Types of AI

Introduction here

Academic AI

Instructional Technology has been working closely with the Faculty Development Center and faculty groups to understand how faculty, departments, and colleges want to engage with AI in their instructional activities. We understand that due to the lack of available tools and time, many faculty have not had the chance to use AI. We also understand that GenAI can be used incorrectly and create academic misconduct issues. At the same time, we have been working with individual faculty on some small pilots where they want to leverage AI to better support students in their classes.

Below are a few examples where AI can be leveraged to support teaching and learning:

  • Students will need to learn how to navigate in a world in which AI is a commonplace feature, if not a job requirement (Lakhani, 2023). Learning new skills, such as how to use large language models, as well as the benefits, failures, and ethics of doing so, are important components we can include in our courses and internships (ChatGPT, 2023; Mollick & Mollick, 2023c).
  • In an age where misinformation is rampant, understanding AI can help students discern between genuine information and AI-generated content, whether news articles or deepfake videos (Kreps, McCain, & Brundage, 2020; Hsu & Thompson, 2023). Additionally, since AI depends on vast amounts of data for its training models, including personal information, students need to understand how AI can be biased and harmful (Kertysova, 2018; Dwivedi, et al., 2023).
  • Today’s cloud-based tools (Google & Microsoft) will include AI as a native feature (Warren, 2023; Vincent, 2023). Embedded tools provide generative AI across productivity applications to help users visualize, organize, and write as they work. In the near future, it is very easy for students to use AI in some measure.
  • Survey your students and then invite your class to have a conversation about AI. Share your thoughts and ask your students for their perspectives. Set clear expectations for using generative AI tools including how to cite or reference appropriately, if permitted (Mollick & Mollick, 2023).
  • Consider your course schedule, how much content is in your course, and how that might impact whether students may be tempted to use generative AI tools to take short-cuts (Alexander, 2022; Watkins, 2022).
  • Demonstrate how AI tools work: Show students the benefits and limitations of using AI tools in your course and discipline. Clarify parameters in which you might consider AI (e.g., brainstorming, grammar checking) and when you would not permit it (e.g., writing).
  • Have students critique what generative AI tools output — code, text, lesson plans, etc. — and determine if it is accurate, inclusive, accessible, etc. for your discipline or course level. AI can be a beneficial tool when used appropriately.
  • Incorporate AI into active learning to help students learn how to appropriately use AI technologies by writing prompts, analyzing AI outputs, and refining follow-up interactions (Watkins, 2022).
  • For non-timed assessments, ask students to compose their assignments in Google so they can share the version history. This will show the overall composition process as they work and whether large blocks of text were pasted into the document. If assignments are composed in Word (in 365 online), it’s also possible to view the document version history.
  • Scaffold major assessments. Build steps, such as outlines and drafts, so students show their writing progress. Have them share their notes and other preparatory work that contributes to the final product.
  • Include reflection components for each assessment, especially the writing process, so students provide personal insight into the process of developing their ideas (Borup, 2023). Reflections can also be created using multimedia with Panopto or VoiceThread.
  • Consider peer assessment, group work, and other collaborative activities where students can learn from each other and share responsibility for the assessment process.
  • If students do use AI, they should have prompts readily available to explain how they made use of them and explain their process. For example, ChatGPT includes a share function that allows a user to provide a link to the conversation that you can review.
  • Leverage Respondus Lockdown Browser, which prevents students from opening anything except the assessment environment. This works best if students are working in a timed assessment scenario. Respondus Monitor will record the desktop if it is absolutely imperative to have this level of security.
  • There are a number of AI detection tools available, some built on older APIs for ChatGPT and therefore they are not accurate just on this factor alone. AI, by its nature, is constantly learning and improving itself and it may never be possible to truly detect whether text is AI-generated. Passages from the Bible, the U.S. Constitution, and Macbeth have been flagged as written by AI.
  • Researchers argue that AI detectors are not reliable (Sadasivan, Kumar, Balasubramanian, Wang, & Feizi, 2023) or consistently misclassify non-native English writing as AI-generated (Liang, Yuksekgoul, Mao, Wu, & Zou, 2023).
  • In a study of fourteen AI detection tools, all scored below 80% accuracy — only five managed to score over 70% (Weber-Wulff, et al., 2023). When submissions are modified to obfuscate AI-generated text, such as editing or paraphrasing, the AI detection is even lower.
  • The Washington Post found that some AI detectors falsely flagged students 50% of the time (Fowler, 2023). Similarly, Rolling Stone noted that a professor failed students due to inaccurate AI detection in their work (Klee, 2023).
  • AI detectors do a poor job of detecting as the quality of AI-generated text is constantly improving or students can adapt the output to trick the AI detection tools (Wiggers, 2023; Coffey, 2024).
  • Educators may consider AI detection tools to test their assessment design and determine how easy it is to use AI to complete an activity… “assume students will be able to break any AI-detection tools, regardless of their sophistication” (Lee & Palmer, 2023).

