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Generative Artificial Intelligence (GenAI): Home

This guide provides an introduction to Generative Artificial Intelligence, originally created in Fall 2023 and updated in Winter 2024 by Librarian Greg Bem. Content based on Fall 2023 and Winter 2024 workshops developed by Greg Bem.

AI Guide Disclaimer

This guide was designed to support student learning at Spokane Community College. Its primary goal is to provide an introduction to understanding Generative Artificial Intelligence (GenAI)​. Consider this guide a steppingstone in a journey of Digital Literacy / technology education​. Note that this guide was created by a librarian and provides a general approach to learning about GenAI. This guide was not co-created with college administration or any specific academic programs or departments. Note that this guide was not created with the intention to promote GenAI as a universal technology solution. Students should critically think about technology tools and consider issues of use.

AI Definitions

What is Artificial Intelligence (AI)?

"Artificial intelligence is a field of science concerned with building computers and machines that can reason, learn, and act in such a way that would normally require human intelligence or that involves data whose scale exceeds what humans can analyze. ​

"AI is a broad field that encompasses many different disciplines, including computer science, data analytics and statistics, hardware and software engineering, linguistics, neuroscience, and even philosophy and psychology."​


What is Generative Artificial Intelligence (GenAI)?

"Generative AI refers to deep-learning models that can generate high-quality text, images, and other content based on the data they were trained on."


What is Generative AI? Video


Emerging GenAI Technologies and Considerations

  • Integration of technology into more apps​/platforms, including various AI technologies brought into single interfaces (e.g. Bing Chat)
  • Consolidation of Language Learning Models (LLMs) into single apps
  • Input advancements, including Vision and Speech​
  • Apps available for offline access, including GPT4All
  • Costs are increasing with more advanced features

Bias in GenAI Images

GenAI Images have many of their own problems and issues, and often those connected intellectual property and copyright law are centered. However, bias and stereotyping is rampant across many GenAI tools. Issues include:

  • Trained datasets hold significant bias and sustain stereotypes (race, gender, body type, etc)​
  • Image stereotypes can be blatant or subtle​
  • Stereotypes can be in the background/periphery of the image, not always main subject​
  • Ethical safeguards tend to be manual and sometimes are reactive​
  • Jailbreaking as civic action (example)​
  • Deep fakes can be created by training GenAI tools on sample images

Additional Resources to Learn about Bias in Technology

Intro to GenAI Tools

A Selection of Popular GenAI Tools

Updated March 2024

Qualities of GenAI Tools

  • "Trained" on large sets of data (millions+ of documents)​
  • Utilizes "Large Learning Models (LLM)" (eg. "Generative Pre-Trained Transformer 3")​
  • Requires user input to create some form of output​
  • Developed by for-profit companies, non-profit organizations, and individuals​
  • Platforms can be free, paid, or both​
  • Mostly available through web browsers, mobile apps​

Common GenAI Output Types

  • Plain text​
  • Stylized text
  • Computer code​
  • Original image​
  • Edited image​
  • Animated image​
  • Video​
  • Music​

Prompts and Iterations

  • GenAI interfaces are similar to search engines​
  • The prompt is the phrase or keywords entered into search box​
  • Some tools have advanced features​
  • Iterative design offers a conversational approach to search​
  • Iterations can be limited (platform control, cost, etc) (eg. Bing Chat = 30 iterations in a single chat)​
  • And "Prompt engineer" is an emerging role / skill set​ that centers expertise in using prompts in a GenAI platform

Generative AI: What is it good for?

GenAI at College

GenAI in Higher Ed

  • GenAI usage exists across disciplines​ and is used in different ways depending on need
  • Some students use GenAI tools like ChatGPT as their "Copilot" or Virtual Tutor

Reported benefits of using these tools include:​

  • Familiar/friendly voice​
  • Support for different learning styles / disabilities​
  • Precision in answers​
  • Iterative conversations​
  • Technological access​
  • Ease of use​

Other considerations:​

  • Online access requirements​: many of these tools require an active Internet connection to use
  • There are typically financial costs for premium models / features​, and these costs can change at any time

Popular GenAI Tools Used by College Students'

Note: use these tools with caution and critically consider their functionality and output.

