ride wasn't just any old car; it was a fully loaded electric Jaguar, and among other details worth sharing, one in particular stands out. Are you the least bit nervous? "No," she said with a giggle. Our robotaxi service was Waymo, the Google autonomous vehicle company that has fleets in San Francisco and Phoenix and began limited service in Los Angeles this spring in a 63-square-mile area between downtown L.A. and the beach. California is about to be hit by an aging population wave, and Steve Lopez is riding it.

Recent advancements in image generation technology have enabled widespread access to AI-generated imagery, prominently used in advertising, entertainment, and progressively in every form of visual content. However, these technologies often perpetuate societal biases. This study investigates the representation biases in popular image generation models towards people with disabilities (PWD). Through a comprehensive experiment involving several popular text-to-image models, we analyzed the depiction of disability. The results indicate a significant bias, with most generated images portraying disabled individuals as old, sad, and predominantly using manual wheelchairs. These findings highlight the urgent need for more inclusive AI development, ensuring diverse and accurate representation of PWD in generated images. This research underscores the importance of addressing and mitigating biases in AI models to foster equitable and realistic representations.

Until recently, in all of human history, the number of true cyborgs stood at about 70. Ian Burkhart has kept a count because he was one of them--a person whose brain has been connected directly to a computer. Burkhart had become quadriplegic in a swimming accident after a wave ran him into a sandbar and injured his spine. He was later able to receive an implant from a research study, which allowed him to temporarily regain some movement in one hand. For seven and a half years, he lived with this device--an electrode array nestled into his motor cortex that transmitted signals to a computer, which then activated electrodes wrapped around his arm.

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.

In 2010, Barack Obama signed the Plain Writing Act into law, requiring that federal government documents use clear, straightforward language. Plain-language documents serve a dual purpose: they can make information more accessible to people with disabilities that affect cognition and memory, but also address the fact that legislation is already complicated for most people to read--a case in point of how accessibility practices benefit even those without a particular disability. New Disabled South, a disability justice nonprofit founded in 2022, is trying to make more information available to disabled people on legislation that affects them, launching its Plain Language Policy Dashboard in November to cover 14 Southern states. As of now, the bills it explains fall into six categories: accessibility, civil rights, criminalization, poverty and care, democracy, and education. Dom Kelly, New Disabled South's CEO, told me that he hopes the dashboard--which uses AI to translate texts into plain language, which is then checked for accuracy--can also help "combat myths and disinformation" that spread on social media, like whether a mental health–related bill could actually lead to more institutionalization.

People in Texas sounded off on AI job displacement, with half of people who spoke to Fox News convinced that the tech will rob them of work. The growing use of artificial intelligence will likely lead to biased and discriminatory outcomes for minorities and disabled people, several groups warned the federal government this week. The National Artificial intelligence Advisory Committee, an interagency group led by the Commerce Department, held a public hearing online Tuesday aimed at informing policymakers about how the government can best manage the use of AI. Panelists were told by most of the witnesses that bias and discrimination are the biggest fears for the people they represent. Patrice Willoughby, vice president of policy and legislative affairs at the NAACP, told panelists that technology has already been used as a means to disenfranchise and mislead voters, and said her group worries about AI for the same reason.