Thinking about Artificial Intelligence

I've been taking some time to reflect on what is happening in the world around us. The advancement of artificial intelligence (AI) and its impact on my profession and industry, specifically software engineering and insurance, are at the forefront of my mind.

I wanted to explore three sides of the problem: the thing being impacted, the thing that is impacting, and then only the impact. This approach breaks down this complex topic into its fundamental components, allowing for an intuition for the complex topic to emerge.

I use first principles thinking to explore each in a meaningful way. In this post, I aim to bring together some high-level thoughts. I hope to elaborate on each of these in more detailed posts.

The thing being impacted

My inquiries regarding the thing being impacted:

1. What is knowledge? Knowledge emerges from problem-specific consideration of related data and information. See this post.
2. What is knowledge work? Both knowledge work and analytics aim to reveal knowledge inherent in data and information to inform action. The difference is that analytics utilises semiconductor capacity to process data, while knowledge work applies bio-computational capacity. See this post.
3. Why do knowledge organisations do knowledge work? A knowledge organisation seeks the profitable exchange of data, information, and knowledge at its boundaries. To understand how technology impacts tech-forward organisations, we need to examine how technology supports the efficiencies in this type of business operation. See this post.
4. What is software/information technology? Software is a well-structured recipe for working knowledge using semiconductor-based computational capacity. See this post.
5. What is the role of information technology in knowledge work? Information technology helps knowledge organisation scale information flows. This post is coming.
6. What is the tension between organisations and information technology? Entropy! The automation of knowledge work through information technology demands low entropy. This post is coming.
7. What is the role of the Software Development Life Cycle? The SDLC is a process that converts high-entropy information into low-entropy information. This post is coming.
8. What do I really mean by entropy? [Thinking about]

The thing that is impacting

My inquiries regarding the thing impacting:

1. What is Artificial intelligence? Arteficial intelligence is an advanced analytics capability that not only aims to surfaces knowledge from data and information, but also use this knowldedge to make decisions and take action against in a way that optimizes desired outcoms. Most importantly artificial intelligence is learning systems. These systems maintain feedback loops about the outcomes to guide future attempts to extract knowledge and make decisions. They get smarter. See this post.
2. What is neural networks? See this
3. Is Neural Networks and GenAi new? Neural Networks were invented and shown to be universal approximators in the 80s. The availablility of on demand computational capacity, funding sources that can command large quantities of this computational capacity, established SaaS models to enable the dissemination of models, and bold entrepreneur willing to make high-risk/high-reward bets is new.

The thing impact

My inquiries into the impact! What happens when AI meets knowledge work:

1. How does GenerativeAI help information techn organizations deal with entropy? GenAI invites interface arround information technology that is more able to deal with information entropy!
2. How does GenAI change the SDLC?
3. What is the impact of AI on the software engineer? In the short term, the hypothesis is that AI is an invitation to X-type people to be pretend to do more work, and Y-type people more effective and efficient. Its an invitation to everyone to think less critically.
4. How does GenAI and AI on the insurnace industry?
5. How does GenAI and AI on the wider society?
6. Will AI take your job?