Artificial Intelligence
Explore curated Artificial Intelligence (AI) resources, including articles, books, and databases. This guide helps you understand AI principles, stay updated, and apply AI techniques in research. Whether you're new or experienced, these resources support your learning in this transformative field.
What is Artificial Intelligence (AI)?
Artificial intelligence. (2018). In P. Lagasse & Columbia University, The Columbia Encyclopedia (8th ed.). Columbia University Press. https://search.credoreference.com/articles/Qm9va0FydGljbGU6NjM5MDI3?aid=96765
Glossary of Terms
Prompt Engineering
According to Britannica, prompt engineering is a "process of designing inputs for generative artificial intelligence (AI) models to deliver useful, accurate, and relevant responses" (Comstock, 2024).
Student Resources
A Student Guide to Navigating College in the Artificial Intelligence Era by 
Citing AI
Teaching & Learning AI
Full Playlist Available at: AI by Laura Otero, Ph.D.
AI Detection Research & Tools
**These detection tools are not endorsed but are a selection of available options. They should not be the only method for identifying AI usage, but they should complement other educational and instructional approaches.**
This tool is designed to detect AI-generated images produced by platforms such as Stable Diffusion, MidJourney, DALL-E, GAN, and generated faces. It focuses on identifying specific characteristics and patterns associated with these AI image-generation models. If you would like more details, you can check the source. (Privacy Policy)
Detect GPT is a Chrome extension that analyzes online page content to determine if AI generated it. It displays a colored icon indicating whether the content is AI-generated and allows users to paste text into a form for authenticity checks. This tool aids in verifying the originality of written content. (Privacy Policy)
This site features software for AI proctoring during online exams. (Privacy Policy)
Is it an AI or a human artist that created your image? Detect AI generated images, synthetic, tampered images and Deepfake. (Privacy Policy)
Originality claims to be the most accurate content detection tool for AI-generated text, covering models like ChatGPT, GPT-2, GPT-3, and GPT-4, as well as Bard. It also features paraphrase detection, making it unique in the market. (Privacy Policy)
QuillBot's AI text detector flags content with characteristics like repetitive words, awkward phrasing, and unnatural flow for further inspection. This feature helps identify AI-generated text by highlighting these common indicators of AI writing. (Privacy Policy)
Start detecting AI-generated content immediately without creating an account. You can perform unlimited AI content checks for free, ensuring the authenticity of your work. This accessibility makes it easy to verify your text and maintain academic integrity. (Privacy Policy)
Turnitin is a widely used plagiarism detection tool that evaluates written content for originality by comparing it against a vast database. It helps educators ensure academic integrity by identifying potential instances of copying and providing feedback for students to improve their writing skills. (Privacy Policy)
For more information on Turnitin, visit: https://www.lmunet.edu/ctle/faculty/faq
Rated the #1 AI Detector by Forbes, this tool checks if your text is flagged as AI-generated. Its AI text humanizer enhances your writing to match human quality, and clicking "humanize" helps bypass AI detection. (Privacy Policy)
Evaluate your text using this detector to determine if adjustments are needed before publishing. It helps ensure your content meets quality standards and reduces the risk of being flagged as AI-generated. (Privacy Policy)
ZeroGPT is a free tool that detects whether text is generated by AI, like ChatGPT, or written by humans, including mixed content. Utilizing DeepAnalyse™ Technology, it claims an accuracy rate of over 98%. This tool can help users assess the originality of their writing before publishing. (Privacy Policy)
Books
Artificial Era: predictions, problems, and diversity in AI by
Presenting a ground-breaking view of technology trends and their impact on our society, Artificial Era contributes to the current debate about the consequences of technological innovations. Alongside different viewpoints and statistics on the use of robots worldwide, productivity, and job displacement, Gissel Velarde identifies the particular problem of the lack of diversity in AI communities - and how that can exacerbate representation issues in employment, civil rights, gender, and education if no actions are taken. A timely, inciteful book which will be required reading for scholars and professionals working with AI and automation, and leaders in business and government interested in better understanding it and its effects on business and society.
Artificial Intelligence - Intelligent Art? by
As algorithmic data processing increasingly pervades everyday life, it is also making its way into the worlds of art, literature and music. In doing so, it shifts notions of creativity and evokes non-anthropocentric perspectives on artistic practice. This volume brings together contributions from the fields of cultural studies, literary studies, musicology and sound studies as well as media studies, sociology of technology, and beyond, presenting a truly interdisciplinary, state-of-the-art picture of the transformation of creative practice brought about by various forms of AI.
