The Era of Signals and Changing Power Dynamics. By Dana Edwards. Posted on Steemit. October 8, 2018.
The world we live in is rapidly changing. For instance the #MeToo era has arrived. This new era shows us that any individual in any position in society can be brought down. It proves a point that many in the blockchain community may have known instinctively which is that any individual source of authority and or power can and may be removed from that position. Some people actively choose to seek to be in these positions of power for their own reasons and then some of these people abuse their positions of power. People who seek power for the wrong reasons and then abuse it are in my opinion a risk which positions of authority bring (which blockchain technology may help reduce).
What are signals and what is signalling theory?
Social desirability bias is a popular topic in academic circles. To explain:
In social science research, social desirability bias is a type of response bias that is the tendency of survey respondents to answer questions in a manner that will be viewed favorably by others. It can take the form of over-reporting "good behavior" or under-reporting "bad," or undesirable behavior. The tendency poses a serious problem with conducting research with self-reports, especially questionnaires. This bias interferes with the interpretation of average tendencies as well as individual differences.
People tend to want to be liked/loved. People when asked questions on a survey may feel pressured to answer the survey in a way which they think they will be viewed more favorably by others. In other words rather than answering in a manner which they truly think or feel they will assess how others might judge their response and then answer in a way which they think they will be judged more favorably.
A full video on this topic is below:
Social desirability bias is exactly why voting on platforms such as Steem will not work. When voting is public then most of the research seems to show that people will feel pressured to answer the question not in the way which they really believe or prefer but in the way which they think the whales want them to vote or prefer. In other words because on Steem the whales can reward (or punish) anyone who votes in ways which go against "political sensibilities" it is likely that social desirability bias applies particularly on DPOS style consensus platforms. If there are votes and the votes are not encrypted (secret) then we have no way to determine which votes are legitimate and which votes are the result of signalling (such as virtue signals).
For example when it was Trump vs Hillary the polls suggested Hillary would win. This is because there likely was social desirability bias which made it socially undesirable for anyone to admit they voted for Trump. As a result people who voted for Trump or who planned to vote for Trump may have said in public that they intended to vote for Hillary. Because the votes in the election are secret the people who may have seemed like loud Hillary supporters could have been secret Trump supporters in disguise.
In some of my previous posts I discuss signalling theory a bit more:
In these posts I have identified that behavior of individuals is shaped by how individuals think other individuals will think of their behaviors. This would apply to social desirability optimization which I'll label as adopting behaviors which provide the expected payoff of being rewarded with improved social desirability.
To provide clarity the definition of social desirability:
Social desirability is the tendency for research participants to attempt to act in ways that make them seem desirable to other people.
In other words people want to be liked. Likeability is a word I can use to simplify the concept of social desirability for readers. In the example with the 2016 election it is clear that supporters of Trump would risk a social stigma with severe social consequences if they came out in public support. This high cost of public support is why some believed that there were secret Trump supporters who were simply afraid of "losing face". In the most simple terms a person can talk red or talk blue depending on where the social stigma is.
One of the stunning conclusions I reached in my own research on this topic is that the increasing transparency leads to "preference falsification". That is a person who is talking blue while thinking red. If all speech is public (like it is on Steem) then there is the possibility that preference falsification is taking place.
Here is a video on the topic of preference falsification:
Why is this a major problem in the blockchain community? The evolutionary trajectory of a platform relies entirely on market preferences. If censorship exists and conformist pressures hinder true preference aggregation then the developers (and the community itself) will have no way of knowing which improvements to make or which changes would best satisfy the community.
What is leadership and what is the era of signals?
Before I attempt to discuss leadership I will first explain what I think leadership means and what it is. In my opinion the community must always come first. A person who is put into a leadership position is in my opinion in what I'll term "the seat of responsibility". This is in my opinion not an enviable position to be in but someone has to be in this position. For example a person who receives a security clearance is now in a position of heavy responsibility. The information which they protect is not their secrets but the nations secrets.
