Artificial intelligence (AI) refers to a set of technologies which enable computers to perform advanced functions that are typically thought to require human intelligence. These functions might include recognizing faces, analyzing data, driving cars, creating art, interpreting and generating written and spoken language, and more. AI systems are trained on vast amounts of data, allowing them to identify patterns and relationships which humans may not be able to see. The AI learning process often involves algorithms, which are sets of rules or instructions that guide an AI's analysis and decision-making. Through continuous learning and adaptation, AI systems have become increasingly adept at performing tasks, from recognizing images to translating languages and beyond.
This guide contains a selection of resources that can help teachers and students learn about AI, literacy, and ways to navigate AI in classroom settings, giving us all a strong foundation to ethically and responsibly use AI technologies.
Suggested introductory articles:
Sources: AI Literacy: A Framework to Understand, Evaluate, and Use Emerging Technology (Keun-woo Lee, Kelly Mills, Pati Ruiz, Merijke Coenraad, Judi Fusco, Jeremy Roschelle and Josh Weisgrau; Digital Promise, June 18, 2024); What is Artificial Intelligence (AI)? (Google Cloud); What is AI? Everyone thinks they know but no one can agree. And that’s a problem (Will Douglas Heaven; MIT Technology Review, July 10, 2024)
You've probably been hearing a lot about artificial intelligence (AI)—but what is it exactly? As stated in the previous tab, artificial intelligence is a term that refers to technologies that are thought to require human intelligence. Though it might feel like AI had only recently been brought into our lives, it has actually been around since the 1950s. The Dartmouth Summer Research Project on Artificial Intelligence (known as the Dartmouth Workshop) was a 1956 summer workshop widely considered to be the founding event of artificial intelligence as a field.
Image: Participants at the Dartmouth Workshop. The Minsky Family (1956).
In the 1980s, "expert systems" (programs that answer questions or solve problems about a specific domain of knowledge) became widely used by corporations around the world to streamline processes like ordering computer systems and identifying compounds in spectrometer readings. In the 2000s, AI were trained on big data, leading to new systems that could perform tasks such as facial recognition, natural language processing, answer trivia questions (remember IBM's Waston?), and more.
Image: IBM's Watson competing on Jeopardy in 2011.
Since 2020, we have been in an "AI Boom" era, following the release of large language models exhibiting human-like traits of knowledge, attention and creativity such as ChatGPT. For more on the current state of AI, check out the following video:
Video: How will AI change the world? Ted-ED (2022). Stuart Russell discusses the current limitations of artificial intelligence and the possibility of creating human-compatible technology.
Sources: "History of artificial intelligence" & "Dartmouth Workshop" (Wikipedia)
There is a long history of depicting artificial beings in literature. Even in antiquity, thinkers and alchemists were imagining artificial beings endowed with intelligence or consciousness by master craftsmen. The books listed below are in chronological order beginning in the 1800s and highlight some pivotal moments of AI in fiction.
For more films, see Wikipedia's list of artificial intelligence films or this list on Letterboxd.
A generative AI system creates new text, images, or other media in response to prompts. As a student, it is important to take caution when utilizing AI software, especially for coursework or when importing data. To help you ethically and responsibly engage with these tools (especially generative ones), see the AI literacy box below and read through the acceptable uses of generative AI services at IU prepared by University Information Technology Services (UITS). Always ask your professor or TA if you are using AI for a class assignment.
The remainder of this box contains a collection of software (all with free trial or free tier options). We have focused on AI that can assist with productivity, task management, studying, and organizing your work and personal life, rather than generative AI.
Adobe Firefly As part of IU's software license with Adobe, you have access to the Firefly web app and generative AI features inside apps like Photoshop and Illustrator as well as Adobe Stock.
See more scheduling assistants and comparison charts here.
Sources: The best AI productivity tools in 2024 Miguel Rebelo, Zapier Blog
Note: Though this can help you summarize research more quickly, it is important to be cautious and read papers yourself if you plant to cite them or include them in your research
See a comparison chart of AI tools for research here.
Note: Always double-check generated citations.
Chatbots have the potential to revolutionize our lives, make work more efficient, and free up time so that people can focus on other tasks. However, it is important to be very cautious when using chatbots. Not only are they newly-developed and continually evolving, but we have already seen bias in many other AI systems (see the "Centering Justice" tab for more. Before using an AI chatbot, make sure you understand the risk and be sure to use the AI Literacy Framework above to evaluate outputs. See below for articles on the risks of chatbots:
Claude Built for work and trained to be safe, accurate, and secure. Claude can answer nuanced questions and create a variety of content. Trained by Anthropic using Constitutional AI. While Claude is fast and well-organized, it is not connected to the internet and does not automatically provide sources. Free tier available.
Perplexity A research chatbot that is good at providing sources (which it lists in an easily-accessible sidebar). Though Perplexity gives nuanced answers in an easy-to-follow list, it does tend to rely on Reddit posts as sources, which most people cannot cite for their projects. Free tier available.
