EdD in Educational Leadership: AI and Research

What is generated AI good for and not good for?

Remember, you'll always need to verify the information, because AI will sometimes make things ups (known as "hallucination.")

What is it good for?

• Brainstorming ideas
• Narrowing your topic ideas for a research paper, and keywords for searching in library databases.
  See Generate Topics for Your Research Paper with ChatGPT.
• Explaining information in ways that are easy to understand
• Summarizing and outlining
• Asking questions (be sure to fact check the results) You can ask a million questions without fear of being judged.
• Translating text to different languages (not completely fluent in every language)
• Helping to write or debug computing code

What is it not so good for?

• Library research (not yet). For now, it's best to use Library search, Library databases, or Google Scholar.
• Asking for any information that would have dire consequences if it was incorrect (such as health, financial, legal advice, and so on). This is because of its tendency to sometimes make up answers, but still sound very confident

Adapted from:

 Student guide to ChatGPT. (2023). University of Arizona Libraries,  The Arizona Board of Regents on behalf of The University of Arizona. https://libguides.library.arizona.edu/students-chatgpt/

If you have access to the internet, chances are you've tried out some generative AI tools to create content, like ChatGPT or Dall-E. While it's fun, there are some serious business use cases -- and concerns -- about AI generated content. Watch to learn the notable pros and cons. What do you think? Is AI content doing more harm than good? (Eye on Tech)

Safeguarding Your Integrity

Remember, as a university student, you have a unique opportunity to gather insights from experts, collaborate with peers, and learn from valuable feedback. Embrace the opportunities of being in an environment where you can explore, experiment, and test theories with relatively low risk. Unlike your interactions with GenAI, learning at university provides the additional benefits of human interaction, personal growth, and the chance to build skills that are uniquely your own.

As you contemplate the ethical and responsible use of generative AI in your studies, here are a few guidelines you can follow:

Be Transparent

• Stay Informed: Take the time to understand how generative AI systems work and how they generate content. Knowing their limitations and potential biases will help you make informed decisions about their appropriate use.
• Ask Questions: If you are unsure about using GenAI or about an output it generates, don't hesitate to ask for help. Seek the assistance of someone who might know. An instructor or TA are obvious choices.

Be Fair

• Biased Content: Be mindful of bias in AI-generated content that may perpetuate negative and harmful stereotypes. Seek out AI systems that prioritize diversity and inclusivity in their training data.
• Equal Access: Consider accessibility so everyone benefits equally from the use of AI tools, regardless of background or socioeconomic status.

Be Responsible

• Proper Attribution: Always provide proper credit and citations when using AI-generated content in your academic work. Avoid plagiarism and respect intellectual property rights.
• Think Ethically: Consider the impact of using generative AI on your academic integrity and originality. Make ethical decisions that align with your values and institutional guidelines.
• Be Accountable: Take responsibility for how you use AI-generated content and be aware of any ethical dilemmas that may arise. Being accountable ensures you maintain the highest ethical standards in your work.

When using LLMs like ChatGPT

• Consider ethical implications: Adhere to guidelines set by your instructor, your college or the university.
• Be critical and verify the information: Cross-reference AI-generated content with trusted sources.
• Use multiple sources: Supplement your findings with information from reputable scholarly articles and other reliable sources.
• Start early: Ensure you have enough time to explore a wide range of sources and think critically about varying perspectives.

From: 

“Safeguarding Your Integrity: Understanding Generative AI.” Academic Integrity Tutorial: Learning Activities. University Library. University of Saskatchewan. 6 May 2024. https://libguides.usask.ca/c.php?g=705005&p=5302879

Artificial intelligence technology is not new, but dramatic advances in generative AI have captured the world’s attention and are transforming the information landscape.

