WNF Guide to Using Generative Artificial Intelligence
WNF Guide to Using Generative Artificial Intelligence
Artificial Intelligence (AI) refers to the capability of computer systems or algorithms to imitate intelligent human learning, comprehension, problem solving, decision making and creativity. Learning to use artificial intelligence (AI) tools productively and responsibly is an important part of developing digital literacy and staying current with new technologies that are available.
1.0 Purpose
The WNFGuidetoUsingGenerativeArtificialIntelligenceis a developing/living policy to provide WNF members guidelines on the use of generative artificial intelligence when creating or developing WNF information and documents.
When it comes to the protection and use of WNF information we encourage you to reference the accompanying WNFArtificialIntelligenceandConfidential InformationandIntellectualPropertyPolicy. We have provided a number of resources at the end of this document that provide additional information on guidelines, cautions and challenges with Generative AI Tools.
1.1 Areas where Generative AI Tools may be Beneficial
AI is an important tool that can have benefits in areas such as:
● Translation of research articles
● Verification of copyright.
● Assisting with citation management.
● Grammatical editing.
● Formalization of information.
2.0 Guiding Principles for Generative AI Tools
The following are the guiding principles that will ensure safe and effective use of AI.
2.1
Cautions and Guidelines
Although there are benefits to AI, it is important that it is used with caution and that the results are always checked and verified. General guidelines include:
● Factual Correctness: AI often changes the meaning of a sentence when improving grammar or comprehension - critically reviewing any AI edits for factual correctness and meaning are imperative.
● Poor References: AI can be a very poor reference source. Academics and researchers still need to be across the literature and scholars in the field.
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WNF Guide to Using Generative Artificial Intelligence
● Confidentiality Concerns: Be extremely careful with putting any of your own writing into AI with an undefined sandpit - when checking grammar or spelling. For example, some AI programs when used under an institutional agreement keeps your data confidential (in a defined sandpit) but can still be read by the host program. Please refer to the WNFArtificialIntelligenceandConfidential InformationandIntellectualPropertyPolicyas it relates to and WNF information.
● Lack of Transparency: The use of AI tools in the generation of work must be declared to the WNF and within any projects that are undertaken.
● Plagiarism: Avoid copying and pasting directly from AI tools due to the high risk of plagiarism.
● Privacy Breach: AI tools may transmit or store data without user awareness.
● Research Compliance: Research journals will have specific guidelines on how AI can be used when creating research papers and/or when reviewing research papers. We encourage you to familiarize yourself with the guidelines.
● Mis-Information (Hallucinations): Keep in mind that AI algorithms can make up information when posed with an inquiry. Made-up information is referred to “hallucinating”. It is important that all information generated from AI programs is verified.
● Authorship: AI should not be listed as an author.
2.2 Key Recommendations
Choose tools that protect user data. The various GAI tools offer different levels of user protection. Review the terms and conditions of the GAI tools that you are using. Apply settings that prevent the GAI tool from using your data for training purposes and that ensure privacy and the ability to disable your history.
Utilize GAIs as Supportive Tools, Not as Substitutes: While GAIs can be very useful for brainstorming research topics, refining research questions, and identifying keywords, they should not be used to generate complete academic papers or to locate primary sources of information.
WNF Guide to Using Generative Artificial Intelligence
Be Transparent About the Use of GAIs:
All users of GAI should explicitly declare when they have used generative AI tools in their work. This transparency upholds professional and academic integrity and enables work to be assessed appropriately.
Develop Critical Evaluation Skills:
It is essential to verify the accuracy, credibility, and relevance of AIgenerated content using reliable sources. Users must be aware of potential biases in the training data of AI models and, consequently, in their responses.
Focus on Developing Information Research Skills:
The ability to formulate effective research questions and to conduct strategic searches in academic databases remains fundamental. GAIs can complement these skills but should not replace them.
Use GAIs to Enhance Learning and Teaching: Educators can leverage GAIs to generate ideas for classroom activities and explore diverse technological applications with students. This approach not only demystifies AI but also illustrates both its potential and its limitations.
Recognize the Parallels Between Prompt Engineering and Research: Crafting effective prompts for AI is analogous to developing clear, focused research questions. This process can be harnessed to reinforce students’ research skills and critical thinking.