Leadership in my understanding is not about "being in power" but is about serving a community. To be in a "big seat" is to be in a position of responsibility to make decisions on behalf of a community which the chosen person must represent. In other words being in positions of responsibility is entirely about service and not about power. A representative in congress is not in a position of power but in a position to serve their constituents who put them in that position to represent their interests.
In my opinion to be a good leader is to be a great listener. The leader must listen to the community to find out what the community wants and or needs. The leader must listen to the community to determine what the community thinks is right or wrong. The leader then must offer solutions or proposals or policies which satisfies the requirements of the community. What matters more than who is in the seat is the seat itself. This means the Presidency itself matters more than who is in office. The positions themselves matter more than who is in them. Long after whomever is in these positions are gone there will be these positions to be filled. Any leader in any position is replaceable by someone else if they show failure to lead (whether it be a CEO, or a President of a country, or a lead developer, or any other kind of community leader).
In my understanding it is like chess where all pieces on the board can be in various positions. We know in chess that the pawn can become any piece on the board. The point with this analogy is that individuals in my opinion are not likely to remain the source of power in society. The source of power in society is increasingly becoming the community for better or for worse. According to me, to lead is to serve and to lead effectively is to serve effectively.
To accept a responsibility to serve (to lead) it is required to seek feedback from all whom the community servant represents. This does not require voting specifically but it does require under any circumstance a mechanism by which the community can give brutally honest feedback to the system itself. When I say the system itself I do not mean the feedback must go direction to those who serve the system but that the system must have a means of collecting data, analyzing data, and then informing those who can improve the system on which changes best would satisfy the needs of the community.
In my opinion this is a very data driven process. I do not think leaders can for example process big data using their brain power. This will require that they harness the power of machines (machine intelligence). There is also risk if all the processing is done by one company (such as Google) just as there is risk if all people rely on Facebook for the news and opinions. We can see that Facebook has the ability right or wrong to shape elections by deforming the news feed or by allowing certain fake profiles to interact on the site. We see that Facebook can ban crypto ads at will for example to enforce certain policies without taking any kind of poll from the community or the users for instance. We simply do not see any poll data from the users which indicated that the users were tired of seeing crypto ads.
Summary of thoughts on leadership:
Augmenting the wisdom of the community as a means of better governance
In a world where the community must decide what to do we have a situation where responsibility is increasingly diffuse. This means while it is true that the signature may come from the face of the community (if it is a human face) it is still the community which has to be capable of wisdom. The problem is most communities in the world do not become wiser as more join the community. A bigger community doesn't produce better policies by merely voting together. The problem is while most people have opinions it does not mean opinions are well informed or scientific or wise. The lack of wisdom in a community results in horrible (harmful) policies, over reactions, systemic bias, and more.
The conclusion I have reached so far is that in order to have better governance in an era where the community is the government it is a requirement that the community be wise. It's not enough to simply give the community unlimited power to shape the future without providing any capacity for the community to be wise or to do research or to solve problems. Voting in the sense we see in elections does not involve informed voters. Information supplied to voters is almost always sub par and voters are expected to trust "opinion leaders" and "opinion shapers" who tell them how to vote and why. Often disinformation shapes elections more than scientific evidence, facts, math, or reason.
As we build blockchain technology I think it is critical that we put great emphasis on data analytics. Data analytics will allow our leaders to make better decisions on our behalf. Blockchain technology will have to rely on data analytics to figure out potential wants and needs of it's participants, users, e-citizens, etc. At the same time private communication will be a necessity even if just to conduct surveys. The reason is people will not necessarily provide their real opinion in a survey which is completely transparent. The only solution I could find to the problem of preference falsification is privacy.
Most important of all is those who are put into positions of leadership are in trusted positions. This includes people who are moderators at forums, people who are lead developers, people who run exchanges. People who are in these positions have the responsibility to serve the blockchain community to the best of their ability. The abuse of these positions for personal power or personal gain is a violation of this trust and in these instances the community can and should select someone else for that position.
