IEEE Technology and Society Magazine - December 2015 - 48

Bias Reduction and
Memory-Reimprinting
Blockchain-based memory aides
are just the first step. A second
killer app that starts to evoke the
ability to work with the data of the
whole of an entity's memory is bias
reduction. It is known that humans
are currently biased in many ways
of perceiving and interacting with
the world, mainly due to evolution
and culture [22]. Some of the many
cognitive biases include loss aversion, overconfidence, confirmation,
rationalization, probability neglect,
and hindsight [8]. (See also LessWrong: http://lesswrong.com/.)
B lo ckc ha i n - b a s e d me mor y
could be used as an input for
the algorithmic assessment of
agent bias, and smart contracts
employed to monitor this in real
time and make bias-adjustment
suggestions to ameliorate actions
or conceptualizations. A third killer app could use blockchain-based
memor y ledgers together with
pattern-recognition algorithms
for mental health improvement.
In some areas of therapy, one
main psychological operation is
helping individuals reimprint the
memories of earlier experiences
in a more resourceful way. Early
memories are encoded in the
child brain in different stages of
development, and can later recur
in strange, artificial, exaggerated, and unempowering ways that
hamper productive and healthy
adult life. Situations often repeat
that relate to the same underlying issue that was initially poorly-coded. Psychologists seek to
trace back and root out all of the
instances, starting with the most
recent, having only the crude and
imprecise tools at their disposal of
individuals working with their own
subjective memories. A future use
of blockchain-based memory to
address this could be a DIY Reim-

The obvious question is why
with all of this raw computing
power are there not AI applications closer to human intelligence
in the ability to solve general-purpose problems (e.g.; any new problem). This is because comparing
raw computational capacity is just
one metric, and probably not the
right one for assessing intelligence
or understanding the complexity of the human brain [28]. The
parallelized modular architecture
of supercomputing is nothing like
human brain architecture. Digital
is not analog. Signal transmission
and processing is different in biological systems, with a variety of
analog parameters such as context
and continuum determining the
quality, quantity, and persistence of
signals. This could be why Digital
Thinkers and general AIs do not yet
exist. The reason is because supercomputing, for all its power, is still
monolithically homogeneous.
Supercomputers do not think but
only have simple linear architectures massively replicated. One
claim is that for a Digital Thinker
to think, it would need to think
more like humans, with analog
signal valences, non-linear architectures, and greater complexity.
Some approaches to developing general-purpose problem-solving digital intelligences use deep
learning algorithms and large
data corpora to simulate or emulate whole-brain thinking. This
approach may yield useful results
for some kinds of AI applications
but is still far from representing
the messy non-linear "wet" architecture of biological systems like
the brain in silico. Instead, blockchain technology might be a helpful addition to these approaches
in allowing the development and
coordination of decentralized architectures and clusters of non-linear
functionality that are more like

printing app where optimal mental
performance coaching algorithms
continually canvas for potential
issues, including surfacing potential situations for reimprinting.

Processing
In addition to memory, storage,
and file-serving as key inputs for
creating Blockchain Thinkers, processing is the next element of the
inputs-processing-outputs architecture. One benefit of blockchain
architecture, and Internet architecture more generally, is decentralized
processing and massive network
redundancy. In the blockchain context, there could be an opportunity
to reinvent the operation of thinking
in a decentralized way. What would
it really be like to have packetized
thoughts and packetized thinking?
Blockchain-based decentralized
memory storage was discussed, but
perhaps an even greater benefit for
higher-potentiality thinking is the
possibility of distributed processing. A Digital Thinker could have
decentralized processing nodes that
reassemble back into the goal or
task. It would be like giving a brain
additional processing nodes. Supercomputing is an existing example of
massively-parallelized processing,
however this is of a "Level 1" variety
such that tasks can be neatly packaged into many similarly-structured
parallelizable computations whose
results can be easily coordinated
back into the larger system. The raw
compute capacity of supercomputers surpassed that of the human
brain (estimated at 1013-1016 operations per second [12] in 2012 with
IBM's Sequoia BlueGene/Q at 1016
flops, and as of November 2014
had reached 1034 flops with China's Tianhe-2 at the National Super
Computer Center in Guangzhou, a
TH-IVB-FEP Cluster with over 3.1
million cores (http://www.top500.
org/lists/2014/11/).
IEEE Technology and Society Magazine

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december 2015

http://www.lesswrong.com/ http://www.top500

Table of Contents for the Digital Edition of IEEE Technology and Society Magazine - December 2015