This infographic provides an overview of how this technology works and offers six news literacy takeaways to keep in mind as these tools evolve:

1. Generative AI tools are not objective: They are subject to the biases of the humans who make them, and any biases in the training data may show up when they are used.
2. . . .or reliably factual: AI tools might feel authoritative and credible, but the responses they generate are routinely riddled with inaccuracies.
3. It’s not all bad: AI tools also have tremendous upsides. (For example, they can boost scientific research and make complicated or specialized tasks more accessible, like writing computer code or building websites.)
4. Content is easier than ever to create — and fake: AI chatbots and image generators produce text and visuals at an unprecedented scale — and have the potential to supercharge the spread of misinformation. Be ready to encounter even more information with less transparency about its origin.
5. It signals a change in the nature of evidence: The rise of more convincing photos and videos means that determining the source and context for visuals is often more important than hunting for visual clues of authenticity. Any viral image you can’t verify through a reliable source — using a reverse image search, for example — should be approached with skepticism.
6. Reputable sources matter more than ever: Credible sources follow processes to verify information before sharing it, and this should translate into higher levels of trust.

Don’t let AI technology undermine your willingness to trust anything you see and hear. Just be careful about what you accept as authentic.

Source:

6 things to know about AI. (n.d.) News Literacy Project.  https://newslit.org/tips-tools/6-things-to-know-about-ai/

Key Takeaways

While generative AI has the potential to augment your learning at university, it is important to prioritize and uphold the highest standards of academic integrity. Keep in mind that its use comes with both advantages and drawbacks. While it might feel like magic at times, it is essentially a tool that recognizes language patterns very effectively. As with all decision-making, think critically about using AI and recognize that, ultimately, AI is not a responsible entity. The onus, therefore, is on you to uphold ethical standards, verify the information generated by AI, and develop a balanced approach to harnessing its potential.

Points to Remember

Generative AI models do not always produce accurate and truthful information. They can generate content based on learned patterns, but biases in training data, limitations in grasping context, and other factors can lead to the generation of inaccurate or misleading information.

The use of Generative AI in education raises significant privacy concerns. When students interact with AI systems for learning purposes, their data and interactions might be collected, analyzed, and shared by the corporations/companies that own the AI.

Generative AI trained on biased data can amplify or perpetuate those biases. This can result in discriminatory outcomes, possibly reinforcing existing stereotypes and prejudices.

The authorship and copyright of content generated by AI is not always clear. If the input or training data used to train the AI model contains copyrighted material, it is possible that the output data contains the same copyright infringement.

Generative AI models can be used to generate misleading information. Deep fake videos and misinformation can be used to spread false narratives. While AI models themselves are not responsible entities, the individuals who use the information without fact-checking are culpable.

The use of Generative AI can have far-reaching consequences. It can perpetuate bias and discrimination, affect the job market, and inadvertently contribute to the digital divide if access is available to some and not others.

Ultimately, it is your responsibility to be aware of these ethical dilemmas, to carefully consider the implications and to implement strategies that mitigate the potential negative effects of using generative AI in your academic pursuits.

From

“Summary and Key Takeaways: Understanding Generative AI.” Academic Integrity Tutorial: Learning Activities. University Library. University of Saskatchewan. 6 May 2024. https://libguides.usask.ca/c.php?g=705005&p=5302880

We live in a world where advanced technologies known as generative artificial intelligence, or GenAI, can produce art, music and even stories that are almost indistinguishable from those created by humans. Popular examples include ChatGPT, DALL-E and MuseNet. These tools don't only replicate existing work but are designed to generate new or original content based on the patterns learned from the data they are trained on.¹

If this is true, what might the implications be of machine-generated content for artists, musicians, or journalists whose work is used to train GenAI, and for students who take advantage of the content created by GenAI? Some important considerations are

• Who owns AI-generated content?
• How accurate or reliable is AI-generated content?
• What are the ethical implications of using AI-generated content?

Now, consider another aspect - the darker side of AI-generated content. What if these same machines can be used to manipulate information, spread misinformation, or create deceiving deep fakes? As you ponder the world of AI-generated content, ask yourself

• What risks are associated with bias or misinformation in AI-generated content?
• Is Gen AI plagiarizing when it produces content that imitates existing work?
• How does the use of AI in content creation affect the job market for human content creators?
• Is there a need for regulation and oversight of AI-generated content to ensure its responsible use?

“The Big Picture: Understanding Generative AI.” Academic Integrity Tutorial: Learning Activities. University Library. University of Saskatchewan. 6 May 2024. https://libguides.usask.ca/c.php?g=705005&p=5302873