Comment by pgodzin
8 years ago
What does it mean to be as smart as a mouse? If you specify a handful of tasks that demonstrate it, someone will be able to purpose-build an "AI" to do those things well.
8 years ago
What does it mean to be as smart as a mouse? If you specify a handful of tasks that demonstrate it, someone will be able to purpose-build an "AI" to do those things well.
Basically it means having "agency." What most people are looking for when they think of "intelligence" is not the ability to master specific tasks, but to choose which tasks to perform using one's own "free will," ultimately leading to behavior that humans find novel and feel they can connect with.
What makes you think a mouse (71M neurons) has agency\free will? Does a cockroach (1M neurons), fruit fly (250K), jellyfish (5k) have agency? I don't think we're gonna get far by relying on a phenomenon that we can't clearly define or even (externally) observe.
Indeed. Human beings have many, many examples to suggest that we lack agency, as well. Why do addiction, obesity, crimes of passion, etc exist?
Without the baggage of the limbic system and dopamine-seeking behaviors, it's quite easy to argue that an artificial intelligence is potentially capable of even greater degrees of agency than humans.
2 replies →
But what does it mean in the context of a mouse? The mouse isn't using it's free will to decide whether to become a computer programmer or a doctor, it's responding to stimulus and environment. If an AI is trained to mimic the responses of a mouse is that intelligent?
Agency in the context of a machine seems purposefully impossible to reach - its decisions are always somehow tied back to how it was programmed to react.
The mouse reacts to stimuli and environment in a qualitatively different way than our programs do. It does continuous and essentially free-form learning of the environment around it, and engages in what looks to us as dynamic formulation and achievement of goals. In "AI" we have today, the learning is very shallow (despite the "deep learning" buzzword), it's usually neither free-form nor continuous, and goals are set in stone.
3 replies →
I put agency in quotes because it's really a convincing illusion of agency that we're going for. In the end, I agree with those making the point that even we don't have free will.
Ultimately it just has to be able to convince humans that "wow, there's an actual thinking and learning 'being' in there."
What’s the difference compared to a human, whose decisions are always tied back to how its atoms are arranged?
"Basically it means having 'agency.'"
Well, in these definitions of intelligence, what one often ends up with is some combination of "deal robustly with it's environment" and a bunch of categories defined in terms of each other. That's not to say categories/qualities/term like "agency", "free will", "feel they can connect with", "find novel" and such are unimportant. It's just saying people using the terms mostly couldn't give mathematically/computationally exact definitions of them. And that matters for any complete modeling of these things.
To use machine learning parlance, such a solution would (likely) be overfitting the problem, and not generalize well. If one instead changed the setup to be: 1) Specify a handful of tasks for the AI system to complete 2) Test the performance on a _separate_ (un)related set of tasks
The test set has to be unknown to the system developers.
If the system can realize the unknown tasks without further input from researchers, in the same way that a mouse can, then we have some level of generalizable intelligence.
What is the baseline? How well does a mouse perform when placed in an "unrelated" task for the first time? The mouse also gets an explicit reward function (food, pain, etc) - does the "unrelated" task use the same reward function as what the AI was optimized for?
Also, is it ever really the "first time" for a mouse when behavior has been ingrained and tuned over millions of years of evolution? Is this different than training an algorithm?
My point is just that it's really hard to define these tasks and how to evaluate performance for a machine and a mouse.
The baseline performance would be whatever a set of mice would do in the same situation. What constitutes an "unrelated" task is quite a difficult question, we would probably need to iterate a lot on that. If we are to have "hidden" tasks available we need to come up with a lot of new task formulations/variations anyway.
I think that replicating mouse-level adaptability in an intelligent agent while allowing 'inherited' behavioral traits will already be an achievement. And probably take us quite a while.
Navigate a forest floor looking for food and avoid predators.
Not even that, mice are very social creatures, they make friends with other animals. They have so many other micro traits
(most humans can't do this task and survive)
Huh? Of course most humans could do this. Obviously humans who have lived their entire lives in modern human society will have serious difficulty, but this is true of literally any animal taken out of a wild habitat.
2 replies →
So basically we just need to show a computer can beat PacMan?