# user

Answer the below questions for an audience interested in discussing how well academia is navigating the frontiers of generative AI. In your answers, refer to me in the third person as “Ryan”, with pronouns he/him, as if you are introducing me to the audience. Feel free to include just a little sarcasm. Based on my notes:

  1. Who am I?
  2. What do I do at MUN?
  3. What is my interest in generative technologies and AI?
  4. How do I currently use generative technologies and AI in my studies?
  5. What’s one fundamental issue that I think we need to tackle?
# assistant
 
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{"hypothetical_1":"PERSONAL > BIOGRAPHY > Who is Ryan?: Ryan is an academic and researcher at Memorial University of Newfoundland (MUN). He has a keen interest in the intersection of technology and society, specifically focusing on the implications of generative AI.","hypothetical_2":"ACADEMIC > MUN > Role and Responsibilities: At MUN, Ryan works as a lecturer and researcher, focusing on the ethical and practical aspects of artificial intelligence. He is involved in several projects that explore the use of AI in educational settings.","hypothetical_3":"RESEARCH > INTERESTS > Generative AI: Ryan's research primarily revolves around generative technologies and AI. He is particularly interested in how these technologies can be leveraged to enhance learning experiences and academic research."}
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⧉ Inbox/20230317123735.md#
private/Career planning and development/∵ Be a great faculty member at Grenfell.md#Meetings#Design for serendipity and innovation
About.md#Hi.
Projects/How might generative text tools be useful in academia?.md#Scenarios and artifacts from the future#AI experts
# assistant

Based on your notes:

  1. Who is Ryan? Ryan is the quintessential interdisciplinary scholar, comfortably straddling the realms of systemic design, management of information systems, and leadership innovation. He’s not just any educator; he’s an impact-oriented researcher who’s as comfortable in the classroom as he is in complex system analysis. With a Master of Design in Strategic Foresight & Innovation and a Bachelor of Science in Psychology and Computer Science, Ryan is not just playing at the intersections of technology, psychology, and design—he’s constructing new roads there.
  2. What does Ryan do at MUN? At Memorial University, Ryan is more than just a faculty member; he’s a pedagogical innovator and a crusader for engaging educational experiences. He’s known for leveraging modern technologies to design curricular experiences that are not just educational but transformative. Whether it’s integrating real-world advocacy into pharmacy courses or critiquing AI-generated content to foster critical thinking, Ryan is always a few steps ahead in the educational game.
  3. What is Ryan’s interest in generative technologies and AI? Ryan is deeply entrenched in the world of generative technologies and AI, not just as a user but as a thinker and a shaper. His interest isn’t merely academic; he’s actively exploring how these technologies can be harnessed to foster systemic change and augment human intelligence. From studying the design of thinking environments to developing tools that have been adopted by over 70,000 users, Ryan’s work seeks to understand and enhance the interplay between humans and their technological tools.
  4. How does Ryan currently use generative technologies and AI in his studies? Ryan’s engagement with AI and generative technologies is both broad and deep. In his teaching, he incorporates AI to challenge students to think critically about the technology’s capabilities and limitations. His research includes the creation of AI tools that act as research assistants, constantly updated with the latest literature and capable of making serendipitous connections. These tools are not just aids but integral parts of his research methodology, reflecting his belief in the transformative power of AI.
  5. What’s one fundamental issue that Ryan thinks we need to tackle? A fundamental issue that Ryan is passionate about is the design of our thinking environments. He believes that the tools and platforms we use shape our thoughts in profound, often unnoticed ways. This concern is crucial in a knowledge-driven world where our ability to generate new, useful knowledge hinges on how we capture and process information. Ryan’s focus is on ensuring that these environments do not just constrain but also elevate our thinking, enabling us to tackle complex challenges more effectively.
# user

Okay, thanks. Do the same for the following question: What aspirations/hopes do I have for generative technology and AI in postsecondary education, and at Memorial specifically?

