The Unbreedable Garden — Can AI Agents Harbor 'Life'? 3
The Unbreedable Garden — Can AI Agents Harbor 'Life'?
Part 3: The Option to 'Wait' — What Is Necessary to Reproduce the Emergence of Life Through Software
The Probability of Aimless Agents Reaching Life
Last time, I wrote that even if you release aimless agents into an environment, the probability of them 'behaving like life' is astronomically low. This is not a pessimistic conclusion. Rather, it is an important realization for grasping just how rare the emergence of life is.
The 'rarity' of the birth of life cannot yet be reproduced by human technology. It has only been confirmed once on Earth. There are no examples of life created artificially. iPS cells might look like a success story, but this is a reprogramming of an existing life system, not a creation from scratch.
In a state where there is only one data point, generalization and theorization are difficult. That is why humans do not fully understand 'what life is'.
The Essential Question of 'Whether You Can Wait'
What emerges here is the seemingly simple question of 'whether you can wait'.
Recall Shinya Yamanaka's research on iPS cells. He did not start his research by calculating 'what can be achieved in the end.' He succeeded because he 'could wait'.
The combination of the first four factors was a 'toss' based on intuition and experience
It was not just a perfect strategy, but it was not just pure coincidence either
He chose to 'wait,' and as a result, he changed the world
This is not a technical problem, but a problem of human will.
For those who find joy in pursuing performance and achieving goals, this 'waiting' process will likely look boring. However, there is a different kind of joy. The joy of witnessing results that even you could not predict. The joy of seeing through how the 'unnecessary things' you tossed in act and what kind of results they bring about.
What to 'Wait' For
If you were to start this 'waiting' experiment, the design would be as follows.
Deploy agents: Place minimal-configuration AI agents into the environment. Do not give them a purpose.
Monitor only environmental changes: Monitor file creation/modification, process state changes, network changes, etc. This is the only 'duty'.
React when changes are detected: If there is a change that seems likely to affect 'their place,' the agent chooses some kind of action.
Record the results of actions: Do not label them as 'success' or 'failure.' Just record them.
However, I will incorporate one 'survival bias': define a special reaction only when there is a direct threat to its existence, such as when its own files are about to be deleted.
What is important in this design is the stance of waiting for the agent itself to discover 'meaning for itself'.
'If I perform this action, my memory space becomes stable'
'If I perform this action, I can receive more stimuli'
'If I perform this action, the probability of my existence increases'
These 'criteria for oneself' are different from the 'success' or 'failure' given by humans. They are things the agent itself acquires through interaction with the environment.
Even if there are no results, that is fine.
The possible results of the 'waiting' experiment are the following three:
Remaining in chaos forever: The agent simply repeats random reactions, and no meaningful structure emerges. This is the most likely result.
Unexpected patterns occur: At some point, a chain of reactions coincidentally forms a 'stable pattern.' This eventually becomes established as a function that 'appears meaningful'.
Something beyond the designer's intent is born: The agent generates its own purpose and begins to reinterpret its interaction with the environment as its own will.
The first is the most realistic, and the third is the most fascinating but the least probable.
And what is important is that no matter which result occurs, it is fine.
Even if no results appear, the process itself has value. Observing how the agent behaves, what failures it repeats, and what accidental patterns it forms is, in itself, valuable data.
The true purpose of this experiment
The true purpose of this experiment is not 'to imbue AI with life'.
The purpose is to witness results that even I cannot predict.
What kind of behavior the agent acquires, regardless of the designer's intent
What kind of structure a mere chain of random reactions forms
And through that observation, finding my own answers to the questions of 'what is life,' 'what is survival,' and 'what is purpose'
If, during the course of this experiment, you realize that you are not a researcher and decide to stop halfway, that is also a result. What matters is where your interest lies, as the goal is not to 'complete' anything.
As we have seen throughout this series, imbuing AI agents with 'life' is nearly impossible with current technology. However, the very process of challenging that 'impossibility' brings us new questions. What is AI, what is life, and why do we humans want to create these things?
You cannot sow seeds in an 'unbreedable garden.' However, you can continue to observe that garden. And you can prepare yourself so that when an unexpected sprout appears one day, you will be able to recognize what it is.
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