Why aren’t more people working on AGI?
This question came up again at a recent debate on the merits of advanced AI.
Here’s a list of some of the most common reasons, plus an analysis of why there seems to be so little progress in AGI development:
Why are so few researchers pursuing AGI?
Many researchers believe: Human-level AGI is not possible because…
- Biological beings (especially humans) have something special (a soul?) that cannot be replicated in machines
- Human intelligence requires consciousness, which in turn arises from weird quantum processes that cannot be implemented in computers
- They tried in their youth (20–40 years ago) and failed — now, conclude that it can't be done
Others have fundamental problems with ‘general intelligence’…
- Believe that it is inherently an invalid concept (‘g’ in psychology has become quite unpopular — one could even say ‘politically incorrect’)
- Overall intelligence is just a collection of specialized skills, and we just need to somehow engineer or create all individual ones
A very common objection is that the time is not ripe…
- AGI can’t be achieved within their lifetime, so there is no point
- Hardware is not nearly powerful enough
Most researchers believe that ‘nobody know how to build AGI’ because…
- “We don’t understand intelligence/ intuition/ consciousness/ etc.”
- They haven’t seen or heard of any viable theories of AGI
- They aren’t even looking for that possibility (because of many of the other reasons listed here)
We should rather copy the brain in some way to achieve human-level AI…
- Reverse engineer the brain with custom chips—one area at a time
- Simulate a human brain in a supercomputer
- Build specialized hardware that copies brain neural structure
- Grow biological brains in a vat
Don’t think that AGI is all that important because…
- Narrow AI already exceeds humans abilities in many areas
- They don’t believe that self-improving (Seed AI) is viable
- Don't share the vision of AGI’s benefits, or our need for it
Simply don’t have the ‘patience’ for such a long-term project
- Can get quicker results (financial and other) pursuing Narrow AI
Quite a few people think that AGI is highly undesirable because…
- Lead to massive unemployment, or is generally not socially acceptable.
- We don’t know how to make it safe, and will likely destroy us
Finally, there are those would love to work on AGI, but…
- Don’t know how to do it, and see no viable model
- Are researchers who will get little academic respect/ support/ funding
- Can’t get their AGI efforts funded
All of the above combine to create a dynamic where AGI is not fashionable, further reducing the number of people drawn into it!
Why is there so little progress in (workable) AGI models and systems?
See above: Why are so few researchers pursuing Real AI?
The field is dramatically underfunded
Most theories of general intelligence, and approaches to AGI, are quite poor:
- Poor epistemology: understanding the nature of knowledge and certainty, how it is acquired and validated, the importance of context, etc.
- Poor understanding of intelligence: knowledge vs adaptive learning, static vs dynamic, offline vs interactive, big data vs instance learning, etc.
- A poor understanding of other key concepts involved: grounding, understanding, concepts, emotions, volition, consciousness, etc.
- A lack of logical integration of connectionist, statistical, logic, and other AI techniques and insights
- Not appreciating the importance of a comprehensive cognitive architectures, and looking for an overly simple, ‘silver-bullet’ approach
- Overly modular designs, incompatible with deep cognitive integration
- Focusing on only one, or a few, aspects of intelligence
- Focusing exclusively on the wrong level: either too high (at logical reasoning) or too low (perception/ action)
- Too much focus on copying the brain — i.e. biological feasibility
- Using physical robots prematurely (i.e. now)
- A lack of commonality/ compatibility between various AGI efforts
- Performance expectations are set too high for any specific functionality: early general intelligence is not likely to be competitive with narrow AI
Of course, the (perceived) lack of progress feeds the lack of interest and people working in the field… a non-virtuous cycle.