Note: UMBC does not license any AI detection tools at this time. The institution engages with the broader higher education community to stay informed about the latest trends, technologies and resources related to artificial intelligence and AI detection in academic environments.

Generative AI tools are helpful to improve course and unit learning objectives, including alignment of those objectives to assessments, instructional materials, and activities (Quality Matters standards 2.1, 2.2, 3.1, 4.1, 5.1, and 6.1).

  • Generative AI tools can help create long descriptions for complex images. (Discover more in this presentation, Leveraging AI for Enhanced Visual Content to Support Accessibility.)
  • Anthology Ally can provide limited support generating descriptions for some images using generative AI, but instructors should review the description for accuracy.
  • Handwritten essays and oral exams may disadvantage students with disabilities, or provide a non-inclusive environment for students (Folts, 2023). Google Assignments and other collaborative tools help track student work.

2024-25 FLCs Related to AI

The Faculty Development Center (FDC) has sponsored two faculty learning communities in AY 2024-25 associated with AI, and these can be ways to reach out to fellow faculty and learn from their discussions.

  • Developing Students’ AI Literacy Within and Across Disciplines (Facilitated by Mariajosé Castellanos, CBEE, and Bill Ryan, IS).
  • Using AI to Enhance and Expedite Teaching (Facilitated by Diane Alonso, PSYC, and Neha Raikar, CBEE).

Instructional Technology Presentations on AI

  • Hawken, M., & Biro, S. (2023). Ask Janet: Leveraging AI for Course Design, Instruction and Learning. OLC Accelerate Conference, Washington, DC.
  • Penniston, T. (2023). Toward a New Paradigm: Learning Analytics 2.0. 25th International Conference on Human-Computer Interaction, HCI International 2023. Copenhagen, Denmark.

Administrative AI

Generative AI, or GenAI, can be a powerful productivity tool that has the potential to increase productivity in our everyday work. UMBC wants to be at the forefront of supporting employees in using these tools to improve service and give employees more time to provide personalized support.

As we use AI, we want the administrative use of AI to be guided by the following principles:

  • Safeguard data in our use of AI. Please remember, unless you are using a tool from the AI @ UMBC web page, you may only use public data with a generative AI service. Using any UMBC proprietary data is forbidden.
  • Support excellent self-service and err on the side of correct information over guessing. Our goal in launching myUMBC Answers was to provide students with self-service, personalized, and curated information without having to search our websites. In building myUMBC Answers, we have limited and focused the sources of data we use.
  • Learn what does and doesn’t work. GenAI is a new technology that is evolving rapidly, and we want to understand what does and doesn’t work. Sharing feedback is essential to help us learn what does and doesn’t work.

Cloud Computing AI

UMBC has cloud computing contracts for Microsoft Azure (Open AI), Google Cloud (Gemini AI), and Amazon AWS Bedrock (Anthropic and Meta).

The vendor cloud computing options provide a wide range of commercial options that faculty can utilize in their research. There is a cost when using cloud computing. DoIT has contracts in place, and if your grant allows the purchase of cloud computing resources, we can set up accounts specific to your grant for chargebacks. DoIT has worked with some different cloud vendors and has found that cloud computing costs for AI are quite reasonable, if architected correctly. Please submit a ticket and let DoIT know how we can help you.

One advantage of using cloud computing for generative AI development is that each of the cloud computing vendors has built powerful development environments with all the appropriate libraries needed to build a generative AI application.

Generative AI

Generative AI, also known as GenAI, is a type of artificial intelligence that can create new content like text, images, videos, and music.

GenAI can also learn from data and generate new data instances. Like any technology, generative AI offers both opportunities and risks to manage. UMBC is actively evaluating and exploring AI and its potential impact on teaching and learning, research and scholarship, administrative, and other functions within our community.

One of the critical issues with GenAI is that some tools use the information provided, such as documents, textual input, or other forms of content, as training data for the GenAI service. Unless this information is considered public material, something you would publish on a website for the Internet to see, you should not use content from UMBC on any GenAI service unless you know that UMBC has verified it is safe to use. Luckily, UMBC has access to several GenAI tools that have been verified as safe to use on UMBC Level 1 & FERPA data, which is data intended to be kept internal to UMBC.