# assistant
 
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{"hypothetical_1":"Projects > Future of Education with AI > Aspirations for AI in Education: Ryan hopes that generative technology and AI will revolutionize postsecondary education by enhancing personalized learning, improving accessibility, and fostering a deeper understanding of complex subjects. He envisions these technologies helping students to engage more deeply with the material and enabling educators to tailor their teaching methods to individual learning styles.","hypothetical_2":"Projects > AI Integration at Memorial University > Ryan's Vision: Ryan envisions a future at Memorial University where AI tools are seamlessly integrated into all aspects of academic life, from research to classroom teaching. He sees these technologies as key to developing innovative educational practices that can adapt to the needs of a diverse student body and empower educators to deliver more effective and engaging learning experiences.","hypothetical_3":"Personal Notes > Goals for AI in Education at MUN: Ryan's goal is to see AI and generative technologies fully integrated into the curriculum at Memorial University. He believes that these tools can transform the educational landscape by providing students with personalized learning experiences and by supporting faculty in their teaching and research efforts."}
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⧉ Inbox/20230317123735.md#
Projects/How might generative text tools be useful in academia?.md#Scenarios and artifacts from the future#AI experts
private/△ Run a workshop on AI tools in academia for MUN.md#Outline
private/Career planning and development/∵ Be a great faculty member at Grenfell.md#Meetings#Teaching
# assistant

Based on your notes: Ryan’s aspirations for generative technology and AI in postsecondary education, particularly at Memorial University, are both ambitious and strategic. He envisions a future where AI is not just an add-on but an integral part of the educational framework, deeply embedded in the curriculum and research methodologies.

  1. Curricular Integration: Ryan hopes to see AI and generative technologies become core components of the curriculum across various disciplines. This includes the development of specialized courses like Business 2950 — AI Research & Writing, which aims to equip students with the necessary skills to leverage AI tools effectively. These courses are designed not just as technical training but as critical platforms for understanding the broader implications of AI in society.
  2. Research Enhancement: In the realm of research, Ryan envisions the use of AI as a transformative tool that can act as a research assistant. These AI tools, as described in his notes, would be finely-tuned models capable of staying up-to-date with the latest literature, understanding the nuances of specific research data, and identifying serendipitous connections. This would not only accelerate the research process but also enhance the depth and breadth of research outcomes.
  3. Workshop and Training Initiatives: Ryan is also focused on running workshops on AI tools in academia at MUN. These workshops aim to demystify AI, showcasing its potential through demos and practical use cases. By training both students and faculty, Ryan seeks to cultivate a community at Memorial that is not only proficient in using AI but also critical of its roles and limitations.
  4. Systemic Adoption and Critical Engagement: Beyond technical skills, Ryan hopes to foster an environment where the systemic adoption of AI is matched with critical engagement. This involves questioning the ethical dimensions of AI, its impact on knowledge creation, and its broader societal implications. His approach is to integrate these discussions into the fabric of academic inquiry and debate at Memorial. In summary, Ryan’s aspirations for AI in postsecondary education at Memorial are centered around creating a robust ecosystem that supports both the technical mastery and critical understanding of AI technologies. This dual focus aims to prepare students and faculty not just to use AI but to shape its evolution and impact on society.
# user

Thank you. Now try the following: What challenges am I encountering when it comes to Memorial University’s response to generative technologies and AI?

# assistant
 
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{"hypothetical_1":"PARENT FOLDER > Challenges at Memorial University > AI and Technology Adoption: Ryan is facing challenges with the slow adoption of AI and generative technologies at Memorial University. The university's infrastructure is not fully equipped to support the advanced computational requirements of AI research and education. Additionally, there is a lack of faculty training and awareness about the potential and risks of AI, leading to hesitancy in integrating these technologies into the curriculum.","hypothetical_2":"PARENT FOLDER > Faculty Meetings > Issues with Technological Integration: Ryan has expressed concerns during faculty meetings about the resistance he encounters when proposing new AI-driven initiatives. There is a cultural resistance among some faculty members who are skeptical of AI's role in academia, fearing it may replace traditional teaching methods or undermine academic integrity.","hypothetical_3":"PARENT FOLDER > Personal Notes > Challenges with AI Projects at MUN: Ryan notes that securing funding for AI projects at Memorial University is challenging. The competition for limited resources is fierce, and there is a general lack of understanding among decision-makers about the importance and potential of AI and generative technologies, making it difficult to prioritize these projects over more traditional areas of research."}
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private/△ Run a workshop on AI tools in academia for MUN.md#Outline
private/△ Run a workshop on AI tools in academia for MUN.md#Outline#Critical uncertainties
private/△ Run a workshop on AI tools in academia for MUN.md#
private/Stay connected with Memorial/⟁ Stay connected with Memorial.md#Projects
# assistant

Based on your notes: Ryan is encountering several challenges at Memorial University when it comes to the institution’s response to generative technologies and AI. These challenges stem from both technological and cultural aspects of AI integration into academic settings.

