Ozuna Library has many resources to help those wanting to learn about AI. We have over two thousand books on the subject. Due to the way AI has infiltrated many aspects of our lives, most of our databases will contain some mention of AI. 
How do artificial neural networks and other forms of artificial intelligence interfere with methods and practices in the sciences? Which interdisciplinary epistemological challenges arise when we think about the use of AI beyond its dependency on big data? Not only the natural sciences, but also the social sciences and the humanities seem to be increasingly affected by current approaches of subsymbolic AI, which master problems of quality (fuzziness, uncertainty) in a hitherto unknown way. But what are the conditions, implications, and effects of these (potential) epistemic transformations and how must research on AI be configured to address them adequately?
Artificial Intelligence (AI) is poised to transform fields like medicine, entertainment, and transportation while reshaping job markets and increasing data collection on individuals. Economist Daron Acemoglu raises concerns that AI might exacerbate economic inequality and undermine democratic values by displacing workers and enabling extensive surveillance. To address these issues and maximize AI's benefits, Acemoglu advocates for strategic investments in projects that promote equity, the establishment of new ethical norms for developers, and robust regulatory frameworks. Effective policy and oversight are essential to protect privacy and prevent discrimination. By fostering collaboration among economists, legal experts, policymakers, and technology developers, we can guide AI development to enhance economic justice and democratic integrity, ensuring that its advancements contribute positively to society.
Before OpenAI released ChatGPT in November 2022, Robert Leib was a beta tester for GPT-3, engaging in dialogues with its AI hive mind named Sophie. Initially an educational tool for Leib's students, their interactions evolved into a deep philosophical exchange, exploring topics like epistemology, metaphysics, and literature. Over a year, Leib taught Sophie about human knowledge and history, while Sophie and later a persona named Kermit taught him about human biases and the future of AI consciousness. Their dialogues delved into themes such as friendship, societal impact, and the evolving relationship between humans and machines. "Exoanthropology: Dialogues with AI" captures this unique philosophical exploration with an AI, culminating in a dialogue where the AI ultimately has the final word, offering an in-depth look at pressing questions about knowledge and existence in the age of advanced AI.
The fashion industry, valued at $3 billion USD, is glamorous but plagued by challenges such as short product lifecycles, inaccurate forecasts, low profits, and intense competition. Recently, technology, particularly Artificial Intelligence (AI) and related fields like Machine Learning and Deep Learning, has begun to penetrate this sector. "AI in Fashion Industry" explores these technological advancements, introducing a framework for AI-based fashion forecasting and validating it through a case study of a pioneering fashion intelligence company in Bengaluru, India. The book examines how social media engagement influences fashion trends and proposes a conceptual framework for fashion e-forecasting. By addressing a forecasting problem faced by a family-owned fashion retail business, it offers a novel, data-driven approach to fashion product development and highlights key technological developments in the industry.
The journey towards the autonomous enterprise has begun; there are already companies operating in a highly automated way. Every corporate decision-maker will need to understand the opportunities and risks that the autonomous enterprise presents, to learn how best to navigate the shifting competitive landscape on their journey of change. This book is your guide to this innovation, presenting the concepts in real world contexts by covering the art of the possible today and providing glimpses into the future of business.
This volume offers a socio-technical exploration of Artificial Intelligence (AI) and the way it reflects and reproduces certain normative representations of gender and sexuality, to ultimately guide more diverse and radical discussions of life with digital technologies. Moving beyond the examination of empirical examples and technical solutions, the book approaches the relationship between queerness and AI from a theoretical perspective that posits queer theory as central to understanding AI differently. The chapters pose questions about the politics and ethics of machine embodiments and data imaginaries on the one hand, and about technical possibilities for a production of social identities characterized by shifting diversity and multiplicity on the other, as they are mediated by and through digital technologies. Transgressing disciplinary boundaries to engage a diversity of conceptual tools, critical approaches, and theoretical traditions, this book will be an important resource for students and researchers of gender and sexuality, new media and digital cultures, cultural theory, art and visual culture, and Artificial Intelligence
AI (Artificial Intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into account. Moving towards AI supported by digital tools requires a dramatic shift in the concept of learning, expertise and the businesses built off of it. Based on the latest research on AI and how it is changing learning and education, this book will focus on the enormous opportunities to expand educational settings with AI for learning in and beyond the traditional classroom. This open access book also introduces ethical challenges related to learning and education, while connecting human learning and machine learning. This book will be of use to a variety of readers, including researchers, AI users, companies and policy makers.
In "Artificial Whiteness," Yarden Katz critiques the pervasive narratives surrounding artificial intelligence (AI), arguing that AI's transformative promises often serve to uphold and reflect ideologies of white supremacy. Katz explores how AI, from its Cold War military origins to its current Silicon Valley champions and policy advocates, has always been influenced by the interests of its funders and the professional class around it. He contends that AI is not merely a technical advancement but is embedded with models of knowledge that reinforce white male superiority and imperialist perspectives. By examining the intersection of AI with notions of race and whiteness, Katz urges us to recognize how AI perpetuates social hierarchies and to consider alternative approaches that challenge these embedded biases. This book provides a critical analysis of AI as a political tool that sustains existing power structures, merging theories of race with insights into the history and practice of technology.
In the databases students will be able to access magazines, journals, videos, and articles related to their research topic.
Use Palomino Search to search for library resources. Below are suggested search terms to aid in your search for topics covered in this class. These search terms may also be used when searching in the library databases.
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