Creative applications of artificial intelligence in education by
This open access book explores the synergy between AI and education, highlighting its potential impact on pedagogical practices. It navigates the evolving landscape of AI-powered educational technologies and suggests practical ways to personalise instruction, nurture human-AI co-creativity, and transform the learning experience. Spanning from primary to higher education, this short and engaging volume proposes concrete examples of how educational stakeholders can be empowered in their AI literacy to foster creativity, inspire critical thinking, and promote problem-solving by embracing AI as a tool for expansive learning. Structured in three parts, the book starts developing the creative engagement perspective for learning and teaching to then present practical applications of AI in K-12 and higher education, covering different fields (teacher education, professional education, business education) as well as different types of AI supported tools (games, chatbots and AI assisted assessment). It also delves into the ethical considerations, policy implications, and the central role educators play in harnessing the power of an AI informed educational experience. Alex Urmeneta is a transformational and results-driven Learning Experience Strategist specialising in EdTech and start-up environments. Currently working for the Danish EdTech startup Rotoy ApSFor, he has been developing innovative curricula and leveraging technology and science-backed pedagogical strategies to create impactful educational content for over a decade. He has international experience in the finance, technology and education sectors and has led teams for Microsoft as well as other Fortune 500 entities. Margarida Romero is a full professor at Université Côte d´Azur, France, and associate professor at Université Laval, Canada. Founder of the Laboratoire d'Innovation et Numérique pour l'Education (LINE) research lab, she also coordinates the #Scol_IA Working Group on the educational challenges of artificial intelligence in education and co-directs the international MSc Smart EdTech program. Her research focuses on the study of transversal competencies, particularly in relation to computational thinking and creative problem-solving.
The descent of artificial intelligence : a deep history of an idea 400 years in the making by
The idea that a new technology could challenge human intelligence is as old as the warning from Socrates and Plato that written language eroded memory. With the emergence of generative artificial intelligence programs, we find ourselves once again debating how a new technology might influence human thought and behavior. Researchers, software developers, and "visionary" tech writers even imagine an AI that will equal or surpass human intelligence, adding to a sense of technological determinism where humanity is inexorably shaped by powerful new machines. But among the hundreds of essays, books, and movies that approach the question of AI, few have asked how exactly scientists and philosophers have codified human thought and behavior. Rather than focusing on technical contributions in machine building, The Descent of Artificial Intelligence explores a more diverse cast of thinkers who helped to imagine the very kind of human being that might be challenged by a machine. Kevin Padraic Donnelly argues that what we often think of as the "goal" of AI has in fact been shaped by forgotten and discredited theories about people and human nature as much as it has been by scientific discoveries, mathematical advances, and novel technologies. By looking at the development of artificial intelligence through the lens of social thought, Donnelly deflates the image of artificial intelligence as a technological monolith and reminds readers that we can control the narratives about ourselves.
Ethics of artificial intelligence : case studies and options for addressing ethical challenges by
This open access collection of AI ethics case studies is the first book to present real-life case studies combined with commentaries and strategies for overcoming ethical challenges. Case studies are one of the best ways to learn about ethical dilemmas and to achieve insights into various complexities and stakeholder perspectives. Given the omnipresence of AI ethics in academic, policy and media debates, the book will be suitable for a wide range of audiences, from scholars of different disciplines (e.g. AI science, ethics, politics, philosophy, economics) to policy-makers, lobbying NGOs, teachers and the educated public.
Feature models : AI-driven design, analysis and applications by
This open access book provides a basic introduction to feature modelling and analysis as well as to the integration of AI methods with feature modelling. It is intended as an introduction for researchers and practitioners who are new to the field and will also serve as a state-of-the-art reference to this audience. While focusing on the AI perspective, the book covers the topics of feature modelling (including languages and semantics), feature model analysis, and interacting with feature model configurators. These topics are discussed along the AI areas of knowledge representation and reasoning, explainable AI, and machine learning.
