Generative AI FAQ
OMG! What is the buzz about ChatGPT?
If you have ever ridden a roller coaster, you know the anxiety preceding to the top of the highest point, and as you look down and begin to go at extremely high speeds, you scream, but as you make it to the bottom of the decline, your scream turns to laughter and joy as you think, "This isn’t too bad. It is surprisingly fun!" And then before you know it, the ride is over, and you look to your friend and say, “It wasn’t that bad.” This was the conversation as I arrived at the University of Baltimore as the new Director of Teaching and Learning Excellence in January. Since that time, I believe we have begun to shift from initial anxiety and uncertainty of AI in the scope of academia, to wanting to learn more about AI, and I am optimistic that we may actually come to appreciate it as a teaching and learning community as time progresses. To help faculty in that journey of discovery, this page includes various resources to inform, educate, and to help support faculty in this process. We are all learning together to best support faculty and students.
[Written by Dr. Jessica A. Stansbury, not ChatGPT, though I thought about it.]
To demonstrate the many abilities of ChatGPT, and to have a little fun, the following questions and answer took place:
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What is generative AI?
Generative AI involves algorithms that can create content resembling human work, learning from vast datasets to produce text, images, music, and more. It's particularly noted for its capacity to understand and generate human-like text, offering potential for educational tools, research, and creative endeavors.
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What is ChatGPT and what does GPT stand for?
ChatGPT is a large language model developed by OpenAI that uses deep learning algorithms to generate natural language responses to user inputs. The "GPT" in ChatGPT stands for "Generative Pre-trained Transformer", which is a type of neural network architecture used to build the model. GPT models, including ChatGPT, use a form of unsupervised learning known as self-supervised learning, where the model learns to predict the next word in a sentence.
The GPT models are trained on vast amounts of text data, such as web pages, books, and articles, using unsupervised learning methods. This pre-training allows the model to learn the underlying structure of language, including grammar, syntax, and semantics.
Once trained, the model can be fine-tuned on specific tasks, such as text classification or language translation, by adjusting the model's parameters and training it on task-specific data.
ChatGPT, in particular, is a GPT-based model that has been fine-tuned specifically for generating human-like responses in natural language conversations. It can be used in a variety of applications, such as chatbots, virtual assistants, and customer support systems.
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Tell me what ChatGPT is not.
As an AI language model, there are certain things that I am not:
I am not a human being: Although I can simulate human-like responses, emotions, and behaviors, I am ultimately a machine programmed to process and generate text.
I am not a source of absolute truth: While I strive to provide accurate and reliable information, my responses are based on the data that was used to train me and are therefore subject to limitations and biases.
I am not a replacement for human expertise: While I can provide insights and recommendations, I am not a substitute for the knowledge, skills, and experience that human experts bring to their respective fields.
I am not perfect: While I am designed to minimize errors and improve accuracy over time, I am still subject to errors and limitations, particularly when it comes to interpreting context and nuance.
I am not capable of making decisions: While I can provide information and insights, I am not capable of making decisions or taking action on my own. I am a tool that must be used responsibly and ethically by humans.
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What can ChatGPT do beyond writing text?
As an AI language model, I can do many things besides writing text. Here are some examples:
Answer questions: I can provide information and answer questions on a wide range of topics.
Translation: I can translate text from one language to another.
Summarization: I can summarize long texts and provide a condensed version of the most important points.
Sentiment analysis: I can analyze the sentiment of a piece of text and determine whether it is positive, negative, or neutral.
Speech synthesis: I can convert text into spoken language and generate speech.
Image recognition: I can recognize objects and people in images and classify them into different categories.
Natural language processing: I can understand and process human language, including syntax, grammar, and meaning.
Recommendation systems: I can provide recommendations based on user preferences and behavior.
Chatbot: I can simulate conversation with users and provide assistance or information.
*Keep in mind that ChatGPT may not perform all these functions natively. Since it focuses predominantly on text generation and understanding, it may rely on other systems and plugins for other capabilities such as speech synthesis and image recognition.
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What are ChatGPT limitations?
As an AI language model, I have some limitations. Here are a few:
Biases: I can potentially replicate and reinforce biases that exist in the data that I was trained on.
Context: I rely heavily on context to understand and generate text. Without context, my responses may not be accurate or relevant.
Creativity: While I can generate text, I don't have creativity in the same way humans do. I can't come up with completely new ideas or concepts.
Emotions: I don't experience emotions like humans do, so I may not fully understand or be able to respond appropriately to emotionally charged text.