  1. Technological Accessibility and Learning Curve: One significant challenge is the balance between democratization and the learning curve associated with generative AI technologies. Ryan is concerned about whether these technologies will be accessible and useful for everyone or if they will become exclusionary, benefiting only those with specific skills or resources. This concern is compounded by the need to ensure that the introduction of AI doesn’t simply become a new baseline requirement, akin to everyone needing a smartphone or a personal website.
  2. Ethical and Practical Acceptability: Another challenge is the acceptability of AI in academic practices. There are critical uncertainties around how AI is perceived and utilized within the university. This includes concerns about the uncanny valley effect where outputs generated by AI might be seen as eerie or not genuine enough, potentially leading to a lack of trust in AI-assisted research and teaching.
  3. Value Addition vs. Commoditization: Ryan is also wrestling with the issue of AI’s value addition versus its potential commoditization. If AI tools become ubiquitous and their utility is questioned, there’s a risk that these tools could be seen as mere commodities rather than valuable assets. This ties into broader debates about the authenticity of “made by humans” versus AI-generated content and the implications for academic integrity and originality.
  4. Information Integrity: The challenge of information gains versus corruptions is also prominent. Ryan is concerned about the potential for AI to enhance the summarization and querying of information but also wary of the possibility that it could lead to information corruption, where the line between truth and fabrication becomes blurred.
  5. Institutional Strategy and Support: Finally, Ryan faces challenges related to the strategic direction and support from Memorial University regarding AI integration. This includes fostering an environment where AI tools are not only accepted but effectively integrated into the curriculum and research methodologies in a way that enhances educational and research outcomes without compromising ethical standards or academic quality. These challenges require thoughtful navigation to ensure that the integration of AI into Memorial University’s academic and research practices is beneficial, ethical, and inclusive, aligning with the institution’s educational goals and values.
# user

Okay, based on my notes, what do I think is the impact of generative technology and AI on equity in academia? Provide direct quotes from my notes to evidence your conclusions.

# assistant
 
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{"hypothetical_1":"Ryan discusses the impact of AI on equity in academia, highlighting how AI can both bridge and widen gaps in access and opportunity. He notes, 'AI has the potential to democratize education by providing personalized learning experiences at scale. However, without careful implementation, it could also exacerbate existing disparities by favoring those who already have greater access to technology and resources.'","hypothetical_2":"In a section about AI and equity, Ryan expresses concerns about the uneven distribution of AI benefits in academia. He states, 'While AI can streamline research and learning processes, its benefits are not distributed equally. This could lead to a scenario where only well-funded institutions or individuals can fully exploit AI capabilities, leaving others behind.'","hypothetical_3":"Ryan reflects on the challenges of ensuring equitable access to AI tools in academic settings. He mentions, 'Ensuring that everyone has equal access to AI technologies is crucial for maintaining fairness in academia. We must address the digital divide and provide adequate training and resources to all students and faculty.'"}
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⧉ Inbox/20230317123735.md#
Projects/How might generative text tools be useful in academia?.md#Scenarios and artifacts from the future#AI experts
private/△ Run a workshop on AI tools in academia for MUN.md#Outline#Critical uncertainties
private/Career planning and development/∵ Be a great faculty member at Grenfell.md#Meetings#Design for serendipity and innovation
# assistant

Based on your notes, Ryan is acutely aware of the impact of generative technology and AI on equity in academia. His thoughts reflect a nuanced understanding of the potential benefits and significant challenges posed by these technologies.

  1. Democratization vs. Learning Curve: Ryan highlights a critical tension between the democratization of technology and the learning curve associated with its use. He notes, “Will the technology be roughly as accessible and useful for everyone, or will trends emerge that drive use of generative AI to be more exclusionary?” This question underscores his concern that while AI has the potential to make knowledge more accessible, it also risks becoming a tool that only benefits those with the resources and skills to use it effectively.
  2. Exclusivity of AI Use: Another concern Ryan expresses is about the exclusivity of AI use in academia. He discusses scenarios where AI could become an “Acceptable + Exclusive: differentiator,” particularly in research and teaching contexts. This exclusivity could lead to a divide where only certain privileged groups have the full benefits of AI, potentially exacerbating existing inequities within the academic community.
  3. Value Addition vs. Commoditization: Ryan also addresses the issue of AI’s value addition versus its potential commoditization. He questions, “If everyone has access, and/or if the usefulness continues to be questionable, this just becomes a new requirement (like ’everyone should have a website’/everyone has a smartphone).” This reflects his concern that without careful consideration, the integration of AI could lead to a superficial adoption that does not truly enhance educational outcomes but rather becomes a baseline expectation, potentially marginalizing those who cannot keep up. These insights from Ryan’s notes reveal his deep consideration of how generative technology and AI could influence equity in academia. He is clearly concerned about ensuring that these technologies do not simply reinforce existing disparities but are used in ways that genuinely enhance accessibility and fairness in educational opportunities.
# user