Bulbulia, J., & Sosis, R. (2011). Signalling theory and the evolution of religious cooperation. Religion, 41(3), 363-388.
Davis, W. L. (2004). Preference falsification in the economics profession. Econ Journal Watch, 1(2), 359.
Frank, R. H. (1996). The Political Economy of Preference Falsification: Timur Kuran's Private Truths, Public Lies. Journal of Economic Literature, 34(1), 115-123.
Grimm, P. (2010). Social desirability bias. Wiley international encyclopedia of marketing.
Sîrbu, A., Loreto, V., Servedio, V. D., & Tria, F. (2017). Opinion dynamics: models, extensions and external effects. In Participatory Sensing, Opinions and Collective Awareness (pp. 363-401). Springer, Cham.
In a recent article of mine  I hinted my strong suspicion that scaling is itself scalable.
''Scaling is a problem. Scaling must be scalable, too. Metascale from here to Eternity.''
No matter what a terrific grower a system is - as per its own internal algorithmic growth drive rules - it seems inevitable its growth to get it into entropic mutualization  upon impact with a kind of a ... downscaler.
Scaling is everything, yeah. But it is quite intuitive and supported by too big body of evidence to ignore, that, paradoxically: the faster a thing grows - the sooner its encounter with an external and bigger downscaling factor comes.
This realization, refracted through the prism of our 'reptilian brain' layer  amplified to gargantuan proportions by our inherent social hierarchicity  is the source of the 'Malthusian  anxiety' which led to countless violent deaths over all the human history. Fear is anger , so the emotion that there is only as much to go around, and that the catastrophe of 'running out' of something is imminent, is the major source of what makes us bad to each other .
There are plethora of examples of very well mathematically and scientifically grounded doomsayer scenarios, and we must admit that they all correct as per their internal axiomatics  , and simultaneously they are all totally wrong for missing out the obvious - the factors of externalities  , the properties and opportunities of the medium which is consumed and/or created by this growth, and which transcend the axiomatics. For growth being always 'growth into'. The fact that doomsday scenarios are so compellingly consistent internally is what makes them so strong and dangerous ideological weapon of mass destruction .
Lets throw some such problem-solution couples for clarity:
a. the world of 1890es big cities sunk up knee-deep into beast of burden manure , and the super-apocalyptic projections of that VS Tony Seba's  1 pic > 1000 words of NYC carts vs cars situations in 1900 -1913 ...
b. the grim visions of the whole Mankind becoming telephone switchboard blue collar workers , the number of which should've exceeded the number of total world population by now to achieve the same level of telephonization or
c. the all librarians world  where it takes more librarians than the whole mankind to serve the social memory in the paper & printed ink storage facilities mode ...
d. the Club of Rome  as the noisiest modern bird of ill omen with 'projections' based on the same blind extrapolations as the urban seas of shit or the 'proofs' of the impossibility to connect or educate or feed all - instigating mass destruction fear that ''we run out of everything and will soon all die'' , used for justification for mass atrocities VS Julian Simon's  - the ''Ultimate Resource'' (1981, 1996) . Cf.: my accelerando article  and see what precisely is the Factory for succession of better and better Hanson drives for the last few millions of years - from the Blade and the Fire to the Tau - it is the same thing which identification made Julian Simon from fanatical Maltusianist  into rationally convinced Cornucopian  ... the human mind.
e. the predator-pray model  which this pseudo-haiku  I guess depicts best how's it brutally flawed:
''hawk eat chic -> less chic, human eat chic -> more chic''
for missing out to posit and failure to account for positive feedback loop  of predator over pray dynamics ...
