1) The koomey's law adjustment is a constant. Hard constants are bad for something should be able to adapt to future circumstance without intervention. It is possible that with further thought it could work similarly to the latest encoin proposal.
If the computer hardware cycle fell outside of koomey's law (and, like Moore's, it always does to some degree and is only a measure of history, not predictive of the future), the value of GEMs would be less stable than ENC.
Still working my way though your new section on how you do this in Encoin. I'm behind on my reading.
Koomey's law is the best way I could explain what the goal is. I am still not sure how variances from Koomey's law could be measured of automatically compensated for. I do still think those differences will be swamped by actual economic changes though. This compounds the measurements.
2) It centralizes trust. It would be very complicated to use the block chain to keep track of this trust (or reputation), so Red's idea was to have peers use well-known merchants/exchanges as the basis for trust. I'm sure it would end up being more complex and more secure than just that, but his implementation ideas are still at the early stages; I've had a bit of a head start. But since the bitcoin block chain does not scale well at all, it is likely always going to revolve around a small number of entities.
The basic problem is that given varying necessity for coin generation, there is no absolute way to resolve network partitioning like Bitcoin proposes. Both Encoin and GEM attempt to avoid the problem, by identifying network partitioning up front. Nodes should know ASAP if they have been partitioned from the main network.
GEM does this on a 10 minute block basis using the announcements from non-anonymous nodes. Encoin does it for each transaction independently.
Both require a benchmark for how a node can measure if they are in the majority or minority network partition. This benchmark is a very difficult thing to name. Encoin proposals have called it by several different names "Trust" being the most common. GEM also uses the term "Trust" but it does so differently than Encoin.
Trust in GEM is basically human to human pragmatic trust. If you don't see your friend, you get worried. Trust in Encoin is more of a mathematical relationship. It is (sort of) a summation of "node compliance to the specification" (times) "node availability over time". Consistency or Dependability might be good alternate terms to describe what Encoin is measuring. But these terms don't work in most of the sentences discussing how a node can "trust" that its transactions have been confirmed.
Both of these Encoin and GEMs "trust" benchmarks are designed to frustrate Sybil attacks. In this case that means creating additional entities in hopes of convincing a node it is in the majority partition when it is indeed in the minority partition. GEM frustrates this by requiring trusted nodes to be non-anonymous and trusted in the human to human sense. Encoin frustrates this by requiring anonymous nodes to put in extended effort over time (electricity) to build "trust". If a node violates the compliance rules, their expensive trust is easily revoked.
The main drawback with Encoin's "trust" implementation is it requires almost as many words to describe (and lines of code to implement) as is needed for the rest of the transaction processing. This does not imply that it won't work or that it isn't worth doing.
The main drawback with GEMs "trust" implementation is that it is difficult to guarantee that it is sufficient to frustrate deliberate network DOS or forking attacks. I tend to think it is. However, it requires acknowledging that when things get deliberately wonky, humans are going to step in no matter how much we hope they won't.