Explorations and Discovery: Looking for Adjacent Content

Exploration is more than just discovering what we agree with; it's about pushing boundaries and challenging our perceptions.

The words exploration and discovery go well together.  If you start on an exploration journey, you are likely to make some discoveries.  It's even a little more exciting than going on a learning journey and collecting some lessons. Words matter.

Today I discovered someone I now want to follow because what I read from that person resonated strongly.  This is part of the problem.  We tend to read and follow what resonates, what we agree with, which leads to reading more of the same people who write things that resonate with us, which only reinforces our opinion of ourselves and allows us to dismiss everything else either as crazy or just noise.  

I would like my explorations to lead me to things that are adjacent to what resonates with me, to push the boundaries a little, to expand the zone of what resonates with me to what makes me think and rethink.  

I am particularly interested in this discovery because it will expand my thinking.  I discovered Joan Westenberg's blog and other writings.  I discovered her via Harold Jarche's blog.  Harold Jarche is already on the edge of my comfort zone and someone I have followed closely for a long time around Personal Knowledge Management.  Joan Westenberg is pushing things in the same zone of discovery.

What's the point I am trying to make?

In an attempt to curate interesting, relevant information, and to support my explorations for valuable discoveries, I need to strategically pay attention beyond what immediately resonates with me and notice the adjacent content that can take my own thinking one step further. 

2024 Explorations - Q1 Review

I started my 2024 Explorations in January. It was meant as a combination of two main objectives:

1) a learning framework or learning agenda, not so much to ensure that I would engage in continuous learning but more to ensure that my continuous learning was adequately focused on some key themes of interest;

2) using technology, and more specifically TiddlyMap, as a personal knowledge management tool that would allow me to experiment with (a form of) knowledge graph.

We've reached the end of the first quarter of 2024 and so far so good. I just completed a quarterly review of progress and generated a few insights.

• Is TiddlyMap allowing me to really learn about knowledge graphs? Yes, but as expected, it has its limitations. I will eventually crash the tool. I don't think it is meant as a graph database but it works well as an exploratory tool. Ultimately I need to move my data to a real knowledge graph tool like Neo4J. That should be a goal for the second quarterly. I started learning more about Neo4J, including learning the basics of Cypher.
  
  
• Is my learning framework working? The main themes and topics have proven very useful as guardrails and as an organization schema both for my thinking and for capturing notes. There are some issues with the taxonomy. Some topics are overlapping and I keep wanting to create more tags. So far, I have limited the number of additional tags and I have only made minor adjustments to the topic tags. Proliferation of tags would lead to inconsistencies. Until the tagging is automated, the number of tags is limited by my capacity to remember them all.
  
  The maps are telling me something pretty clear. I have focused perhaps 80% of my efforts on the AI and Knowledge Graph topics. The maps related to those topics are very large, which has enabled me to test filters. Like a search returning too many results, a map showing too many relationships is unreadable. For other topics, I have collected and curated resources, but I have not spent time connecting the dots. As a result, the maps are less interesting (so far).
  
  
  

• Is the basic ontology working? Yes, but the value of TiddlyMap's automated functionalities has made it much more powerful to create maps based on what TiddlyMap does with relationships based on tags and links associated with Tiddlers than to manually create a specific set of relationships based on my simple ontology. I have learned most by manipulating the filters to understand how relationships are displayed. Interpreting the resulting maps for potential insights is the next stage I want to dive into. Since I am the one creating all the links and the tags, the maps are not telling me anything I didn't already notice, but they are representing the connections visually and often reminding me of connections I made weeks ago that I don't hold in immediate memory.  I posted one of the maps in the Insight Maps section. 

The biggest ha-ha moment was related to tagging. I was using the tagging functionality to tag too many different types of things and failing to use a major functionality of the tool. I realized after a while that I should be using the fields to document the properties of a node. For example, "author" is a field rather than a tag. This allows me to have a consistent set of node properties and to rely on tags only for topics and some of the metadata used for navigation purposes. This also really helped make the maps more meaningful.

Using a GPT to get updates in topics of interest

About a month ago, I created a GPT based on ChatGPT 4.0.  It's easy to create but requires some fine-tuning.  I used Ross Dawson's approach detailed here:  Creating custom GPTs for news and Information Scanning; and I adjusted it to suit my own purpose.  The results have been mixed but I'm reasonably happy with what I got today. 

Critical Cognitive Capabilities in the Age of AI

In an era increasingly dominated by artificial intelligence (AI), our cognitive landscape is undergoing a transformation as significant as any in our history. This shift demands not just an adaptation but a deliberate enhancement of our cognitive capabilities. Amidst this technological evolution, the cultivation of critical thinking, emotional intelligence, creativity, and adaptive learning emerges as essential to thrive.

Created by DALL.E, with human input.  A vision of a harmonious collaboration between humans and AI, showcasing human collective intelligence, creativity and innovation, augmented by the capabilities of technology, including AI. 

The story of Theuth and his invention of writing, as recounted by Socrates (see the previous post), provides a profound starting point for this discussion. Just as the introduction of writing raised concerns about memory and wisdom, today's rapid advancements in AI and the Internet pose new challenges and opportunities for human cognition. In this digital age, the capacity for ''critical thinking'' has never been more important. As we navigate vast oceans of information, discerning fact from fiction, valuable data from noise, requires a keen analytical mind. This skill ensures we remain effective decision-makers in both personal and professional realms, notwithstanding the deluge of AI-generated content and analysis.

Emotional intelligence stands out as a uniquely human attribute that AI is far from replicating. Our ability to understand, empathize, and interact with others is paramount, especially as AI technologies handle more cognitive tasks. Developing emotional intelligence helps us navigate the complexities of human relationships and teamwork, fostering environments where collaboration between humans and AI tools is productive and innovative.

Creativity is another domain where humans can excel beyond AI's capabilities. While AI can generate new patterns and ideas based on existing data, the human capacity to think abstractly, imagine the unimaginable, and connect disparate concepts in novel ways remains unmatched. Encouraging creativity in education and the workplace ensures that as AI takes over more routine or analytical tasks, humans will continue to lead in innovation, design, and artistic expression.

Lastly, the concept of adaptive learning is crucial. Just as AI systems learn and evolve based on new data, so too must we. However, our learning is not just about absorbing information; it's about adapting to new ways of thinking, new technologies, and changing societal norms. This ability to learn and relearn throughout life is what will keep us relevant and resilient in the face of rapid technological changes.

As we consider the future in this age of AI,  our focus should not only be on developing technical skills to use and manage AI systems. Instead, we must emphasize the uniquely human capabilities that will complement AI's growth. By nurturing critical thinking, emotional intelligence, creativity, and adaptive learning, we prepare ourselves not just to coexist with AI but to lead a future where technology enhances our human experience, not diminishes it.

Of related interest:

• Gianni Giacomelli's "With AI, learning and reskilling ≠ training|", blog post of 3/25/2024.