f. The comment of Dary Oster  , founder of the other passion of mine - ET3 , on the aka 'saturation' of the scalables (exemplified in the field of transportation, which btw, being communication ... our social structures map onto mobility systems we have on disposal ... ).:
''... US transportation growth has focused on automobile/roads (and airline/airport) developments. (And this has been VERY good for the US economy.) The reason is that cars/jets offered far better MARKET VALUE than horse/buggy/train transport did 150 years ago. In the mid 1800s, trains displaced muscle power for travel between cities - because trains offered better market value than ox carts. Trains reached 'market saturation' about 1895 to 1905 (becoming 'unsustainable') - however 'market momentum' produced 20 years of 'overshoot'. Cars/jets were far more sustainable than passenger trains and muscle power, and started to displace trains (and finish off horses). By 1916 the US rail network peaked at 270,000 miles (today less than 130,000 miles is in use).Just like passenger trains hit market saturation, roads/airports are reaching economic limitations. The time is ripe for a market disruption, and all indicators (past and present) say it will NOT come from, or be supported by government or academia -- but from private sector innovations that offer a 10x value improvement (like ET3), AND also offer incentives for most (not all) key industries to participate (like ET3). Automated cars, smart highways, and electronic ride sharing are industry responses that will contribute to overshoot of cars/roads for the next 5-10 years.The main problem i see with the education system is that is that academic research and publication on transportation is primarily funded by status quo industries like: railroads and rail equipment manufactures, highway builders, automobile/truck manufactures, engineering firms, etc. -- all who fund research centered on 'improving' the status quo.Virtually all universities (for the last 1k years+) are set up to drive incremental improvements that industry demands, and virtually all paradigm shifts are resisted until AFTER they occur and are first adopted by industry. Government is the same (for instance in 1905 passing laws to forbid cars that were disrupting horse traffic; or in 1933 passing laws to limit investment in innovation startups to the wealthy (those successful in the status quo)).''
g. Darwinian algo  sqrt(n) VS higher algos - like Metcalfe n^2 . It is not precise, it is more of metaphorical, to indicate direction or scale of scaling, rather then rigorous precision, but ... the former figuratively speaking takes 100 times more to put up 10 times more, and the later takes 10 times more to return 100 times more...
h. Barter vs money. See.:  bottom of page 5 over the bottomline notes, about the later:
simpliﬁes pricing calculations and negotiations from O(n^2) complexity to O(n) complexity
As demonstration how one item out of a scaling barter system, emerges as specialized transactor and accelerator to transcale the barter economy. From within. Endogenously as always. (btw, Extremely strong document where there are entire books read and internalized behind each tight and contentful sentence!)
i. The heat death of the universe  VS the realization that the 2nd law  - conservation law for entropy/information law does not allow that , the asymptoticity  of the fundamental limits of nature, the fact that max entropy grows faster than/from/due to the actual antropy growth  and that entropy is not disorder  and that at the end of the day it is an unbounded immortal universe  ... cause it's all a combinatorial explosion .
j. The Anthropic principle  and the realization that it is extremely hard if not impossible to posit a lifeless universe  ...
k. The Algoverse - my 'psychedelic' vision  of the asymptotic inexorable hierarchy of the Dirac sea  of lower algos which take everything for almost nothing - up towards giving almost everything for almost nothing - Bucky Fuller's runaway Ephemeralization . Algorithms are things. Objects. Structure. Homoousic or consubstantial to their input and output. Things taking things and making things outta the former. Including other algos of course! Stronger ones.
l. The Masa Effect . The Master of Softbank seeing how the machine productivity is on the imminent course to massively overscale the human clients base and his apparent transcaling solution to upscale the clients base with bots and chips, with the same which scales supply in such a too-much way. 
m. The Pierre the Latil 1950es and Stanislaw Lem 1960es ( copied 1:1 by Tegmark  ) hierarchy . Of degrees of self-creating freedom of Effectors ...
n. Limits of growth - present in any particular moment and in any finitary setting of rules ,  but nonexistent in the infinity of rules upgradability. Like a cancer cell trapped in a cage of light  vs ... photosynthesis.
o. Ray Kurzweil - static vs exponential thinking .
