Integration of AI tools into your research

This tab will provide a point of view on the challenges of using AI and how to consider using it to its fullest capacity while maintaining ethical standards. 

Whether you are a general user of this website or a part of the UofA community, please practice the policies your institution has set to maintain academic integrity when using Artificial Tools.

If you are a part of the University of Arizona community please familiarize yourself with the policies set in place as to how to use the tool appropriately as a student and managing as an instructor. More information can be found at the Artificial Intelligence in Teaching and Learning.

Artificial Intelligence in Teaching and Learning will highlight important considerations when it comes to:

• Exploring AI
• Guidance for Syllabus Language
• Talking with Students on AI
• AI Citation and Acknowledgement
• AI Detection Software
• Opportunities, Ethical Issues, and Risks

Bias is defined as "prejudice in favor of or against one thing, person, or group compared with another, usually in a way considered to be unfair."

Artificial Intelligence can have possible biases that it may produce in the instance of only providing information that is the most recent, has the most peer reviews, or provides information specific to only one demographic. 

Controlling for biases is difficult to manage unless you know what type of material you are gathering and appropriately include your target population within your research. Additional bias can accidentally be produced if not enough research is done to thoroughly review the evidence and not find counterclaims to the question at hand.

Generative AI is known to produce bias and users should be aware that not all data is presented equally.

Learn More:

• Bias in AI - Chapman University
• There’s More to AI Bias Than Biased Data - National Institute of Standards and Technology
• About Ethics, Bias, and Transparency for People and Machines - National Institutes of Health
• Machines and Society - New York University Libraries

It is difficult to have an AI tool to operate with 100% accuracy. With some AI models, it is found that they can produce false responses (hallucinations), which can then lead to disinformation, skewed research results, and creating answers that can potentially harm users.

It is important to read forums produced by the AI model company that openly recognize that their model will generate inaccurate results or produce bias and how to avoid these issues. An additional course of action is to locate the generated sources in the journal in which they are published or through a website search.

For the University of Arizona community, you may be able to locate many of these sources through the University of Arizona Libraries or Google Scholar.

Learn More:

• How to Check the Reliability of Artificial Intelligence Solutions—Ensuring Client Expectations are Met - Dr. John Patrick 
• Contextualizing End-User Needs: How to Measure the Trustworthiness of an AI System - Carnegie Mellon University
• Generative AI Reliability and Authority - University of South Florida

• What is hallucination - University of Arizona Libraries

When entering your research question into the AI tool, you will get varied responses depending on how you phrase the question.

An appropriate course of action is to rephrase the question in order to clearly get the appropriate responses. 

The AI model will interpret what it thinks you are asking and that is why users will get varied responses. If you ask for the model to answer a question, it should be noted to ask if it can present citations if the application does not already do so. AI models must continually be trained on how to explain their responses by remaining transparent on information to remain neutral unless instructed by the user to provide strict evidence on their topic. 

Learn More:

• Getting started with prompts for text-based Generative AI tools - Harvard University IT
• Using Generative AI - University of Alberta

Most, if not all, AI models require an account to use their site even if it is free. Some sites allow you to use preexisting accounts you may already have such as Google, Microsoft, and Apple accounts. The sites you allow access to your preexisting accounts could potentially fail if exposed to cyber security attacks harvesting your personal information.

Using a burner accounts or alias does not provide a barrier to your identity when performing academic research.

Using a VPN provides a buffer of security which allows you to stay safe while on the web and downloading resources and is highly recommended for all computers. Click here to access a free VPN download through the UofA(you must be a UA affiliate in order to use this). 

Learn More:

U.S. Copyright law balances the interests of authors who have created works with the interests of users of those works. The purpose of copyright is "to promote the progress of science and the useful arts," while also serving as a form of protection provided to authors of "original works of authorship."

This balance is maintained by the provision of certain rights to authors – such as the right to reproduce, distribute, or prepare derivatives of the work – and the provision of some exceptions and limitations to those entitlements.

The U.S. Copyright Act can be found at Title 17 of the United States Code. The U.S. Copyright Office also provides information on copyright.

Learn More:

• Support for Researchers
  • University of Arizona Library Guide
• Research Engagement drop-ins and workshops

  • Attend a University of Arizona Libraries workshop or drop-in session to learn how to research effectively and engage with useful resources to produce informed and innovative scholarship.