ChatGPT Offers meaningful answers with a good amount of context on a variety of topics. While ChatGPT is good at most tasks like research and writing emails, it can be slow at times and it can be tedious to get ChatGPT to cite its sources. Developed by OpenAI and free to use.
InterviewBy.ai Practice job interview questions tailored to your job description. Get instant AI feedback and suggestions to improve your answers. Free plan includes 3 questions/month
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Visuals and Photography
AI Detectors
Though many people have grown up surrounded by AI technologies that have affected everything from traffic patterns to the products available at grocery stores, the recent release of ChatGPT brought AI to the forefront of our lives. The increased accessibility of AI bring with it a need for AI literacy. In this context, literacy does not simply refer to the ability to use AI technologies but to the combination of knowledge and skills that allow users to critically understand and evaluate AI tools in an increasingly digital world. In our daily lives, we implement information, media, financial, and health literacy when performing all kinds of tasks. When practicing AI literacy, one might ask questions like: How does this technology work? What kind of data was this system trained on? What biases are present in this technology? How does this impact my world and the world around me?
Source: AI Literacy, Explained (Alyson Klein; EducationWeek, May 10, 2023)
Everyday, we utilize different literacies. For example, when we read the news, we might use an information literacy framework to determine whether or not we can trust the media which we encounter. We can ask questions about who created or funded an article, about why the message of the piece is being sent, and about what kind of research went into the piece. Similarly, we can utilize an AI Literacy Framework when utilizing AI-enable technologies or engaging with the outputs of such systems. The following practices, developed by consultants and research at Digital Promise, define how users can understand and evaluate AI-enabled tools and how educators can support AI literacy development.
AI Literacy Practice | Description | Student Looks For |
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Algorithmic Thinking, Abstraction & Decomposition | Develop and/or use a computer’s ability to recognize data and create a prediction or perform an action based on both the situation and stored information without explicit human guidance. |
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Data Analysis & Inference | Consider the context of datasets, data visualizations, and data collection with criticality. Assess quality of training data for AI tools and leverage AI models and methods to collect, analyze, and visualize data. |
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Data Privacy & Security | Develop awareness of data privacy and security while fostering ownership and agency of how to protect data in AI-enabled systems. This includes the privacy and security of personal data collected by an AI system or tool and how that data is used. |
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Digital Communication & Expression |
Understand how AI Systems create synthetic content, evaluate synthetic AI creations, and consider ethical responsibilities when consuming, creating, and sharing AI-enabled products. |
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Ethics & Impact | Examine the outputs of algorithms and question the biases inherent in the AI systems and tools being used. Consider the benefits and harms of AI tools to the environment, people, or society Importantly, it includes considering how datasets, including their accessibility and representation, reproduce bias in our society. |
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Information & Mis/Disinformation |
Determine credibility of AI system outputs in digital landscapes. This includes evaluating datasets and AI products/outputs for false, inaccurate or misleading information. |
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Source: AI Literacy: A Framework to Understand, Evaluate, and Use Emerging Technology (Kelly Mills, Pati Ruiz, Keun-woo Lee, Merijke Coenraad, Judi Fusco, Jeremy Roschelle, & Josh Weisgrau; Digital Promise, June 2024)
Similar to an AI Literacy framework, the ROBOT test, developed by librarians at McGill University (Amanda Wheatley and Sandy Hervieux) offers a helpful mnemonic for evaluating AI systems and outputs. "Being AI Literate does not mean you need to understand the advanced mechanics of AI. It means that you are actively learning about the technologies involved and that you critically approach any texts you read that concern AI, especially news articles."
Reliability Objective Bias Ownership Type
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For more books, see the following subject headings in IUCAT:
AI has many applications at all levels of education. Though we may know AI best for the way it has reshaped student learning (through the proliferation of generative AI technologies that can create text, code, and other types of content), AI is also utilized by teachers and administrators. Predictive AI tools can analyze patterns in student data to forecast outcomes such as graduation rates and student learning milestones. These insights allow educators to intervene proactively but require careful evaluation for potential bias. See some more uses of AI in education below:
Chart: Examples of AI Applications in Education (Digital Promise).
AI also has many potential benefits when implemented in an educational setting. Of course, there are many risks as well:
Graphic: Potential risks and benefits of AI in education (TeachAI).
In this box, we have selected frameworks, toolkits, books, and articles that will help teachers and students implement and utilize AI in their classrooms.
For more books, see the following subject headings in IUCAT:
Much research has been done on bias in AI. As AI becomes more ubiquitous, it is important to understand that our own unconscious, implicitly biased associations can affect AI models, resulting in biased outputs. Though we might think of technology as neutral, AI has a long history of perpetuating biases present in our society such as racism, ableism, ageism, sexism, homophobia, and more. We should also think about the climate impact of AI when discussing its ethics. This box contains articles, books, and reports to help you learn more.
Video: Artificial Intelligence: Last Week Tonight with John Oliver. (2023, HBO)
The Uneven Distribution of AI’s Environmental Impacts (Shaolei Ren and Adam Wierman, Harvard Business Review)