As technology continues to advance, embracing discussions about artificial intelligence (AI) in our professional circles becomes increasingly vital. Recently, I had the opportunity to facilitate a structured yet casual conversation among librarian peers about AI, focusing on its implications and potential applications in our field. This blog post shares my approach and resources used, aiming to inspire and guide other professionals interested in conducting similar discussions.

​To ensure a comprehensive foundation for our discussion, participants were first emailed a detailed handout about a week in advance of the meeting. This document served to introduce essential concepts related to AI and ChatGPT, offering insights into how these technologies function, current applications, and key terms such as ‘Generative Pre-trained Transformer’, ‘Large Language Models’, and ‘Machine Learning.’ By explaining core concepts the handout helped equip participants with a uniform understanding, paving the way for a more productive discussion. The handout also helped level the playing field so that all participants, regardless of their prior knowledge of AI, could engage meaningfully.

​Alongside the handout, a word cloud activity was employed to gauge initial sentiments about AI. Each participant was asked to select up to ten words from a list of fifty, reflecting their feelings and views on AI. This exercise not only prepared participants mentally for the discussion but also visually illustrated the group’s collective sentiments, highlighting prevalent themes like ‘curiosity’, ‘caution’, and ‘possibility’.

​Our discussion began with an analysis of the word cloud, focusing on the frequency and context of chosen words. This segment proved to be an excellent icebreaker, but also a revealing lens into the prevailing attitudes towards AI within the group. The analysis highlighted a mix of intrigue and prudence, with words like 'curiosity' and 'caution' appearing prominently, indicating a keen interest in exploring AI's potential tempered by an awareness of its ethical and practical challenges. Notably, the frequent selection of 'responsibility' and 'ethical' underscored the group's collective emphasis on the moral dimensions of AI usage. Moreover, the recurrence of terms like 'possibility', 'concern', and 'distrust' emphasized a clear recognition of both the opportunities and risks associated with AI, reflecting a nuanced understanding of AI's impact. This initial exploration set a reflective tone for the discussion that followed.

​Following our initial conversation, I presented ‘Directed Intelligence: AI as a Strategic Tool for Human Enhancement.’ I crafted this presentation to emphasize an understanding of AI as a powerful tool that enhances human capabilities by automating complex tasks that traditionally require human intelligence. By drawing parallels between AI and mechanistic tools, I emphasized that AI functions within the confines of the directives set by its human creators, thereby serving as an extension of human intent. This emphasis helped illustrate how the design and directives given to AI influence its outputs, guiding participants to better understand strategies for utilizing AI to minimize biases and improve accuracy in its applications.

​Later in the presentation, I explored practical AI applications tailored specifically for library services. I explained how AI-driven chatbots could manage routine queries, allowing librarians to dedicate more time to complex patron interactions. I highlighted AI's potential for creative content generation, such as producing thematic reading lists, designing graphics for posters, summarizing texts, and creating engaging questions for book club discussions. Moreover, I discussed how AI could enhance readers’ advisory services and facilitate in-depth discussions on obscure texts. This capability allows patrons and librarians to explore and share excitement about literary works that are less known or discussed within their communities. I shared personal experiences where AI helped me engage with and discuss ideas from texts that were not familiar to my peers, demonstrating AI’s utility in enriching our intellectual engagement with diverse materials.

​The presentation also touched on the ethical dimensions of AI use in libraries, emphasizing the need for continuous oversight to ensure that AI applications align with ethical standards and effectively serve the public good. Recognizing AI’s limitations was a key theme, particularly the need to address biases in AI outputs and the importance of transparency in AI deployments to foster trust among library users.

​The session concluded with a hands-on demonstration of ChatGPT, vividly showcasing its capabilities and discussing its integration into library services to boost user engagement and efficiency. This interactive portion fostered a dynamic exchange of ideas, providing practical insights into AI’s applications. Reflecting on the session, it became clear that the broad and complex nature of AI topics necessitates more extensive discussion than our time allowed. To address this, I recommend allocating ample time or scheduling follow-up sessions for such discussions. Additionally, a pre-session poll on participants' familiarity with AI could assist with tailoring content to better meet the audience's needs. Moving forward, I plan to host drop-in Teams meetings to facilitate knowledge sharing, delve deeper into complex and contentious topics, and ensure all participants have the opportunity to engage fully.

​This discussion format not only provided a platform for learning and sharing insights but also demystified AI technology, making it more accessible to library professionals. For those interested in hosting similar discussions, I highly recommend starting with preparatory materials and incorporating interactive elements like live demonstrations and group analyses.

​This approach ensures that participants are not only receivers of information but also active contributors, which enhances the learning experience and fosters a collaborative environment. I hope this guide and shared resources, including the handout, presentation slides, and word cloud analysis, inspire you to facilitate your own AI discussions, advancing our collective understanding and implementation of this transformative technology in the library world. 

