The set of designs that look like “Human brains + BCI + Reinforcement learning” is large. There is almost certainly something superintelligent in that design space, and a lot of things that aren’t. Finding a superintelligence in this design space is not obviously much easier than finding a superintelligence in the space of all computer programs.
I am unsure how this bypasses algorithmic complexity and hardware issues. I would not expect human brains to be totally plug and play compatible. It may be that the results of wiring 100 human brains together (with little external compute) are no better than the same 100 people just talking. It may be you need difficult algorithms and/or lots of hardware as well as BCI’s.
I think using AI + BCI + human brains will be easier than straight AI for the same reason that it’s easier to finetune pretrained models for a specific task than it is to create a pretrained model. The brain must have pretty general information processing structure, and I expect it’s easier to learn the interface / input encoding for such structures than it is to build human level AI.
Part of that intuition comes from how adaptable the brain is to injury, new sensory modalities, controlling robotic limbs, etc. Another part of the intuition comes from how much success we’ve seen even with relatively unsophisticated efforts to manipulate brains, such as curing depression.
Its easier to couple a cart to a horse than to build an internal combustion engine.
Its easier to build a modern car, than to cybernetically enhance a horse to be that fast and strong.
Humans plus BCI are not to hard. If keyboards count as crude BCI, its easy. Making something substantially superhuman. That’s harder than building an ASI from scratch.
You can easily combine multiple horses into a “super-equine” transport system by arranging for fresh horses to be available periodically across the journey and pushing each horse to unsustainable speeds.
Also, I don’t think it’s very hard to reach somewhat superhuman performance with BCIs. The difference between keyboards and the BCIs I’m thinking of is that my BCIs can directly modify neurology to increase performance. E.g., modifying motivation/reward to make the brains really value learning about/accomplishing assigned tasks. Consider a company where every employee/manager is completely devoted to company success, fully trust each other and have very little internal politicking/empire building. Even without anything like brain-level, BCI enabled parallel problem solving or direct intelligence augmentation, I’m pretty sure such a company would perform far better than any pure human company of comparable size and resources.
Secondly, do BCI’s mean brainwashing for the good of the company? I think most people wouldn’t want to work for such a company. I mean companies probably could substantially increase productivity with psycoactive substances. But that’s illegal and a good way to loose all your employees.
Also something moloch like has a tendency to pop up in a lot of unexpected ways. I wouldn’t be surprised if you get direct brain to brain politicking.
Also this is less relevant for AI safety research, where there is already little empire building because most of the people working on it already really value success.
“… do BCI’s mean brainwashing for the good of the company? I think most people wouldn’t want to work for such a company.”
I think this is a mistake lots of people make when considering potentially dystopian technology: that dangerous developments can only happen if they’re imposed on people by some outside force. Most people in the US carry tracking devices with them wherever they go, not because of government mandate, but simply because phones are very useful.
Adderall use is very common in tech companies, esports gaming, and other highly competitive environments. Directly manipulating reward/motivation circuits is almost certainly far more effective than Adderall. I expect the potential employees of the sort of company I discussed would already be using BCIs to enhance their own productivities, and it’s a relatively small step to enhancing collaborative efficiency with BCIs.
The subjective experience for workers using such BCIs is probably positive. Many of the straightforward ways to increase workers’ productivity seem fairly desirable. They’d be part of an organisation they completely trust and that completely trusts them. They’d find their work incredibly fulfilling and motivating. They’d have a great relationship with their co-workers, etc.
Brain to brain politicking is of course possible, depending on the implementation. The difference is that there’s an RL model directly influencing the prevalence of such behaviour. I expect most unproductive forms of politicking to be removed eventually.
Finally, such concerns are very relevant to AI safety. A group of humans coordinated via BCI with unaligned AI is not much more aligned than the standard paper-clipper AI. If such systems arise before superhuman pure AI, then I expect them to represent a large part of AI risk. I’m working on a draft timeline where this is the case.
