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public:t-720-atai:atai-22:self-x [2022/09/11 11:07] – [Four Dimensions of Control System Autonomy] thorisson | public:t-720-atai:atai-22:self-x [2024/04/29 13:33] (current) – external edit 127.0.0.1 |
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| Predictability is Hard to Achieve | In a growing, developing system that is adapting and learning (3 or 4 levels of dynamics!) achieving predictability can only be achieved by **abstraction**: Going to the next level of detail (e.g. I cannot be sure //what exactly// I will eat for dinner, but I can be pretty sure that I //will// eat dinner). | | | Predictability is Hard to Achieve | In a growing, developing system that is adapting and learning (3 or 4 levels of dynamics!) achieving predictability can only be achieved by **abstraction**: Going to the next level of detail (e.g. I cannot be sure //what exactly// I will eat for dinner, but I can be pretty sure that I //will// eat dinner). | |
| Achieving Abstraction | Can be done through hierarchy (but it needs to be //dynamic// - i.e. tailored to its intended usage, as the circumstances call for - because the world has too complex combinatorics to store precomputed hierarchies for everything). | | | Achieving Abstraction | Can be done through hierarchy (but it needs to be //dynamic// - i.e. tailored to its intended usage, as the circumstances call for - because the world has too complex combinatorics to store precomputed hierarchies for everything). | |
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| ====Trustworthiness==== |
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| | What It Is | The ability of a machine's owner to trust that the machine will do what it is supposed to do. | |
| | Why It Is Important | Any machine created by humans is created for a purpose. The more reliably it does its job (and nothing else) the more trustworthy it is. Trusting simple machines like thermostats involves mostly durability, since they have very few open variables (unbound variables at time of manufacture). | |
| | Human-Level AI | To make human-level AI trustworthy is very different from creating simple machines because so many variables are unbound at manufacture time. What does trustworthiness mean in this context? We can look at human trustworthiness: Numerous methods exist for ensuring trustworthiness (license to drive, air traffic controller training, certification programs, etc.). We can have the same certification programs for all humans because their principles of operation are shared at multiple levels of detail (biology, sociology, psychology). For an AI this is different because the variability in the makeup of the machines is enormous. This makes trustworthiness of AI robots a complex issue. | |
| | To Achieve Trustworthiness | Requires **reliability**, and **predictability** at multiple levels of operation. Trustworthiness can be ascertained through special certification programs geared directly at the **kind of robot/AI system in question** (kind of like certifying a particular horse as safe for a particular circumstance and purpose, e.g. horseback riding kids). | |
| | Trustworthiness Methods | For AI are in their infancy. | |
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