The Socratic Method, characterized by question-driven dialogue and critical thinking, has been a foundational pedagogical technique since ancient times. As we integrate more technology into learning and knowledge sharing, tools like ChatGPT offer new platforms where this old method can flourish in innovative ways. This blog post explores how the Socratic Method can be applied through conversations with AI, specifically with ChatGPT, enhancing our understanding and engagement with complex topics.

​The Socratic Method is a form of cooperative argumentative dialogue between individuals, based on asking and answering questions to stimulate critical thinking and to draw out ideas and underlying presuppositions. Named after the classical Greek philosopher Socrates, this method is employed to develop a deeper understanding of complex ideas. It typically involves an individual, often playing the role of the teacher, asking a series of pointed questions that lead the interlocutor to examine and sometimes contradict their own assumptions. The ultimate goal is not merely to debunk beliefs, but to encourage a profound shift in understanding and perspective, fostering both self-awareness and a more thoughtful engagement with the subject matter.

Key Characteristics of the Socratic Method:

• Systematic Questioning: Socrates employed a methodical approach to questioning, challenging his interlocutors to reflect deeply on their beliefs and to consider the logical consequences of their answers.
• Emphasis on Critical Thinking: The method prioritizes deep analytical thinking and understanding over simple rote memorization, encouraging learners to develop their reasoning skills.
• Dialogic Interaction: The method utilizes dialogue, not just as a means of communication but as a fundamental tool for intellectual exploration and mutual understanding.
• Exposing Contradictions: One of its primary aims is to reveal contradictions in the participant’s thoughts or arguments, fostering a deeper insight into the subject matter and encouraging intellectual honesty.
• Philosophical Inquiry: It promotes an ongoing quest for deeper understanding and truth, often questioning the foundational aspects of knowledge and societal norms.​

​The Socratic Method has its roots in ancient Greece, where the philosopher Socrates employed this technique as a fundamental part of his teaching and philosophical practice. His approach was primarily focused on engaging his students through probing questions that challenged their existing beliefs and exposed contradictions in their reasoning. This not only aided in deepening their understanding but also encouraged a rigorous pursuit of knowledge.

​This method of inquiry was extensively documented by Plato, one of Socrates' most famous students, who used it as a literary device in his dialogues. Through Plato's works, such as the dialogue ‘Meno’, the Socratic Method has been preserved and has profoundly influenced educational systems and philosophical thought for centuries. In ‘Meno’, Plato vividly demonstrates how Socrates uses a series of guided questions to explore the nature of virtue, making it an excellent example of the Socratic Method in action.

​After Socrates, the method continued to evolve and adapt to different cultural and educational contexts. It has been particularly embraced in legal education, where it is used extensively to teach law students the complexities of legal reasoning and to sharpen their analytical skills. Today, the method's emphasis on critical thinking and active learning makes it relevant across various disciplines and increasingly valuable in a world that values independent thought and problem-solving skills.

​Applying the Socratic Method in conversations with ChatGPT can be an effective way to deepen understanding of various subjects. Here’s how you can engage in this method:

1. Formulate Your Question: Start with a broad question that opens up a topic for discussion.
2. Follow Up with Deeper Questions: Based on the AI’s responses, ask further questions that delve deeper into the subject or that challenge the responses given.
3. Encourage Elaboration: Prompt ChatGPT to elaborate on points, providing more details or clarifications.
4. Seek Examples: Request examples to better illustrate the points discussed; this can be especially helpful for clarifying abstract concepts.
5. Summarize and Reflect: After a series of questions and answers, summarize the discussion and reflect on any new insights or contradictions that emerged. This helps solidify learning and enhance understanding. 

To maximize your experience with Socratic dialogues with ChatGPT, consider the following tips:

• Be Clear and Specific in Your Questions: Clarity leads to more meaningful answers. Vague questions might not yield the depth you are looking for.
• Be Patient and Thorough: The essence of the Socratic Method is depth. It may take several rounds of questioning to fully explore an issue.
• Use Critical Thinking: Always think critically about the answers provided by ChatGPT. Look for inconsistencies and compare with established knowledge.
• Engage Regularly: Frequent practice will enhance your questioning skills and your ability to analyze responses effectively. 
• Document Your Conversations: Keeping a record of your dialogues can be useful for reviewing and understanding your progress in thinking critically and engaging deeply.

​The Socratic Method, through its emphasis on questioning and critical dialogue, remains a powerful educational tool. When integrated with AI platforms like ChatGPT, it not only facilitates deeper learning but also enhances our interaction with technology as a medium for intellectual exploration. By adopting a meticulous and thoughtful approach to our questions and conversations, we can unlock the full potential of AI to delve into complex ideas and cultivate a richer understanding of the world around us. This blend of ancient technique and modern technology opens up new avenues for discovery and understanding, making it a quintessential practice for learners and thinkers in the digital age.