The set of designs that look like “Human brains + BCI + Reinforcement learning” is large. There is almost certainly something superintelligent in that design space, and a lot of things that aren’t. Finding a superintelligence in this design space is not obviously much easier than finding a superintelligence in the space of all computer programs.
I am unsure how this bypasses algorithmic complexity and hardware issues. I would not expect human brains to be totally plug and play compatible. It may be that the results of wiring 100 human brains together (with little external compute) are no better than the same 100 people just talking. It may be you need difficult algorithms and/or lots of hardware as well as BCI’s.
I think using AI + BCI + human brains will be easier than straight AI for the same reason that it’s easier to finetune pretrained models for a specific task than it is to create a pretrained model. The brain must have pretty general information processing structure, and I expect it’s easier to learn the interface / input encoding for such structures than it is to build human level AI.
Part of that intuition comes from how adaptable the brain is to injury, new sensory modalities, controlling robotic limbs, etc. Another part of the intuition comes from how much success we’ve seen even with relatively unsophisticated efforts to manipulate brains, such as curing depression.
Its easier to couple a cart to a horse than to build an internal combustion engine.
Its easier to build a modern car, than to cybernetically enhance a horse to be that fast and strong.
Humans plus BCI are not to hard. If keyboards count as crude BCI, its easy. Making something substantially superhuman. That’s harder than building an ASI from scratch.
You can easily combine multiple horses into a “super-equine” transport system by arranging for fresh horses to be available periodically across the journey and pushing each horse to unsustainable speeds.
Also, I don’t think it’s very hard to reach somewhat superhuman performance with BCIs. The difference between keyboards and the BCIs I’m thinking of is that my BCIs can directly modify neurology to increase performance. E.g., modifying motivation/reward to make the brains really value learning about/accomplishing assigned tasks. Consider a company where every employee/manager is completely devoted to company success, fully trust each other and have very little internal politicking/empire building. Even without anything like brain-level, BCI enabled parallel problem solving or direct intelligence augmentation, I’m pretty sure such a company would perform far better than any pure human company of comparable size and resources.
Firstly we already have humans working together.
Secondly, do BCI’s mean brainwashing for the good of the company? I think most people wouldn’t want to work for such a company. I mean companies probably could substantially increase productivity with psycoactive substances. But that’s illegal and a good way to loose all your employees.
Also something moloch like has a tendency to pop up in a lot of unexpected ways. I wouldn’t be surprised if you get direct brain to brain politicking.
Also this is less relevant for AI safety research, where there is already little empire building because most of the people working on it already really value success.
“… do BCI’s mean brainwashing for the good of the company? I think most people wouldn’t want to work for such a company.”
I think this is a mistake lots of people make when considering potentially dystopian technology: that dangerous developments can only happen if they’re imposed on people by some outside force. Most people in the US carry tracking devices with them wherever they go, not because of government mandate, but simply because phones are very useful.
Adderall use is very common in tech companies, esports gaming, and other highly competitive environments. Directly manipulating reward/motivation circuits is almost certainly far more effective than Adderall. I expect the potential employees of the sort of company I discussed would already be using BCIs to enhance their own productivities, and it’s a relatively small step to enhancing collaborative efficiency with BCIs.
The subjective experience for workers using such BCIs is probably positive. Many of the straightforward ways to increase workers’ productivity seem fairly desirable. They’d be part of an organisation they completely trust and that completely trusts them. They’d find their work incredibly fulfilling and motivating. They’d have a great relationship with their co-workers, etc.
Brain to brain politicking is of course possible, depending on the implementation. The difference is that there’s an RL model directly influencing the prevalence of such behaviour. I expect most unproductive forms of politicking to be removed eventually.
Finally, such concerns are very relevant to AI safety. A group of humans coordinated via BCI with unaligned AI is not much more aligned than the standard paper-clipper AI. If such systems arise before superhuman pure AI, then I expect them to represent a large part of AI risk. I’m working on a draft timeline where this is the case.