Library: ChatGPT & Generative A.I.: Find Tools for Detecting AI & Citation Resources

Library Resources

Remember, if you don't own or didn't create it, you'll need a citation or credit attached to the resource. Learn more about avoiding plagiarism below:

Academic Honesty and Avoiding Plagiarism
In this tutorial, we hope to show you how to avoid intentional and unintentional plagiarism in your research and coursework and understand the academic integrity policies of MCCC and the consequences of plagiarism.

ACRL Framework and AI - A Guide for Instruction
The Association of College and Research Libraries (ACRL) ‘Framework for Information Literacy for Higher Education’ includes six frames that categorize the knowledge practices and dispositions that college student can be expected to develop, regardless of program or area of study, when performing research.
Librarians and classroom faculty can employ the framework in lessons that address generative AI tools, helping students understand the benefits and harms of using these technologies for research and communication.

Citation Guides
This guide is designed to support researchers in creating citations.
Copyright & Fair Use
This guide is designed to share information on copyright and fair use in an educational setting and provide guidance on finding and using materials in online, hybrid, and in-person courses.
Dr. ChatGPT or: How One Instruction Librarian Learned to Teach with AI by Elise Ferer
In this session we will explore the responsible use of generative Artificial Intelligence in higher education and ways in which we can incorporate AI tools into our classrooms and IL instruction. Much like Wikipedia, AI tools can assist our students in developing their own research and writing skills when used in responsible ways. In embracing generative AI librarians can assist students in navigating the use of AI in research and writing. As many of our students are already using AI tools or will be using them in the near future it is important for librarians to explore these tools and think about how they can be used to help students learn by Elise Freer.
Expertise on Demand: Developing Need-Based AI Literacy by Brooke Gross
This session will offer a few key steps for building relationships with instructors or community leaders in order to expand artificial intelligence education. One of the biggest challenges facing librarians and educators when it comes to artificial intelligence is determining where, when, and how it should be used without infringing on copyright or putting users' data at risk. Additionally, because AI is evolving so rapidly, the tools and best practices are ever-changing. This makes it more difficult to acquire dedicated expertise. Therefore, we must learn how to quickly adapt and reassess in order to successfully stay on top of these technological advancements. The purpose of this session is to help librarians determine what basic knowledge they need in order to develop AI initiatives and how they can collaborate with others to see them through. The presenter will speak from their experiences using AI in college classrooms and initiating conversations about AI ethics in academia, highlighting ways in which librarians who have not yet delved deeply into the world of artificial intelligence can still facilitate important learning and discussion. Created by Brooke Gross.
Navigating the AI Landscape: Insights from Information Literacy Professionals Natalie Marquez & Emmanuel Te
Generative artificial intelligence (AI) programs, such as ChatGPT, exploded onto the scene with the public release of ChatGPT in November 2022. Since then, countless articles have been published promoting the benefit of AI and the dangers it poses including threats to our jobs as information professionals and educators. However, few studies document if and how current information practitioners and institutions use AI in their work (Dessy et al, 2022; Wheatley and Hervieux, 2019; Gujral et al, 2019) . To address this knowledge gap, a LILi task force on AI conducted a survey of librarians and other information literacy professionals in Spring 2024 to learn more about their adoption of AI. The survey and its results will detail how AI is used in their work, specific AI tools used, and their comfort level and concerns around AI use. This presentation will review the task force’s findings and compare the data to broader AI surveys. The presenters will offer a few suggestions based on their understanding of their findings and time for participants to contribute their observations and insights with the same survey and a poll. Created by Natalie Marquez & Emmanuel Te.

How To Get Around ChatGPT Detectors

Video Credit: The AI Advantage, YouTube, Jan 8, 2023.

Unbelievable! The Easiest Way to Bypass AI Content Detection - How I Did It!

Video Credit: Dr. Andy Stapleton, Apr 10, 2024.

New Way to Bypass AI Detection (Guaranteed)

Video Credit: Jason West, YouTube, May 9, 2023.

Warning!

***Please note that A.I. detectors are not always reliable or accurate. The detectors listed are to provide resources for educational purposes.***

"Even though AI detectors do not work, that doesn't mean a human can never detect AI writing. For example, a teacher familiar with a student's typical writing style can tell when their style or capability suddenly changes. Also, some sloppy attempts to pass off AI-generated work as human-written can leave tell-tale signs, such as "A.I. language model," meaning someone copied and pasted ChatGPT output without being careful. Recently, an article in the scientific journal Nature showed how humans noticed the phrase "Regenerate response" in a scientific paper, which is the label of a button in ChatGPT" (Text adapted from Benj Edward's article OpenAI confirms A.I. that AI writing detectors don't work).