Additional GenAI Tools to Explore

Note: use these tools with caution and critically consider their functionality and output.

Recommended Best Practices of GenAI Use for Students

  • Communicate with your professor from the start of your course about GenAI expectations​
  • Look for syllabus / assignment language on how/how much you can use GenAI tools, if at all​
  • Be aware of differing opinions on GenAI across the college; some professors love GenAI, some hate GenAI
  • Stay up to date on news and trends with GenAI​
  • Consult with a librarian for best practices and any information about GenAI at the college​
  • As with any technology, acknowledge over-reliance​
  • Include statements of use and citations when using a GenAI tool​

GenAI at Work

GenAI in the Workforce

  • GenAI is being integrated with a variety of pre-existing technology, including Microsoft Windows and Office, the Adobe Suite, and more
  • Common outputs for creating and editing include:​
    • Business documents and templates​
    • Emails and meeting agendas​
    • Speeches and formal announcements​
    • Translations / localizations​
    • Simple code for computer programming​
  • Visual outputs for virtual environments and images are changing a variety of workflows and impacting many industries
  • GenAI may threaten certain jobs and evolve others, as time is saved and productivity is increased
  • GenAI may open opportunities for more creativity and evaluative thinking

Ethics and GenAI Tools

Ethical Use of Technology

Ethics in the context of technology typically means using technology in a way that aligns with community values and standards. Ethics is a large topic with many branches. Occasionally in academia, ethics is connected to academic integrity. The Spokane Community College (SCC) Student Handbook describes another related area of thought, student conduct:

"Students are expected to conduct themselves as responsible members of the academic community. This includes obeying the law, complying with policies, procedures and rules of the district, the colleges and their departments, and maintaining a high standard of integrity and honesty and respecting the rights, privileges and property of others."

(SCC Student Handbook)

As members of the academic community, we should apply this way of thinking to how we interact with technology tools, including those that use GenAI.

Examples of Ethical Use of GenAI Tools in Higher Ed

  • Brainstorming / topical idea generation​
  • Editing / review of documents​
  • Assistance with creative writing​
  • Checking for problems in code​
  • Learning how GenAI works / operates in culture​

Examples of Unethical Use of GenAI Tools in Higher Ed

  • Entering assignments as prompts to have GenAI do all of the work for you​
  • Using GenAI information as credible and authoritative ​
  • Using GenAI tools and providing output information without including a student statement​Copying output from GenAI tools without adding any citations​

Citations and GenAI Tools

Many writing styles have proposed language around GenAI citations and/or statements of use. Due to GenAI tools emerging in between official releases of the style guides, we have yet to see formal adoption in many of the official manuals, but the organizations who manage the styles are contributing resources to support students and researchers. Additionally, citation methods and strategies are being created locally at various schools and organizations. The following are links to two popular styles used at SCC:

You might also find the following guide from Grammarly helpful:

GenAI Problems and Issues

As GenAI becomes more prominent and used across disciplines and contexts, problems and issues with the technology emerge. Some of these problems are ethnical in nature and have to do with the values of the community, including legal constraints. Other problems may be concerned with the hardware and software of the technology. In many cases the lines are blurred and the issues overlap. Below are a few common issues.

  • Hallucinations and lack of citeable sources in some GenAI output​
  • Lack of governmental oversight / common rules​
  • Barriers to access tools, including fiscal costs for best features​
  • Developer safeguards may limit research potential​
  • Bias in data sets and bias in design lead to bias in GenAI output​
  • Violations of intellectual property in data sets, especially visual data; copyright limbo

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Creative Commons License Information

Introduction to GenAI by Greg Bem is licensed under CC BY 4.0