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The Information Silk Road
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Date: Fri, 29 Aug 1997 13:18:43 -0400 (EDT)
To: [email protected]
Subject: The Information Silk Road
Cc: [email protected], "R. Jason Cronk" <[email protected]>
From: Ted Anderson <[email protected]>
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Subject: The Information Silk Road
In this note I criticize recursive auction markets as a good model for
the global market in public information. Instead I suggest an agent
based model where data merchants compete to be suppliers of information
to clients based almost entirely on value they above and beyond the
value of the information itself. I ignore issues of data ownership and
data privacy.
I realized that e$ is perhaps not the best forum for this message and
welcome redirection to a more appropriate venue.
The Information Silk Road
I would like to draw a distinction between trading in digital services
and trading information. There are interesting proposals to use
market-based mechanisms to manage computer resources such as memory and
CPU cycles[1] or network bandwidth[2]. Attempts have been made to
extend this idea to trading information, such as the recursive auction
market[3]. While the similarities between computer resources and the
material world are close enough to make market-based ideas quite
successful, I don't think the same is true for markets in information.
Differences stem from the fact that information can be copied with
perfect fidelity and essentially zero cost while both physical
commodities and computing resources are strictly limited in quantity.
- From another point of view, the problem is that the responsibilities of
ownership are different. Market-based mechanisms work by clearly
identifying an owner for each resource. The owner (in computational
contexts this is usually a software agent) then tries earn enough income
from its asset to pay expenses. The job of the owner is then to avoid
overuse (the tragedy of the commons problem) and underuse. However,
with information, overuse is impossible (maximizing the use of
information is actually beneficial to general good) and only underuse is
a risk. Underuse of information can even lead to a problem not shared
with other limited commodities, it may be lost altogether.
Practically speaking there is another difference between computer
resource commodities and information products. For example, any memory
page can be sold to a software agent and numerous agents will compete
for a fixed pool of identical pages. However, while I can endlessly
replicate a piece of information, each customer won't need more than one
of each datum. While different agents may occasionally request the same
piece of information, this is often rare. Partly this is because a even
small cache near the customer will mean that the server only gets a
single request from each cache miss, not from each customer request.
Therefore, an information seller must stock a huge selection of data and
only expect a very tiny fraction of them to be to be in high demand.
Still, I would like to see both the digital silk road (markets for
computer services) and the information silk road (markets for data)
built. I am particularly interested in the design of the data merchants
that will be the traders on the information silk road.
Recursive Auction Market
A useful contribution of the recursive auction market idea is that it
denigrates to concept of information ownership. While ownership of
information may still be useful to prevent valuable information from
disappearing altogether (by being replaced in every supplier's inventory
by more profitable data) it has nowhere near the standing of ownership
of finite commodities.
The recursive auction market idea assumes that data in high demand would
propagate from suppliers or intellectual property producers, through
intermediate distributors, to consumers as fast as the network could
carry it. At each stage the data is auctioned to the highest bidder who
must factor into his bid price the network transfer charges[2] and his
ability to further resell it. As the data is distributed, the rarity
premium available to early sellers disappears, leaving only the basic
network delivery costs.
These auctions require multiple simultaneous buyers. However it would
seem that this would be a very unusual case. Except for a few extreme
cases, the market for data will consist of multiple buyers spread out in
time. This means that a significant expense of the seller is for the
storage of the data between buyers. This storage rental must be
factored into the data's price. This is a hard cost that depends on the
interval between requests of each piece of data. Rarity, and the
premium it adds to the price, is usually an ephemeral, even
self-defeating, property of data. This suggests that an auction is not
a good general paradigm to use for trading information.
Data Merchants
A better model of the information silk road has a large population of
data merchants spread throughout the network. Their mission is to
maintain an inventory of data in anticipation of being able to resell it
profitably at a later time. Viewed individually these data merchants
provide a data caching service. While viewed collectively, the
information silk road is a replicated data storage facility[4].
So what services can a data merchant offer which customers might be
willing to pay for. In other words, how can they add value.
Locality. Assuming some distance (as the packets fly) sensitivity to
network transport charges, data will be cheaper from a local supplier
than from a distant one. This means that a merchant can pay the
transport charges to obtain the distant data once and attract local
buyers by charging less than it would cost them to fetch it from a
remote source. As long as there are multiple local buyers and the data
storage costs incurred between requests is small compared to the
differential between remote and local network transport charges then the
local vendor can turn a profit.
Authoritativity. For small data, where the cost of transferring the
data is comparable to the cost of requesting it, it will be useful for a
client to pass its requests to a single merchant and expect a high
probability of obtaining the data. Without consulting an authoritative
source the client will potentially have to contact many merchants before
finding the data it seeks. Unless the data is large this cost may dwarf
the actual transfer cost. Being an authoritative source does not have
to be a global property, but might apply to narrowly defined types of
data: hostname to IP address mappings, perl scripts, or Cypherpunks
messages. Being authoritative depends upon the data merchant
maintaining a persistent reputation. Interestingly an authoritative
source doesn't actually have to store any data, it may operate purely as
a locator service.
Speed. Some data merchants may strive to provide data rapidly but
spending more on rotating media, doing more aggressive prefetch and
caching, and having bigger servers and network connections. For some
customers and some data, paying a premium for speed could be quite
desirable.
Anonymity. Guaranteeing privacy for a client's requests could be an
attractive option. This is an other feature that would depend upon the
merchant maintaining a good reputation.
[1] Mark S. Miller and K. Eric Drexler, "The Agorics Papers",
http://www.webcom.com/~agorics/agorpapers.html.
[2] Norman Hardy and Eric Dean Tribble, "The Digital Silk Road",
http://www.webcom.com/~agorics/dsr.html.
[3] http://www.transarc.com/~ota/RecursiveAuctionMarket.txt
[4] eternity data storage service
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Robert Hettinga ([email protected]), Philodox
e$, 44 Farquhar Street, Boston, MA 02131 USA
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