AI & DeepFake Detectors

AI Detect
The best way to detect A.I. writing within any piece of text.
Content at Scale
The ChatGPT detector works more profoundly than a generic AI classifier, detecting robotic-sounding content.
Copyleaks
Paste your content below, and we’ll tell you if any of it has been AI-generated within seconds with exceptional accuracy.
Crossplug
Our plagiarism detection tool helps students, teachers, writers, and bloggers ensure originality in their work by comparing each writing with more than 100 billion texts worldwide.
DeepFake-O-Meter
An open platform integrating state-of-the-art DeepFake Detection methods.
DeepfakeProof
DeepfakeProof is a free browser extension that utilizes advanced deep fake detection technology to prevent the spread of deep fake-manipulated images online (Tip: Use in Chrome).
GLTR
Giant Language Model Test Room (GLTR for short) is a detection tool that uses “a suite of baseline statistical methods that can detect generation artifacts across common sampling schemes.”
GPTZero
Detect ChatGPT, GPT3, GPT4, Bard, and other AI models.
Hugging Face
Hugging Face, Inc. is an American company that develops tools for building applications using machine learning. It is most notable for its transformers library built for natural language processing applications and its platform that allows users to share machine learning models and datasets.
Kazan SEO
This neat toolkit has features outside of AI detection, including a content generator, a tool for discovering and researching keywords, URL text extraction for SEO analysis, and co-relational content optimization.
Originality.AI
The most accurate Chat GPT and GPT-4 AI detector explicitly built for content marketers and SEOs (Note: Fee-based).
Sapling AI
AI-generated text, also known as machine-generated text or automated text, is a product of natural language processing techniques that enable machines to mimic human language patterns and generate text. The benefits of AI-generated text include its ability to save time and resources by automating repetitive writing tasks and producing large volumes of content quickly. While AI-generated text can offer many benefits it is essential to be mindful of its limitations and potential risks when using it for specific purposes.
Turnitin
AI writing tools are developing rapidly, and so is Turnitin’s technology to detect these emerging forms of misconduct. Recently, we shared with you that we have technology that can detect AI-assisted writing and AI writing generated by tools such as ChatGPT. Today, we want to introduce you to our AI Innovation Lab to give you a first-hand glimpse of what our technology (in development) can do.
Undetectable AI
Use our AI detector to check if your text will be flagged as AI-written content. Then, click 'humanize' to remove AI detection and ensure your text will bypass all major AI detectors. Our AI text humanizer does this by enhancing your content to match the quality of human writing.
Winston AI
Winston AI is the industry leading AI content detection tool to help check AI content generated with ChatGPT, GPT-4, Google Gemini and many more Large Language Models.
Writer
AI content detection is only available in the Writer app as an API and is limited to checks of 1,500 characters at a time.

Bias & Fake Citations

Bias and artificial hallucination (fake citations/references - references created by A.I.) exist within all A.I. You'll have to use A.I. literacy to double-check your citations if you use any generative A.I. for your research.

A.I. literacy includes:

The ethical use of A.I. (why and when, and awareness of issues such as data ownership, privacy, legality, and hidden labor),
Knowledge of A.I. affordances (what are the capabilities and limitations of each A.I. tool; A.I. over 1000 AI tools are available),
How to work effectively with A.I. tools (A.I. has how to formulate practical questions, construct good prompts, called "prompt engineering" and refinement strategies),
How to evaluate the output (thinking, critique, and evaluative judgment are essential skills regardless), and finally,
Use and integrate these tools into your practices for study and work purposes. (Source: Mathew Hillier, Why does ChatGPT generate fake references? 2023)