References:
1.Boyle, Christina. "ChatGPT, Gemini, & Copilot: Using generative AI as a tool for information literacy instruction." TheReferenceLibrarian(2025): 1-17.
2. Jiao, Junfeng, et al. "AGGA: A Dataset of Academic Guidelines for Generative AI and Large Language Models." arXivpreprintarXiv:2501.02063(2025).
3.0 Using Artificial Intelligence (AI)
3.1 Writing Effective Prompts for Large Language Models (LLM)
A promptis the instruction or question you give to a large language model (LLM) to guide its response. It can be a single sentence or a structured set of commands. The way you write a prompt directly affects the quality, accuracy, and relevance of the
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WNF Guide to Using Generative Artificial Intelligence
output. Writing effective prompts is essential to getting meaningful results from AI. According to guidance from the MIT Sloan School of Management’s EdTech Lab, well-designed prompts help bridge human intention with machine logic, reducing misunderstandings and increasing output value.
1. Be Clear and Specific: Avoid vague prompts. Add context, timeframe, and format.
“TellmeaboutAI”→“ComparemachinelearninganddeeplearninginAI.”
2. Ask for Sources: Request real citations in a specific style (APA, MLA). Always verify them.
3. Use Step-by-Step Instructions: Break tasks into numbered steps for clarity.
List>Summarize>Analyze
4. Limit Scope: Narrow the topic to avoid irrelevant info. “FocusonCRISPRresearchafter2020.”
5. Stay Neutral: Avoid biased or leading questions. “Discussprosandcons,”not“Provethisisbad.”
6. Validate Outputs: Always double-check facts. Use trusted sources or experts for complex topics.
7. Use Feedback Loops: Refine your prompt based on the output. Ask the model what might be missing.
8. Mind the Context Window: LLMs have token limits. Keep prompts concise and reintroduce context if needed.
More information on: https://mitsloanedtech.mit.edu/ai/basics/effective-prompts/
4.0 Exploring Different AI Tools
There are numerous AI tools available today, each offering distinct strengths and limitations depending on their design and intended use.
It is important to note that different versions of the same model can produce varying results, so understanding the characteristics and capabilities of each is
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WNF Guide to Using Generative Artificial Intelligence
essential for effective use. Likewise, users should be aware of the differences between free and paid versions of AI tools, especially with respect to data confidentiality. Paid enterprise or institutional versions often offer more secure environments with stricter privacy safeguards, while free or public models may process data in less controlled contexts, potentially exposing sensitive content.
Periodically the WNF will review some of the common GAI tools that are available and will provide an internal list for staff, committee members and volunteers to reference. That being said, the WNF does not officially endorse any specific GAI tool. It is important that each user assess the various GAI tools available to them and choose the one that is most appropriate for their task.
5.0 Comprehensive Glossary of AI Concepts
5.1 Foundational
Concepts
● Artificial Intelligence (AI): The field of computer science dedicated to creating systems capable of performing tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.
● Machine Learning: A subset of AI where algorithms improve automatically through experience. Instead of being explicitly programmed to perform a task, these systems learn from data to make predictions or decisions.
● Deep Learning: A specialized form of machine learning using neural networks with multiple layers (deep neural networks) to analyze various factors of data with a structure similar to the human brain.
● Training Data: The datasets used to teach AI models patterns and relationships. The quality, diversity, and volume of training data directly impact the accuracy, fairness, and capability of the resulting AI system.
5.2 Language AI Concepts
● Large Language Models (LLMs): Advanced AI systems trained on vast text datasets that can understand, generate, and manipulate human language. Examples include GPT (ChatGPT), Claude, Gemini, and Llama.
● Generative AI: AI systems that create new content such as text, images, audio, or video by learning patterns from existing data. These systems can produce original outputs rather than simply analyzing or categorizing existing information.
WNF Guide to Using Generative Artificial Intelligence
● Transformer Architecture: The breakthrough neural network design behind most modern LLMs, using attention mechanisms to process relationships between all words in a sequence simultaneously rather than sequentially.