I, Human: AI, automation, and the quest to reclaim what makes us unique by
For readers of Sapiens and Homo Deus and viewers of The Social Dilemma, psychologist Tomas Chamorro-Premuzic tackles one of the biggest questions facing our species: Will we use artificial intelligence to improve the way we work and live, or will we allow it to alienate us? It's no secret that AI is changing the way we live, work, love, and entertain ourselves. Dating apps are using AI to pick our potential partners. Retailers are using AI to predict our behavior and desires. Rogue actors are using AI to persuade us with bots and misinformation. Companies are using AI to hire us--or not. In I, Human psychologist Tomas Chamorro-Premuzic takes readers on an enthralling and eye-opening journey across the AI landscape. Though AI has the potential to change our lives for the better, he argues, AI is also worsening our bad tendencies, making us more distracted, selfish, biased, narcissistic, entitled, predictable, and impatient. It doesn't have to be this way. Filled with fascinating insights about human behavior and our complicated relationship with technology, I, Human will help us stand out and thrive when many of our decisions are being made for us. To do so, we'll need to double down on our curiosity, adaptability, and emotional intelligence while relying on the lost virtues of empathy, humility, and self-control. This is just the beginning. As AI becomes smarter and more humanlike, our societies, our economies, and our humanity will undergo the most dramatic changes we've seen since the Industrial Revolution. Some of these changes will enhance our species. Others may dehumanize us and make us more machinelike in our interactions with people. It's up to us to adapt and determine how we want to live and work. The choice is ours. What will we decide?
Intelligent secure trustable things by
This open access book provides an overview about results of the InSecTT project. Artificial Intelligence of Things (AIoT) is the natural evolution for both Artificial Intelligence (AI) and Internet of Things (IoT) because they are mutually beneficial. AI increases the value of the IoT through machine learning by transforming the data into useful information, while the IoT increases the value of AI through connectivity and data exchange. Therefore, InSecTTIntelligent Secure Trustable Things, a pan-European effort with over 50 key partners from 12 countries (EU and Turkey), provides intelligent, secure and trustworthy systems for industrial applications to provide comprehensive cost-efficient solutions of intelligent, end-to-end secure, trustworthy connectivity and interoperability to bring the Internet of Things and Artificial Intelligence together. InSecTT creates trust in AI-based intelligent systems and solutions as a major part of the AIoT. InSecTT fosters cooperation between big industrial players from various domains, a number of highly innovative SMEs distributed all over Europe and cutting-edge research organizations and universities. The project features a big variety of industry-driven use cases embedded into various application domains where Europe is in a leading position, i.e., smart infrastructure, building, manufacturing, automotive, aeronautics, railway, urban public transport, maritime as well as health. The demonstration of InSecTT solutions in well-known real-world environments like airports, trains, ports and the health sector shows their applicability on both high and broad level, going from citizens to European stakeholders. The first part of the book provides an introduction into the main topics of the InSecTT project: How to bring Internet of Things and Artificial Intelligence together to form the Artificial Intelligence of Things, a reference architecture for such kind of systems and how to develop trustworthy, ethical AI systems. In the second part, we show the development of essential technologies for creating trustworthy AIoT systems. The third part of the book is composed of a broad variety of examples on how to design, develop and validate trustworthy AIoT systems for industrial applications (including automotive, avionics, smart infrastructure, health care, manufacturing and railway).
Introduction to digital humanism by
This open access textbook introduces and defines digital humanism from a diverse range of disciplines. Following the 2019 Vienna Manifesto, the book calls for a digital humanism that describes, analyzes, and, most importantly, influences the complex interplay of technology and humankind, for a better society and life, fully respecting universal human rights. The book is organized in three parts: Part I Background provides the multidisciplinary background needed to understand digital humanism in its philosophical, cultural, technological, historical, social, and economic dimensions. The goal is to present the necessary knowledge upon which an effective interdisciplinary discourse on digital humanism can be founded. Part II Digital Humanism a Systems View focuses on an in-depth presentation and discussion of the main digital humanism concerns arising in current digital systems. The goal of this part is to make readers aware and sensitive to these issues, including e.g. the control and autonomy of AI systems, privacy and security, and the role of governance. Part III Critical and Societal Issues of Digital Systems delves into critical societal issues raised by advances of digital technologies. While the public debate in the past has often focused on them separately, especially when they became visible through sensational events the aim here is to shed light on the entire landscape and show their interconnected relationships. This includes issues such as AI and ethics, fairness and bias, privacy and surveillance, platform power and democracy. This textbook is intended for students, teachers, and policy makers interested in digital humanism. It is designed for stand-alone and for complementary courses in computer science, or curricula in science, engineering, humanities and social sciences. Each chapter includes questions for students and an annotated reading list to dive deeper into the associated chapter material. The book aims to provide readers with as wide an exposure as possible to digital advances and their consequences for humanity. It includes constructive ideas and approaches that seek to ensure that our collective digital future is determined through human agency.
