UHN Virtual Library: Generative AI at UHN

Microsoft Copilot in Edge is enabled and available to all of TeamUHN. and it's endorsed and supported by UHN Digital.

What is Copilot in Edge?
Edge is the web browser from Microsoft. It’s the default web browser at UHN. Copilot is Microsoft’s Artificial Intelligence (AI) assistant that uses natural language. Copilot in Edge is the use of Gen AI within the web browser.

Is Copilot in Edge the same as ChatGPT?
ChatGPT – arguably the most well-known Gen AI tool – is owned and developed by OpenAI. Copilot in Edge is Microsoft’s version of ChatGPT. In terms of functionality, they are comparable. One important distinction, however, is that Copilot in Edge can be used in a “Protected” mode, meaning that the data (i.e. whatever you type into Copilot in Edge) is kept within UHN’s custody and protection. Your chats and data are not stored or shared with anyone, and previous chats are not used to improve Copilot in Edge responses.   

Which version of Copilot should I use:
Copilot is approved by UHN only when accessed through the Edge browser or by using the Bing search app on your mobile device. Both methods require you to sign in with your UHN credentials to ensure that you are in the “Protected” mode. If you are not logged in with your UHN credentials, any searches you do are NOT properly secured.

Does ‘Protected mode’ mean I can put anything into Copilot in Edge?
Even though the tool is protected for data safety at this time, we ask that UHN staff do not use any Private or Confidential information, including patient data (PHI - Personal Health Information) employee information, research and education confidential data, corporate confidential information, or intellectual property in their queries.

How to access Copilot in Edge
There are currently 3 main ways to access Copilot in Edge and ensure that you are protected

• Logging in using Copilot.Microsoft.com with your UHN credentials
• Logging in using Edge browser with your UHN credentials
• Using the mobile Bing search engine app on a phone or tablet  

NOTE: Copilot in Edge is different from Copilot for Microsoft 365. Copilot for Microsoft 365 is currently not available or supported by UHN and would require additional licensing. This tool specifically integrates into Office 365 applications and a UHN Digital team is actively assessing these applications. Details will be shared when available.

• Citing GenAI: If you use it, you have to cite it!
  Image at the top of this page was generated using Copilot in Edge.
  Citation:
  Microsoft. (2024, November 7). Image generated by Copilot in Edge. https://copilot.microsoft.com/
  For more examples and guidance see Citing AI generated content created by University of Waterloo Library.

• Fair: ensure that content from these tools does not include or amplify biases and that it complies with human rights, accessibility, and procedural and substantive fairness obligations; engage with affected stakeholders before deployment
• Accountable: take responsibility for the content generated by these tools and the impacts of their use. This includes making sure generated content is accurate, legal, ethical, and compliant with the terms of use; establish monitoring and oversight mechanisms
• Secure: ensure that the infrastructure and tools are appropriate for the security classification of the information and that privacy and personal information are protected; assess and manage cyber security risks and robustness when deploying a system
• Transparent: identify content that has been produced using Gen AI; notify users that they are interacting with an AI tool; provide information on institutional policies, appropriate use, training data and the model when deploying these tools; document decisions and be able to provide explanations if tools are used to support decision-making
• Educated: learn about the strengths, limitations and responsible use of the tools; learn how to create effective prompts and to identify potential weaknesses in the outputs
• Relevant: make sure the use of Gen AI tools supports user and organizational needs and contributes to better outcomes for clients; consider the environmental impacts when choosing to use a tool; identify appropriate tools for the task; AI tools aren’t the best choice in every situation

• Understand the Tool: Familiarize yourself with the capabilities and limitations of the AI tool. This includes understanding the type of tasks it can perform, the data it was trained on, and its ability to understand and generate content.
• Clear Instructions: When interacting with the AI, provide clear and concise instructions. The more specific you are with your request, the better the AI can generate the desired output.For examples see GenAI Prompting Guidance section.
• Iterative Process: Using AI tools is often an iterative process. If the initial output isn’t what you expected, refine your instructions and try again.
• Review Outputs: Always review the outputs generated by the AI. While AI can generate useful and creative content, it’s crucial to ensure the information is accurate and appropriate for your needs.
• Ethical Use: Be mindful of ethical considerations when using AI. This includes respecting copyright laws, avoiding generating harmful or offensive content, and considering the privacy implications of the data you’re working with.
• Continuous Learning: AI tools are continually evolving and improving. Stay updated with the latest advancements and updates to the tool to make the most of its capabilities.