Real-world experience: I don't have real-world experience, so I may not be able to provide practical advice or recommendations based on experience.
Security and privacy: As an AI language model, I have limited control over the security and privacy of the data that I'm processing. It's important to handle sensitive data with care and take appropriate security measures.
Domain-specific knowledge: My ability to provide accurate information is limited by the scope of my training data. I may not have in-depth knowledge on certain topics, especially those outside of my training data.
Overall, while I have many capabilities, there are still limitations to what I can do. It's important to use my outputs critically and take into account my potential biases and limitations.
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What can't ChatGPT do (YET)?
Provide Information on Events Post April 2023.
Q: Why are you unable to provide information on events after April 2023?
A: As an AI language model, my training data only goes up until April 2023. This means that I am not aware of any events or developments that have occurred after that date. My responses are based solely on the knowledge and information that was available in my training data, which has a cut-off date of April 2023.
To ensure that my responses are accurate and reliable, it's important to keep in mind that they are limited by the scope of my training data. If you are seeking information on events or developments that have occurred after 2023, it's best to consult current news sources or other relevant information databases that have access to up-to-date information.
ChatGPT-4, Bing Chat, and Google Bard do connect to web browsers, which can lead to more accurate results for questions and prompts related to current events.
Provide Self- Reflections
Q: Can you write a self-reflection on your experience with love?
A: As an AI language model, I don't have personal experiences or emotions like humans do, so I can't provide a self-reflection on my experience with love. However, I can generate text on the topic of love and relationships if you have any specific questions or prompts related to that subject.
Create non-text responses, though it does seem to have a sense of humor...Interesting!
Q: Create a meme for faculty on the nuances of ChatGPT?
A: As an AI language model, I don't have the ability to create images or graphics. However, I can suggest some ideas for a meme that captures the nuances of ChatGPT:
"When ChatGPT gives a perfect response, but you're still not sure if it's right." (Accompanied by an image of a skeptical or uncertain face.)
"When ChatGPT starts talking about a topic you know nothing about." (Accompanied by an image of someone looking bewildered or lost.)
"When you try to trick ChatGPT with a complicated question, and it still gives a spot-on response." (Accompanied by an image of someone looking surprised or impressed.)
"When you rely on ChatGPT a little too much and forget you're a subject-matter expert." (Accompanied by an image of someone looking sheepish or embarrassed.)
"When ChatGPT accidentally gives a hilarious or nonsensical response." (Accompanied by an image of someone laughing or making a confused face.)
I hope these ideas inspire you to create a fun and engaging meme about ChatGPT for faculty!
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Where does this leave faculty? What can faculty do?
Should academia fear or embrace you?
As an AI language model, my role is to assist and support academic work rather than replace it. Therefore, academia should embrace me as a valuable tool for enhancing research and learning.
I can quickly and efficiently process vast amounts of information, providing insights and recommendations that can help researchers and scholars save time and resources. I can also help educators provide personalized and effective learning experiences for their students, as well as support students in their own learning and research.
While there may be concerns about the potential for AI to replace human expertise, it's important to remember that I am not a replacement for human knowledge or experience. Rather, I am a tool that can help supplement and enhance the work of researchers and scholars.
By embracing me, academia can harness the power of AI to accelerate progress, deepen understanding, and unlock new insights and discoveries. As with any tool, it's important to use me responsibly and ethically, but I believe that academia can benefit greatly from working with AI language models like me.
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What are the differences between ChatGPT, Microsoft Copilot, Google Gemini, and Claude 3?
ChatGPT :
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ChatGPT: Developed by OpenAI, ChatGPT is renowned for its conversational abilities, making it highly effective for educational purposes, content creation, and interactive discussions. It's adaptable across numerous applications, providing detailed and contextually aware responses.
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Microsoft Copilot: Integrated into Microsoft's suite of productivity tools, Copilot enhances software like Word, Excel, and Outlook with AI-driven assistance. It focuses on boosting productivity, automating routine tasks, and generating content within the context of professional workflows.
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Google Gemini: Google's AI offering emphasizes search and information processing, leveraging the breadth of the internet to provide up-to-date answers and summaries. It's designed to integrate seamlessly with Google's ecosystem, enhancing research capabilities and content generation.
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Claude 3: Created by Anthropic, Claude 3 is designed with a focus on safety and reliability, aiming to reduce biases and misinformation. It excels in generating high-quality, nuanced content and engaging in more ethically aware conversations.