Media smart : lessons, tips and strategies for librarians, classroom instructors and other information professionals by
"The most important thing today's students can learn is how to find and evaluate information. This book provides in-depth discussion of aspects of media literacy and how they can be used to manipulate information. Classroom exercises are provided to help instructors teach vital media literacy skills to their students."
Poor Technology: artificial intelligence and the experience of poverty by
In recent years, artificial intelligence (AI) has moved in popular discourse from the purview of science-fiction imaginings to the key financial sector of the twenty-first century. As world powers, trillion-dollar companies, and public intellectuals emphasize the importance of AI, the general concerns people raise relate to economic movement, control, bias, and safety. This book adds a further concern, namely the way our approach to AI reinforces assumptions about dignity and personhood tied to the sort of thinking that is characteristic of bourgeois capitalists. The experience of poverty reveals that people who are poor do not think the same way as the upper classes--their experience of the world must be understood through the reality of survival within resource-scarce settings and the attendant domination and discrimination that come with being poor. These experiences do not fit well with the "ideal choice" selection model that underlies AI modeling, and numerous failures of AI to help the poor demonstrate that those who benefit primarily from AI are those who already live well. As a result, the fervor surrounding AI often serves to dehumanize the poor by eliminating employment opportunities, automating social work, reinforcing biases, and prioritizing profit over stability. Worst of all, however, AI functions to satisfy a psychological need for us to have "others" against whom we can distinguish ourselves without having to feel guilty about the reality of the struggle of the poor. Taking seriously the theological perspective of the "preferential option for the poor," this work contends that to avoid relegating poor people to nonhuman status, we must be willing to put aside the fantasy that AI is "intelligent" and focus rather on the all-too-human embodied reality of the poor.
Queer reflections on AI : uncertain intelligences by
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.
The Routledge social science handbook of AI
The Routledge Social Science Handbook of AI is a landmark volume providing students and teachers with a comprehensive and accessible guide to the major topics and trends of research in the social sciences of artificial intelligence (AI), as well as surveying how the digital revolution--from supercomputers and social media to advanced automation and robotics--is transforming society, culture, politics and economy. The Handbook provides representative coverage of the full range of social science engagements with the AI revolution, from employment and jobs to education and new digital skills to automated technologies of military warfare and the future of ethics. The reference work is introduced by editor Anthony Elliott, who addresses the question of relationship of social sciences to artificial intelligence, and who surveys various convergences and divergences between contemporary social theory and the digital revolution. The Handbook is exceptionally wide-ranging in span, covering topics all the way from AI technologies in everyday life to single-purpose robots throughout home and work life, and from the mainstreaming of human-machine interfaces to the latest advances in AI, such as the ability to mimic (and improve on) many aspects of human brain function. A unique integration of social science on the one hand and new technologies of artificial intelligence on the other, this Handbook offers readers new ways of understanding the rise of AI and its associated global transformations. Written in a clear and direct style, the Handbook will appeal to a wide undergraduate audience.
Stephanie Dinkins on love and data. by
Stephanie Dinkins is renowned for her critical investigations into artificial intelligence and machine learning systems as they intersect race, gender, and our future histories. By using her training in documentary practices as a photo-based artist, she creates inclusive platforms for dialogue and action toward building technological ecosystems and datasets that are equitable, accessible, and transparent. Her immersive installations, community-based workshops, and public talks seek audience participation and engagement in a way that pushes the boundaries of new media and socially engaged art practices in the 21st century. Stephanie Dinkins: On Love & Data brings together nationally renowned curators and theorists who draw from methodologies of art criticism, social practice, new media theory, and critical studies to offer an in-depth analysis of key installations in Dinkins's survey exhibition. The book also includes an important essay by Stephanie Dinkins on her concept of Afro-now-ism in which she expands on her theoretical framework and positionality as a Black new media artist in the 21st century. Dinkins's artistic research transcends the boundaries of visual art to challenge and expose the bias and inequities of caste, race, and gender, which are encoded within digital systems on which governance, healthcare, and security infrastructures in the United States are based.
