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12.10 Conclusion: Eight Ways to Bias AGI Toward Friendliness
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12.10.1 Encourage Measured Co-Advancement of AGI Software and AGI Ethics Theory

Everything involving AGI and Friendly AI (considered together or separately) currently involves significant uncertainty, and it seems likely that significant revision of current concepts will be valuable, as progress on the path toward powerful AGI proceeds. However, whether there is time for such revision to occur before AGI at the human level or above is created, depends on how fast is our progress toward AGI. What one wants is for progress to be slow enough that, at each stage of intelligence advance, concepts such as those discussed in this paper can be re-evaluated and re-analyzed in the light of the data gathered, and AGI designs and approaches can be revised accordingly as necessary.

However, due to the nature of modern technology development, it seems extremely unlikely that AGI development is going to be artificially slowed down in order to enable measured development of accompanying ethical tools, practices and understandings. For example, if one nation chose to enforce such a slowdown as a matter of policy (speaking about a future date at which substantial AGI progress has already been demonstrated, so that international AGI funding is dramatically increased from present levels), the odds seem very high that other nations would explicitly seek to accelerate their own progress on AGI, so as to reap the ensuing differential economic benefits (the example of stem cells arises again).

And this leads on to our next and final point regarding strategy for biasing AGI toward Friendliness....

12.10.2 Develop Advanced AGI Sooner Not Later

Somewhat ironically, it seems the best way to ensure that AGI development proceeds at a relatively measured pace is to initiate serious AGI development sooner rather than later. This is because the same AGI concepts will meet slower practical development today than 10 years from now, and slower 10 years from now than 20 years from now, etc. – due to the ongoing rapid advancement of various tools related to AGI development, such as computer hardware, programming languages, and computer science algorithms; and also the ongoing global advancement of education which makes it increasingly cost-effective to recruit suitably knowledgeable AI developers.

Currently the pace of AGI progress is sufficiently slow that practical work is in no danger of outpacing associated ethical theorizing. However, if we want to avoid the future occurrence of this sort of dangerous outpacing, our best practical choice is to make sure more substantial AGI development occurs in the phase before the development of tools that will make AGI development extraordinarily rapid. Of course, the authors are doing their best in this direction via their work on the CogPrime project!

Furthermore, this point bears connecting with the need, raised above, to foster the development of Global Brain technologies capable to "Foster Deep, Consensus-Building Interactions Between People with Divergent Views." If this sort of technology is to be maximally valuable, it should be created quickly enough that we can use it to help shape the goal system content of the first highly powerful AGIs. So, to simplify just a bit: We really want both deep-sharing GB technology and AGI technology to evolve relatively rapidly, compared to computing hardware and advanced CS algorithms (since the latter factors will be the main drivers behind the ac-

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