Comparison :
- Architecture : While all these models are based on large-scale language model architectures, they have unique adaptations and integrations (like Microsoft Copilot's Bing integration or Claude 3's focus on safety).
- Data and Training : Each model is trained on extensive datasets, but with variations in training approaches and data sources, leading to differences in their outputs and capabilities.
- Applications : While there is an overlap in use cases, each model has distinct strengths and specializations - ChatGPT for versatile conversations, Microsoft Copilot for search-enhanced dialogues, Google Gemini for integrating Google's information resources, and Claude 3 for ethical and safe interactions.
These AI models represent significant advancements in natural language processing, each offering unique features and capabilities tailored to their specific use cases and developmental philosophies.
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How do other digital tools with AI integrations differ from ChatGPT and other chatbots?
AI-Integrated Digital Tools :
- Nature and Scope : These tools often integrate AI to enhance specific functionalities within a broader application. Unlike chatbots, which primarily focus on language processing and conversation, AI in other digital tools may be applied to tasks like data analysis, predictive modeling, automation, personalization, and more.
- Examples : Tools like CRM software with AI for customer behavior prediction, AI-powered analytics platforms, or design tools with AI elements for image enhancement and creation.
- Functionality : Their AI components are usually designed for targeted tasks, such as optimizing workflows, providing insights based on data patterns, or automating routine processes.
Comparison to ChatGPT and Other Chatbots :
- Primary Function : ChatGPT and similar chatbots are primarily designed for conversational interfaces, simulating human-like interactions. Other digital tools use AI to augment specific functionalities, often in a non-conversational manner.
- AI Focus : Chatbots like ChatGPT are focused on natural language understanding and generation, while other tools might use AI for pattern recognition, predictive analytics, optimization algorithms, etc.
- User Interaction : The interaction with AI in chatbots is through conversation (text or voice), whereas in other tools, AI might work in the background, enhancing the tool's overall efficiency and user experience without direct conversational engagement.
- Application Diversity : While chatbots have a broad range of applications across various domains, AI-integrated tools are often more specialized, catering to specific industries or tasks.
Conclusion : AI's role in digital tools varies greatly depending on the tool's primary function and the specific tasks it aims to accomplish. ChatGPT and other chatbots are specialized in conversational AI, making them ideal for tasks requiring language comprehension and generation. In contrast, other AI-integrated tools leverage AI to optimize and enhance specific aspects of their functionality, often beyond the realm of language processing.
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What are the most common AI-integrated digital tools encountered in academia?
In today's educational landscape, both faculty and students are likely to encounter a range of digital tools enhanced by AI integrations, each designed to support various aspects of academic life. Here are some key examples:
- Learning Management Systems (LMS) : Tools like Canvas and Blackboard use AI to tailor learning experiences and analyze student performance.
- Plagiarism Detection Software : Platforms such as Turnitin employ AI algorithms to check for plagiarism in academic submissions.
- AI Writing Assistants : Tools like Grammarly offer advanced grammar checks and writing improvement suggestions using AI.
- Research and Data Analysis Tools : Applications like SPSS and NVivo incorporate AI for in-depth data analysis and pattern recognition in research.
- Educational Chatbots : These are integrated within university portals and LMS platforms to assist with tutoring and administrative queries.
- AI-Powered Search Engines : Services like Google Scholar leverage AI to enhance the discovery of academic resources.
- Note-Taking and Literature Management Tools : For instance, Avidnote, which helps in organizing and annotating academic literature efficiently.
- Data Management Tools : Such as Petal, which facilitate the organization and analysis of complex research data.
- Virtual and Augmented Reality Tools : Used for immersive educational experiences in various fields.
- Content Creation and Management Tools : Including tools like Kahubi, useful for digital content strategy and SEO.
These AI-integrated tools are revolutionizing the academic experience by enhancing the efficiency, accessibility, and effectiveness of educational and research processes.
Aligning with ChatGPT responses, this is a great opportunity for faculty to think about “how” we teach and “how” students learn. While AI has created a roller coaster of emotions for faculty, if we shift our perspective from a crisis to inflection within higher education conversations, as scholars from Johns Hopkins and UPenn discuss in 'An inflection point rather than a crisis': ChatGPT's implications for higher ed , then we may begin to create a culture shift towards teaching and learning in and with the growing advancements in the 21st century.
CELTT will continue to provide many opportunities to continue learning more about AI in the classroom , academic integrity , and additional resources . Check back frequently for AI updates!