In the fascinating realm of artificial intelligence, the diversity of technologies ranging from specialized systems like Meta Care AI healthcare diagnostics to general-purpose platforms like ChatGPT represents a dynamic and evolving landscape. In this blog post I will explore the nuanced interplay of specialization versus generalization in AI, the competitive and collaborative ecosystem, the emergence of user-centric AI tools, and the crucial ethical considerations that accompany the adoption of these technologies.

Specialized AI systems are engineered with a focus on specific tasks, making them highly effective in particular domains. For instance, Meta Care AI can diagnose medical conditions with remarkable accuracy, a boon for the healthcare industry. Similarly, AI used in finance is adept at analyzing trends and making predictions, helping businesses and investors make informed decisions.

On the other hand, General-Purpose AI, such as ChatGPT and Google Gemini, provides a broader range of capabilities. These platforms excel in tasks from text generation to basic reasoning over a wide spectrum of topics, making them versatile tools for both personal and professional use. Their adaptability makes them suitable for a myriad of applications, bridging gaps across different tasks and industries.

GPTs offer an incredibly useful advancement in the field of AI, enabling users to easily create customized versions of ChatGPT tailored for specific purposes. Accessible to anyone with a ChatGPT Plus account, creating personalized GPTs requires no coding expertise and can be built for individual use, within a company, or by community groups, such as a Dungeons and Dragons club. Users can decide whether to make their GPTs available to others. 

​The process starts simply by initiating a conversation. Users can instruct their GPT, assign it a persona to suit their style or needs, enrich it with additional knowledge by uploading documents, and choose its capabilities, which might include web searching, image creation, or data analysis.

​This process, known as fine-tuning, enhances a GPT's performance in particular tasks or domains, creating a hybrid AI that combines the broad applicability of general-purpose AI with the precision of specialized knowledge. By doing so, users can leverage the extensive foundational knowledge of GPTs while also meeting specific challenges and requirements. This results in AI solutions that are both efficient and effective, tailored to the unique needs of their users and directives.

​The AI landscape is not just a battleground for competition but also a fertile ground for collaboration. Innovations by companies like You.com, which integrate AI to enhance search engine functionalities, contribute to a healthy competitive environment that propels technological advancements. Moreover, collaborative efforts can lead to the creation of more robust AI systems. For example, one AI might specialize in collecting and organizing data, while another excels at processing this information, and yet another enhances user interaction, creating a seamless workflow.

​With a plethora of AI tools available, users are empowered to select or create the ones that best meet their specific needs, whether for specialized tasks or general assistance. This flexibility enhances not only efficiency but also user satisfaction and engagement. Organizations benefit as well, as they can assemble a suite of AI tools, each chosen or built for its unique strengths and compatibility with various operational tasks, thereby optimizing productivity and outcomes.

Meta AI, a notable example, is making significant strides by integrating its specialized AI capabilities directly into widely used platforms such as Facebook, Messenger, and Instagram, with plans underway to extend these services to WhatsApp. This strategic deployment not only makes powerful AI tools more accessible, but also illustrates how deeply integrated AI is becoming in our everyday digital experiences. As technologies like Meta AI become a seamless part of our daily online interactions, they underscore the notion that AIs are here to stay, each tailored and optimized for different aspects of our digital lives.

​As the use of AI proliferates, so do the responsibilities of developers and users. Ensuring the ethical use of AI is paramount. AI tools must adhere to strict standards of safety and transparency to protect user privacy and data security. Furthermore, the interoperability among diverse AI systems requires well-defined standards and protocols to ensure they work together effectively without compromising data integrity or functionality.

​OpenAI exemplifies responsible data management by explicitly asking for user permission before sending data to an external application or AI when using GPTs. This practice not only enhances user trust but also reinforces the commitment to privacy and ethical AI usage, ensuring that users maintain control over their data and understand how it is utilized.

As we navigate the future of AI, the landscape is increasingly characterized by a mix of specialized and general-purpose tools. From the precision of Meta Care AI in healthcare diagnostics to the versatility of ChatGPT and Google Gemini in handling diverse tasks, the AI ecosystem is becoming more interconnected and efficient. However, this growth comes with the responsibility to manage these tools ethically and thoughtfully, ensuring they enhance human capabilities and contribute positively to our lives.

​The evolution of AI is an exciting journey that promises to transform industries and everyday experiences. By understanding and leveraging the strengths of both specialized and general-purpose AI, we can foster an environment where technology not only advances but also aligns with our broader societal goals and values.

​Which AIs have you had the chance to use? Do you have a favourite? Have you tried tailoring your own GPTs?