p. Craig Venter's  Human Genome project  which when commenced in 1990 was ridiculed that will be unbearably expensive and will take centuries to finish, and it did - it costed a unbearable for 1990 fortune and it did take centuries, of subjective time as per the initial projections conditions - being completed in year 2000.
q. Jeff Bezos vision  of Solar System wide Mankind:
''The solar system can easily support a trillion humans. And if we had a trillion humans, we would have a thousand Einsteins and a thousand Mozarts and unlimited, for all practical purposes, resources.''
r. The 'wastefulness' of data centers and crypto mining collocation facilities  ... which is as funny as to envy the brain for 'wasting' >25% of the body energy. (Btw, the tech megatrend is exponentially and relentlessly towards the minimum calculation energy).
s. The log-scale intuitive measure and smooth straight line visualization coming out of, this quote which I fished out off the net long time ago.:
"The singularities are happening fairly regularly but at an increasing rate, every 500 to 1000 billion man-years (the total sum of the worldwide population over time). The baby boom of the 1950 is about 200 Billion man-years ago."
ops! go back to Q. With 1 trln. humans population the 'singularities' will occur once a year?!
t. the Tau  !!
I can continue with these examples ... forever [wink] - excuse me if I've bored you - but I think that at least that minimum was needed to be shown and it is enough to grok the big picture.
Scaling is the solution. It is a problem too. Its overcoming is what I dub 'Transcaling' for the purpose of that study.
Size matters. Scaling is the way. But the more general is how a system handles change! This is as fundamental as to be in the very core of definition of life and intelligence .
Tauchain is all about change handling!
Now, lets knit the 'blockchain' of these all example threads above into a knot like the Norns do :
Dear friends, please, scroll back to Example D. Yes, the human mind transcaler thing. The Ultimate resource thing.
We are the ultimate resourse.
We the humans (and soon the whole zoo of our technological imitations and reproductions and transcendences of ourselves ).
We as the-I  are strong thinkers and creators, immensely more road lies ahead than it's been traveled, yes, but yet we, as the-I, are the momentary apex in the Effectoring business  in the Known universe ... AND simultaneously we as the-We are mediocre to outright dumb.
We are very far from proper scaling together. The Ultimate resource is not coherent and is not ... collimated. Scattered dim lights, but not a powerful bright mind laser. Dispersed fissibles, but not a concentration of critical masses.
We as The-We - paradoxically- persistently finds ways to transcale its destinies using the power of the-I, but the-We itself does not entertain the scaling well at all .
The individual human mind is the unscaled transcaler.
Tau is the upscaler of that transcaler.
I'll introduce herewith another 'poetic' neologism, which occurred to me to depict the scaling props of a system after the Scrooge factor of ''Tauchain - Tutor ex Machina'' , and it is the:
Spawn  factor
- the capacity and ability of a system to grow through, despite, against, across, from and via the changes. Just like cuboid  is about all rectangular things like squares, cubes, tesseracts ... regardless of their dimensionality, the Spawn Factor - to be a generalization of all orders of scaling. Zillion light years from rigor, of course, as I'm on at least the same distance from my Leibnizization . For the lawyer to become a mathematician is what is for a caterpillar to become a a butterfly. :) Transcaling.
Tau transcends the infinite regress of orders of: scaling of scaling of scaling ... by being self-referential. Or recursive. 
What is the Spawn factor of Tau?
If you let me I'll illustrate this by a poetic periphrasis of the famous piece of Frank Herbert's .:
I will face my change. I will permit it to pass over me and through me. And when it has gone past I will turn the inner eye to see its path. Where the change has gone there will be nothing. Only I will remain.
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Suggested readings to better understand the Tau ecosystem, Tau Meta Language, Tau-Chain and Agoras, and collaborate in the development of the project.
Lecturas sugeridas para entender mejor el ecosistema Tau, Tau Meta Lenguaje, Tau-Chain y Agoras, y colaborar en el desarrollo del proyecto.