Reminders when using any GenAI tool

• Always verify and validate the accuracy of returned results.
• Do not use any Gen AI tool for any type of clinical care related work, including note taking to put into a chart, generating summaries of patient information, or other. UHN has not validated the use of these tools for medical applications and teams are working on controlled pilots for such use cases.
• Never put Private or Confidential information, including patient data (PHI - Personal Health Information) employee information, research and education confidential data, corporate confidential information, or intellectual property in any Gen AI tool. .

• Persona — Who is asking for the information? Who do you want the AI to be?
• Task — What do you need Copilot on Edge to do for you?
• Context — Any additional information Copilot on Edge could use to generate a more specific response
• Output Format — How do you want Copilot on Edge to format its output (in bullet points, tables, images in a specific style, etc.)?

Prompt examples:

• What might international learners want to know?
  See the Copilot answer...

• As a health care professional, what might international learners want to know?
  See the Copilot answer...

• As a health care professional, what might international learners want to know about working in a hospital in Canada?
  See the Copilot answer...

• As a health care professional, what might international learners want to know about working in a hospital in Canada? Please provide the top 12 best answers.
  See the Copilot answer...

Algorithm: A set of rules or instructions given to an AI, neural network, or other machines to help it learn on its own.

Artificial Intelligence (AI) : The simulation of human intelligence processes by machines, especially computer systems.

Chatbots: Software applications that use natural language processing to simulate human conversation. Chatbots can be rule-based or AI-driven, and they are commonly used for customer service, information retrieval, and personal assistance.

Computer Vision: The ability of artificially intelligent systems to “see” like humans, interpreting and understanding visual input on the computer.

Data Mining: The process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.

Deep Learning: A subset of ML that makes the computation of multi-layer neural networks feasible. It is particularly useful for image and speech recognition tasks.

EHR (Electronic Health Records): Digital records of health information. They contain all the information you’d find in a paper chart — and a lot more.

Gen AI : A subset of artificial intelligence focused on creating new content, such as text, images, music, or code. Gen AI models learn patterns from existing data and use this knowledge to generate novel outputs that resemble the original data.

Generative Pre-trained Transformer (GPT) : A specific type of large language model developed by OpenAI. GPT models are pre-trained on diverse text data and fine-tuned for specific tasks. They are known for their ability to generate coherent and contextually relevant text based on the input they receive.

Healthcare Analytics : The branch of analysis that refers to the use of data-driven findings in healthcare settings to enable healthcare professionals to make informed decisions.

IoMT (Internet of Medical Things) : A connected infrastructure of medical devices, software applications, and health systems and services.

Large Language Model (LLM) : A type of artificial intelligence model designed to understand and generate human language. These models are trained on vast amounts of text data and can perform a variety of language-related tasks, such as translation, summarization, and question-answering.

Machine Learning (ML) : A type of AI that allows a system to learn from data rather than through explicit programming.

mHealth (Mobile Health) : Practice of medicine and public health supported by mobile devices.

Natural Language Processing (NLP) : The ability of a computer program to understand human language as it is spoken or written.

Neural Network: A series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.

Predictive Analytics: The use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data.

Precision Medicine: An approach to patient care that allows doctors to select treatments that are most likely to help patients based on a genetic understanding of their disease.

Reinforcement Learning: A type of machine learning where an agent learns to behave in an environment, by performing certain actions and observing the results.

Robotics: A field of engineering focused on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently.

Supervised Learning: A type of machine learning where the AI learns from labeled training data and makes predictions based on that data.

Telehealth: The use of digital information and communication technologies, such as computers and mobile devices, to access health care services remotely and manage your health care.

Telemedicine: The use of technology to provide healthcare remotely.

Unsupervised Learning: A type of machine learning where AI learns from test data that is not labeled and responds to new situations.