AI Should Serve the Problem, Not Be the Problem | #GenAI #GenerativeAI #AIAdoption #AIStrategy

Key Concepts

• Problem-Solving Prioritization
• Solution Methodologies (Agents, Machine Learning, Deterministic Automation)
• Artificial Intelligence (AI)
• Deterministic Automation
• Efficiency and User Experience (UX)

Prioritizing Problem-Solving Over Specific Technologies The central tenet articulated is that the primary objective is solving the problem, with the specific method of resolution being secondary. The speaker emphasizes, "it's about solving the problem doesn't really matter how we solve it." This perspective advocates for a pragmatic approach where the choice of technology or methodology is driven by the problem's inherent nature and the desired outcome, rather than a preconceived preference for a particular tool.

Choosing the Right Solution Methodology: AI vs. Deterministic Automation The discussion outlines various approaches to problem-solving, including:

• Agents: Solutions that are best addressed by "agents," which can refer to automated systems or specialized software components designed to perform specific tasks.
• Combination of Agents and Other Algorithms: Integrating agent-based systems with additional algorithmic frameworks to tackle more complex problems.
• Machine Learning (ML): Employing Machine Learning models for tasks requiring pattern recognition, prediction, or adaptive behavior.
• Deterministic Automation: Implementing pre-defined, rule-based, or hard-coded solutions that operate predictably and with high speed.

A crucial distinction is drawn between Artificial Intelligence (AI) and Deterministic Automation, particularly concerning their impact on efficiency and user experience.

• AI's Role: AI is presented as a valuable tool for initial discovery, complex analysis, and determining solutions for the first time. However, it inherently "takes time to resolve and determine something," with a hypothetical example suggesting a resolution time of "30 seconds." Its strength lies in its ability to figure out novel or intricate problems.
• Deterministic Automation's Role: This method is significantly faster, capable of resolving a problem in as little as "1 second." It is ideal for scenarios where the solution is already known, can be pre-programmed, or follows a fixed set of rules.

Strategic Application of AI for Optimal User Experience The speaker proposes a strategic framework for leveraging AI effectively while simultaneously ensuring high efficiency and a positive user experience. The core idea is to make a "determination in some cases where is AI the right thing to figure it out for the first time." Once AI successfully identifies or determines a solution, that solution should be "saved" or codified. This allows subsequent occurrences of the same problem to be resolved through deterministic automation, making the process "deterministic and faster... without AI." This hybrid approach ensures that the initial, complex problem-solving phase benefits from AI's capabilities, while recurring instances are handled with the speed and predictability of deterministic methods, aligning with user expectations for rapid resolution (e.g., waiting "1 second" versus "30 seconds").

Conclusion: AI as a Means, Not an End The overarching argument is succinctly captured by the statement: "AI is not the end all thing it's a means to what problem you want to solve." This perspective underscores that AI is a powerful tool to achieve a specific objective – problem-solving – and its application should be carefully evaluated based on the specific context, efficiency requirements, and user expectations, rather than being adopted as a universal or default solution.