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"Artificial intelligence -- Popular works"
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The singularity : could artificial intelligence really out-think us (and would we want it to)?
This volume represents the combination of two special issues of the Journal of Consciousness Studies on the topic of the technological singularity. Could artificial intelligence really out-think us, and what would be the likely repercussions if it could? Leading authors contribute to the debate, which takes the form of a target chapter by philosopher David Chalmers, plus commentaries from the likes of Daniel Dennett, Nick Bostrom, Ray Kurzweil, Ben Goertzel, Frank Tipler, among many others. Chalmers then responds to the commentators to round off the discussion.
eBook
Machines Behaving Badly
Artificial intelligence is an essential part of our lives – for better or worse. It can be used to influence what we buy, who gets shortlisted for a job and even how we vote. Without AI, medical technology wouldn't have come so far, we'd still be getting lost on backroads in our GPS-free cars, and smartphones wouldn't be so, well, smart. But as we continue to build more intelligent and autonomous machines, what impact will this have on humanity and the planet? Professor Toby Walsh, a world-leading researcher in the field of artificial intelligence, explores the ethical considerations and unexpected consequences AI poses – Is Alexa racist? Can robots have rights? What happens if a self-driving car kills someone? What limitations should we put on the use of facial recognition? Machines Behaving Badly is a thought-provoking look at the increasing human reliance on robotics and the decisions that need to be made now to ensure the future of AI is as a force for good, not evil.
eBook
Artificial Intelligence and Images Portraying Nurses Through the Decades
Since the middle of the 20th century, the public image of nurses has undergone significant transformation. Shifts in social and gender norms, media portrayal of stereotypes, and evolving healthcare roles for nurses have all contributed to the public perception of nursing. With technological advancements and the explosion of generative artificial intelligence (GAI), images of nurses can now be created in seconds with text-to-image generators; however, these images may contain biases and stereotypes which can lead to continued misperceptions which potentially harm the nursing profession. The purpose of this research study was to empirically and systematically examine GAI images of nurses (n = 288) from three AI image generators using quantitative content analysis. Statistically significant differences were found between the three image generators regarding gender, ethnic diversity, and the sexualization of nurses in images. The study findings highlight the need for critical evaluation of AI-generated imagery to address biases and stereotypes, with implications for leveraging AI technologies responsibly to promote an accurate and diverse representation of the contemporary nursing profession.
Journal Article
Living with robots : what every anxious human needs to know
The truth about robots: two experts look beyond the hype, offering a lively and accessible guide to what robots can (and can't) do. The authors discuss the history of our fascination with robots - from chatbots and prosthetics to autonomous cars and robot swarms.
Book
Robot Futures
A roboticist imagines life with robots that sell us products, drive our cars, even allow us to assume new physical form, and more. With robots, we are inventing a new species that is part material and part digital. The ambition of modern robotics goes beyond copying humans, beyond the effort to make walking, talking androids that are indistinguishable from people. Future robots will have superhuman abilities in both the physical and digital realms. They will be embedded in our physical spaces, with the ability to go where we cannot, and will have minds of their own, thanks to artificial intelligence. In Robot Futures , the roboticist Illah Reza Nourbakhsh considers how we will share our world with these creatures, and how our society could change as it incorporates a race of stronger, smarter beings. Nourbakhsh imagines a future that includes adbots offering interactive custom messaging; robotic flying toys that operate by means of “gaze tracking”; robot-enabled multimodal, multicontinental telepresence; and even a way that nanorobots could allow us to assume different physical forms. Nourbakhsh examines the underlying technology and the social consequences of each scenario. He also offers a counter-vision: a robotics designed to create civic and community empowerment. His book helps us understand why that is the robot future we should try to bring about.
eBook
Research on the Path and Effectiveness of Youngor Group’s Intelligent Transformation
Artificial intelligence (AI) is revolutionizing industries by enhancing efficiency and optimizing labor. For apparel manufacturing, AI addresses critical challenges in productivity, personalization, and digital transformation. This study analyzes Youngor Group’s intelligent transformation (2015–2021) through case studies, financial data, and innovation assessments. Key findings show: Production: Smart factories with AI task allocation and MES systems reduced customization cycles by 67%, increased per-worker output by 27.8%, and achieved 100% mass customization capacity.Marketing: 3D body scanning and 5G+AR virtual fitting improved customer profiling accuracy by 40%, while integrated online-offline strategies drove 11% annual revenue growth. Innovations like digital twin workshops, smart logistics, and immersive retail spaces strengthened supply chain flexibility and consumer engagement. However, cross-departmental data silos lowered collaboration efficiency by 15%, and R&D investment remained below 3% of total expenditure, reflecting talent gaps. The study concludes that apparel firms must prioritize intelligent production as the cornerstone, adopt phased technology integration, and invest in data governance and cross-disciplinary talent. While offering a framework for traditional manufacturing transformation, the research highlights limitations in generalizing single-case results, advocating future multi-industry comparisons for broader validation.
Journal Article