Who Wrote This?: how AI and the lure of efficiency threaten human writing by
Would you read this book if a computer wrote it? Would you even know? And why would it matter? Today's eerily impressive artificial intelligence writing tools present us with a crucial challenge: As writers, do we unthinkingly adopt AI's time-saving advantages or do we stop to weigh what we gain and lose when heeding its siren call? To understand how AI is redefining what it means to write and think, linguist and educator Naomi S. Baron leads us on a journey connecting the dots between human literacy and today's technology. From nineteenth-century lessons in composition, to mathematician Alan Turing's work creating a machine for deciphering war-time messages, to contemporary engines like ChatGPT, Baron gives readers a spirited overview of the emergence of both literacy and AI, and a glimpse of their possible future. As the technology becomes increasingly sophisticated and fluent, it's tempting to take the easy way out and let AI do the work for us. Baron cautions that such efficiency isn't always in our interest. As AI plies us with suggestions or full-blown text, we risk losing not just our technical skills but the power of writing as a springboard for personal reflection and unique expression. Funny, informed, and conversational, Who Wrote This? urges us as individuals and as communities to make conscious choices about the extent to which we collaborate with AI. The technology is here to stay. Baron shows us how to work with AI and how to spot where it risks diminishing the valuable cognitive and social benefits of being literate.
Wittgenstein and Artificial Intelligence, Volume I by
This collection brings together work on the relevance of Wittgenstein's philosophy to the field of Artificial Intelligence (AI). Over two volumes, our contributors cover a wide range of topics from different disciplinary approaches. In this Volume (I), contributions are centred on two major themes in the philosophy of AI: questions of mind and language. Contributions include chapters on AI thought, intentionality, logic and language, as well as the relationship between Wittgenstein's thought and Turing's.
Wittgenstein and Artificial Intelligence, Volume II by
Volume II This collection brings together work on the relevance of Wittgenstein's philosophy to the field of Artificial Intelligence (AI). Over two volumes, our contributors cover a wide range of topics from different disciplinary approaches. In this Volume (II), contributions are centred on two major themes in the philosophy of AI: questions of value and governance. Contributions include chapters on both ethics and aesthetics and AI, as well as questions of the governance of AI systems, including legal and policy issues.
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ChatGPT was developed by OpenAI, an artificial intelligence company founded in 2015. The program generates text, code, and images. ChatGPT is accessible via the web, iOS, and Android. A basic account is free however there are flexible pricing accounts available. ChatGPT collects personal information and provide information to partners, in addition to analysis of user behavior, more information at: OpenAI Privacy Policy |
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Gemini was developed by Google AI, and was released in March 2023. Gemini is accessible via Google app integrations or the Gemini website and generates text, code and images. It also includes links to some web sources. A standard Google account grants access to basic AI services using an @gmail.com account. An upgraded version can be purchased, pricing can be found here. Gemini collects data such as location, past conversation data to respond, more information at: Gemini Apps Privacy Hub. |
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Meta AI was developed by Meta, formerly Facebook, Inc. Meta AI generates text, code, and images. You can use Meta without an account through Meta AI and the cost is free. Meta Privacy Policy requires submission of name and email to download the model. Once downloaded, the model can then be run locally without sharing data. |
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Consensus is a literature search tool using Semantic Scholar to find, summarize, and extract data from papers. It features a "consensus meter" that answers yes/no questions based on study percentages and integrates with Microsoft CoPilot. The free account offers unlimited searches with some CoPilot features, with an option to upgrade. |
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Elicit is a literature search tool that focuses on empirical research, such as randomized controlled trials in social sciences and biomedicine. It uses citations and open-access papers from Semantic Scholar to discover, summarize, and extract data. A free account offers unlimited searches, summaries of up to four papers at once, and more, with an option to upgrade for additional features. |
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ResearchRabbit, known as the "Spotify for papers," is a free tool that uses citations and open-access papers from Semantic Scholar to visualize connections between papers and researchers. It also recommends and summarizes papers for users. |
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Adobe Creative Cloud offers AI-enhanced tools for graphic design, video editing, and photography. Subscription-based. Available online and through desktop applications. |
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Canva AI enhances design capabilities with features like text suggestions, image generation, and layout recommendations. Free and paid versions are available online and through mobile app. |
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Stable Diffusion generates images, video and audio. Free and paid versions. Available to download and run locally, or use online through Stable Assistant. |
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GitHub Copilot generates and optimize code in many programming languages. Free and paid subscriptions are available. |
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Code Llama generate and optimize code in many programming languages. Available for free. |