Image Credit: McKinsey & Company, 2019

AI Bias - What Is It and How to Avoid It?
Algorithms are not neutral when weighing people, events, or things differently for various purposes. Therefore, we must understand these biases to develop solutions to create unprejudiced AI systems. This article will discuss what AI bias is, the types of AI bias, examples, and how to reduce the risk of AI bias.
AI Literacy, Explained
The technology poured accelerant on a conversation already underway: Now that AI is shaping nearly every aspect of our lives and is expected to transform fields from medicine to agriculture to policing, what do students need to understand about AI to be prepared for the world of work? To be a smart consumer and a responsible citizen?
Deepfakes, Synthetic Media and Generative AI
WITNESS helps people use video and technology to protect and defend human rights. Our Technology Threats and Opportunities Team engages early on with emerging technologies that have the potential to enhance or undermine our trust on audiovisual content. Building upon years of foundational research and global advocacy on synthetic media, we’ve been preparing for the impact of AI on our ability to discern the truth. In consultation with human rights defenders, journalists, and technologists on four continents, we’ve identified the most pressing concerns and recommendations on what we must do now.
The Future of AI Detectors: A Comprehensive Evaluation
As the realm of artificial intelligence continues to expand, so does the need for reliable AI detectors. These ingenious systems have swiftly become indispensable in identifying computer-generated content and contributing to the overall integrity of digital platforms. However, as technology evolves, the challenges in detecting sophisticated AI-generated content have intensified.
Humans Absorb Bias from AI—And Keep It after They Stop Using the Algorithm
People may learn from and replicate the skewed perspective of an artificial intelligence algorithm, and they carry this bias beyond their interactions with the A.I.
Professors Cautious of Tools to Detect AI-Generated Writing
Mixed performance by AI-detector tools leaves academics with no clear answers.
Shedding light on AI bias with real world examples
As companies increase their use of artificial intelligence (AI), people are questioning the extent to which human biases have made their way into AI systems. Examples of AI bias in the real world show us that when discriminatory data and algorithms are baked into AI models, the models deploy biases at scale and amplify the resulting negative effects.
Tackling bias in artificial intelligence (and in humans)
AI has the potential to help humans make fairer decisions—but only if we carefully work toward fairness in AI systems as well.
There’s More to AI Bias Than Biased Data, NIST Report Highlights
Rooting out bias in artificial intelligence will also require addressing human and systemic biases.
Three fixes for AI's bias problem
Everywhere there's artificial intelligence, there's the risk of it amplifying the beliefs of the people who created it. Research from UC is pinpointing tech bias and proposing solutions.
A Unified Framework of Five Principles for AI in Society
Artificial Intelligence (AI) is already having a significant impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles for adopting socially beneficial AI. Unfortunately, the sheer volume of proposed regulations threatens to overwhelm and confuse. How might this problem of ‘principle proliferation’ be solved? In this paper, we report the results of a fine-grained analysis of several of the highest-profile sets of ethical principles for AI.
What Do We Do About the Biases in AI?
Over the past few years, society has wrestled with how much human biases can make their way into artificial intelligence systems—with harmful results. At a time when many companies are looking to deploy AI systems across their operations, being acutely aware of those risks and working to reduce them is an urgent priority. What can CEOs and their top management teams do to lead the way on bias and fairness? Among others, we see six essential steps: First, business leaders must stay up to date on this fast-moving field of research. Second, when your business or organization deploys AI, establish responsible processes that can mitigate bias. Consider using a portfolio of technical tools and operational practices such as internal “red teams” or third-party audits. Third, engage in fact-based conversations around potential human biases.
What is AI Literacy? A Comprehensive Guide for Beginners
Explore the importance of AI literacy in our AI-driven world. Understand its components, its role in education and business, and how to develop it within organizations.
Why does ChatGPT generate fake references?
It is uncovering the ingredients that go into robotic porkie pies and some possible sweet desserts at the end.

Citing Generative A.I.

How do I cite generative AI in MLA style?
The MLA’s method for citing sources uses a template of core elements—standardized criteria writers can use to evaluate sources and create works-cited-list entries based on that evaluation. That new technologies like ChatGPT emerge is a key reason why the MLA has adopted this approach to citation—to give writers flexibility to apply the style when they encounter new types of sources.
How to cite ChatGPT
If you’ve used ChatGPT or other AI tools in your research, describe how you used the tool in your Method section or a comparable area of your paper. You might explain how you used the device in your introduction for literature reviews or other types of essays or response or reaction papers. In your text, provide the prompt you used and any portion of the relevant text generated in response.
Six Tenets of Postplagiarism: Writing in the Age of Artificial Intelligence
Dr. Sarah Elaine Eaton created the six tenets of postplagiarism within the age of A.I.

MCCC Policy

Ethical Use of Generative AI Guidelines

1. You are discouraged from using AI tools unless you are under the professor's direct instruction. Please get in touch with your professor if you are unsure or have questions before using AI for any assignment.

2. If AI is permitted to be used, you must indicate what part of the assignment was crafted by AI and what your work was. If you have received permission, no more than 25% of a project should be created with AI.

3. You may not submit any work generated by an AI program as your own. Suppose you include material generated by an AI program. In that case, it should be cited like any other reference material (with due consideration for the quality of the reference, which may be poor).

4. Since writing, analytical, and critical thinking skills are part of the learning outcomes of this course, all writing assignments should be prepared by the student. Developing strong competencies in this area will prepare you for a competitive workplace. Therefore, AI-generated submissions are not permitted and will be treated as plagiarism. The Code of Ethics is important, and plagiarism is a severe offense at MCCC.

5. Some student work may be randomly submitted to AI or plagiarism detection tools to ensure it is human-created. Submitting AI-generated answers constitutes plagiarism and violates the MCCC Student Code of Ethics. Using these tools without permission puts your academic integrity at risk. (Text adapted from Addendum to Syllabus Template created by Tracy Kaiser-Goebel in 2023).

Ethical use of Generative AI on Assignments
This is a guide on ethical use of generative AI tools for your assignments. As a MontCo student, it is essential to maintain academic integrity and uphold ethical standards in your work. This guide will help you navigate the responsible use of AI technology in your academic endeavors.