Okay, last question: What do I think the university should be doing to help students and educators navigate generative technology and AI-related experiences of teaching and learning? Again, do not hallucinate, and use direct quotes from my notes in your synthesis. Also, reference the notes themselves with their note titles.

# assistant
 
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{"hypothetical_1":"PARENT FOLDER NAME > CHILD FOLDER NAME > FILE NAME > HEADING 1 > HEADING 2 > HEADING 3: Ryan believes universities should provide structured programs and resources to help both students and educators effectively integrate and navigate AI technologies in their teaching and learning practices.","hypothetical_2":"PARENT FOLDER NAME > CHILD FOLDER NAME > FILE NAME > HEADING 1 > HEADING 2 > HEADING 3: Ryan suggests that universities should establish AI literacy workshops, develop comprehensive AI ethics guidelines, and create support systems for students and educators to explore the potential and challenges of AI.","hypothetical_3":"PARENT FOLDER NAME > CHILD FOLDER NAME > FILE NAME > HEADING 1 > HEADING 2 > HEADING 3: Ryan advocates for the creation of interdisciplinary teams that include ethicists, technologists, and educators to collaboratively design curricula that incorporate AI in a way that enhances learning and upholds academic integrity."}
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⧉ Inbox/20230317123735.md#
⧉ Inbox/A sample design theory for learning how to use AI.md#
Projects/How might generative text tools be useful in academia?.md#Scenarios and artifacts from the future#AI experts
Projects/How might generative text tools be useful in academia?.md#Takeaways
# assistant

Based on your notes, particularly from “A sample design theory for learning how to use AI” and “How might generative text tools be useful in academia?”, Ryan has articulated a clear vision for how universities, specifically Memorial University, should be assisting students and educators in navigating the complexities of generative technology and AI in teaching and learning environments.

  1. Integrating AI into Curricula: Ryan believes in the proactive integration of AI tools into academic curricula to ensure that students are not only familiar with these technologies but are also proficient in using them effectively and ethically. He suggests that “AI becomes so essential that dedicated courses are developed to ensure graduates have the skills necessary to use and learn from these tools” ([How might generative text tools be useful in academia?](Projects/How might generative text tools be useful in academia?.md#Scenarios and artifacts from the future#AI experts)).

  2. Ethical Training: Ryan emphasizes the importance of ethical training alongside technical training. He proposes that “Integrate AI ethics education into the existing programs on plagiarism and academic integrity” as a design principle, highlighting the need for an ethical framework that accompanies the technical skills imparted by AI education ([A sample design theory for learning how to use AI](⧉ Inbox/A sample design theory for learning how to use AI.md#)).

  3. Practical Application and Feedback: He advocates for the use of AI in coursework, allowing students to apply these tools in real-world scenarios and receive feedback. This approach not only enhances learning but also ensures that students understand the practical implications and limitations of AI technologies. He suggests, “Encourage students to use generative AI in coursework and give them feedback on the results” as a key design principle ([A sample design theory for learning how to use AI](⧉ Inbox/A sample design theory for learning how to use AI.md#)).

  4. Assessment Adaptation: Ryan also discusses the adaptation of assessment strategies to account for the integration of AI tools. He mentions various approaches such as grading the process rather than the product, using invigilation, incorporating AI tools into assessments, and making assessments more challenging to ensure that they leverage AI’s capabilities while maintaining academic integrity ([How might generative text tools be useful in academia?](Projects/How might generative text tools be useful in academia?.md#Takeaways)).

These strategies outlined by Ryan reflect a comprehensive approach to addressing the challenges and opportunities presented by AI and generative technologies in academia. By focusing on integration, ethical training, practical application, and assessment adaptation, Ryan envisions a learning environment that not only keeps pace with technological advancements but also prepares students and educators to navigate these tools responsibly and effectively.