● Prompt: The input text given to an AI system to guide its response. The quality and structure of prompts significantly affect the usefulness of AI outputs.
● Prompt Engineering: The strategic craft of designing inputs to AI systems to achieve desired outputs. This involves understanding model capabilities, limitations, and response patterns to create effective instructions.
● Context Window: The amount of text an AI model can consider at once when generating responses, measured in tokens (roughly 4 characters per token). Larger context windows allow the AI to reference more information.
5.3 AI Capabilities and Limitations
● Hallucinations: Cases where AI systems generate content that appears plausible but contains factual errors, made-up references, or information not grounded in reality.
● Fine-tuning: The process of further training a pre-trained AI model on a specific dataset to specialize its capabilities for particular tasks or domains.
● Retrieval-Augmented Generation (RAG): A technique that enhances AI outputs by combining the model's trained knowledge with information retrieved from external sources or databases.
● Multimodal AI: AI systems capable of processing and generating multiple types of data such as text, images, audio, and video, allowing for more versatile applications.
6.0 External Resources
The field of GAI is changing rapidly. Below are some resources that you may find useful.
1. Innovation and Generative Artificial Intelligence: a problem in sight
○ Website: https://understandingai.iea.usp.br/nota-critica/inovacao-e-iagenerativa-um-problema-a-vista/
2. King's College London - Generative Artificial Intelligence
○ Guidance for doctoral students, supervisors and examiners
3. Understanding Artificial Intelligence - University of São Paulo
○ Website: https://understandingai.iea.usp.br/
WNF Guide to Using Generative Artificial Intelligence
4. University of Sydney, Australia - Artificial Intelligence
○ Website: https://www.sydney.edu.au/students/academicintegrity/artificial-intelligence.html
5. YouTube Video: Artificial Intelligence and Traditional Medicine by Dr Caio Portella, Naturopath
○ Website: https://www.youtube.com/watch?v=F2AQQUBrp6Y&themeRefresh=1
6. World Health Organization - Harnessing Artificial Intelligence for Health
○ Website: https://www.who.int/teams/digital-health-andinnovation/harnessing-artificial-intelligence-for-health
7. Stanford University - Human-Centered AI Institute
○ Website: https://hai.stanford.edu/education/ai-resources
8. MIT - Introduction to Artificial Intelligence
○ Website: https://ocw.mit.edu/courses/electrical-engineering-andcomputer-science/6-034-artificial-intelligence-fall-2010/
9. The Royal Society - Machine Learning Report
○ Website: https://royalsociety.org/topics-policy/projects/machinelearning/
10.arXiv.org - Computing and Language Section
○ Website: https://arxiv.org/list/cs.CL/recent
11.Journal of Artificial Intelligence Research (JAIR)
○ Website: https://www.jair.org/
12.OpenAI Technical Papers
○ Website: https://openai.com/research
13.Anthropic - AI Research
○ Website: https://www.anthropic.com/research
14.Microsoft Research
○ Website: https://www.microsoft.com/en-us/research/researcharea/artificial-intelligence/
15.Google AI Blog & Research
○ Website: https://ai.googleblog.com/
16.AI Ethics Lab
○ Website: https://aiethicslab.com/resources/
17.UNESCO - Recommendation on the Ethics of AI
○ Website: https://www.unesco.org/en/artificialintelligence/recommendation-ethics
18.IEEE - Global Initiative on Ethics of Autonomous and Intelligent Systems
○ Website: https://standards.ieee.org/industryconnections/ec/autonomous-systems/
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WNF Guide to Using Generative Artificial Intelligence
19.OECD AI Policy Observatory
○ Website: https://oecd.ai/
20.National Institute of Standards and Technology (NIST)
○ Website: https://www.nist.gov/artificial-intelligence
7.0 Policy Approval
7.0 Effective date: May 14, 2025
8.0 Disclaimer
This document provides general guidance on the integration of AI into naturopathic practice and should not be construed as legal or clinical advice. WNF staff, committee members and WNF volunteers are responsible for ensuring the appropriateness of AI use within their scope of work on behalf of the WNF. The WNF does not accept liability for the use of AI technologies. Use of any AI-enabled system or tool is at the discretion of WNF staff, committee members and volunteers.
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