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.
Voluntary compliance as a necessary feature. By Dana Edwards. Posted in Steemit. September 29, 2018.
Voluntary compliance in moral alignment with the participant
Every platform which is decentralized in my opinion should allow it's users to comply with the laws of their local jurisdiction to the degree which each user thinks is moral. The platform should not enforce the laws of any specific jurisdiction or remove the ability of any user to comply with the laws of their local jurisdiction. This means if a user would like to track and pay taxes the platform should provide a means for users to do this. This means if users would like to go through KYC before interacting with ICOs so that their accounts are whitelisted by banks they should be allowed. This also means that if a user thinks that a certain regulation or rule or law is immoral that they should be allowed to make up their own mind and take their own risks.
In other words platforms should not choose for users what is right and wrong. Platforms should simply provide the tools so that each person can decide how much risk they are willing to accept in alignment with their morality. The ability to comply with the law is necessary for mainstreamability. Mainstreamability ability is about winning the long war rather than the little battle. In order for crypto to have the maximum positive impact on future generations it must go mainstream and escape from the fringe use cases. This applies as much to Steem as it does to Ethereum as it does to Tauchain. Mainstreamability are the key elements which enable mainstream adoption success.
Legal contracts as tokens
Compliance can be modularized, tokenized, decentralized. Legal contracts can become tokens. The risk (and it is real) of money laundering or rogue nations violating sanctions can be reduced by decentralizing AML/KYC. At the same time regional locks in my opinion are one of the worst ideas and should not be technically enforced. Once again compliance should be voluntary but always allowed.
What does it mean to voluntarily comply? A participant can choose to comply to reduce their risks. The participant who does not comply is willing to take the risk of non-compliance. This means compliance is a means of risk reduction. But in a decentralized network such as a decentralized exchange the risk is entirely on the users. The users can decide (and only the users) which level of risk is best for them. Developers of the platform should have no responsibility to decide for the users of the platform what is morally right or what risks are acceptable or unacceptable to take.
Ohad Asor the lead developer and founder of Tauchain releases first new blog post in over a year. By Dana Edwards. Posted on Steemit. December 30, 2017.
The new blog post titled "The New Tau" is available for everyone to read. The blog post speaks on the critical topic of collaborative decision making. This is a topic which I myself have been interested in and Ohad's solution is different from the usual solution. In my own thinking I was considering a solution based on collaborative filtering but I realized this would never scale. I then considered a solution based upon using IA (intelligence amplification) by way of personal preference agents and this does scale but requires that the agents have a lot of data to truly know each user and their preferences. The solution Ohad Asor comes up with attempts to solve many of the same problems but his solution scales without seeming to require collaborative filtering or any kind of voting as we traditionally think about it.
Let me list some of the obvious problems with voting which many will recognize from Steem which also relies on collaborative filtering:
Now let's see what Ohad Asor has to say:
In small groups and everyday life we usually don't vote but express our opinions, sometimes discuss them, and the agreement or disagreement or opinions map arises from the situation. But on large communities, like a country, we can only think of everyone having a right to vote to some limited number of proposals. We reach those few proposals using hierarchical (rather decentralized) processes, in the good case, in which everyone has some right to propose but the opinions flow through certain pipes and reach the voting stage almost empty from the vast information gathered in the process. Yet, we don't even dare to imagine an equal right to propose just like an equal right to vote, for everyone, in a way that can actually work. Indeed how can that work, how can a voter go over equally-weighted one million proposals every day?
This in my opinion is very true. In reality we have discussions and at best we seek to broadcast or share our intentions. Intent casting was actually the basis behind how I thought to solve this problem of social choice but I would say intent casting even with my best ideas would not have been good enough because again the typical voter would be uninformed. Without an ability of the typical voter to be either educated continuously which in a complex world may be unrealistic, or for the network itself to somehow keep the voter up to date, this intent casting barely works. It works well for shopping where a shopper knows what they want but does not work so well when a person doesn't actually know what they want and merely knows what they value. Values are the basis for morality, for ethical systems, and this is the area where Ohad's solution really shines.
Tauchain has the potential not only to scale discussions but also morality, because it will have the built in logic to make sure people can be moral without constant contradiction. The truth is, without this aid, the human being cannot actually be moral in decision making in my opinion due to the inability to avoid all sorts of contradictions.
All known methods of discussions so far suffer from very poor scaling. Twice more participants is rarely twice the information gain, and when the group is too big (even few dozens), twice more participants may even reduce the overall gain into half and below, not just to not improve it times two.
This is the conclusion that Ohad and myself reached separately but it still holds true. We require the aid of machines in order to scale collaborative decision making. This in my opinion is one of the major difference makers philosophically speaking between the intended design and function of Tauchain vs every other crypto platform in development. This also in my opinion is going to be the difference maker for the community which Tauchain as a technology will serve because it will enable the machines and humans to aid each other for mutual benefit or symbiosis.
The blog post by Ohad Asor brings forward a very important discussion which has many different angles to it. The angle I focused on with regard to the social choice dilemma is the problem of how do we scale morality. In my opinion if we can scale morality in a decentralized, open source, truly significant manner, then nothing stands in the way of absolute legitimacy, mainstream adoption, and with it a very high yet fairly priced token. The utility value of scaling morality in my opinion is higher than just about anything else we can accomplish with crypto tech and AI. If the morality is better, then the design of future platforms will be greatly improved in terms of how the users are treated, and this in itself could at least in my opinion help solve the debate about whether AI can remain beneficial over a long period of time. I think if we can scale morality in a decentralized way, it will make it easier to design and spread beneficial AI. Crypto-effective alturism could become a new thing if we can solve the deeper more philosophical problems.
Using Controlled English as a Knowledge Representation language. By Dana Edwards. Posted on Steemit. April 4, 2017.
Previously I mentioned "controlled English" when discussing the concept of knowledge representation. This post will go into some detail about what controlled English is. In specific I will discuss Kuhn's doctoral dissertation and Attempto Controlled English (ACE).
Computational linguistics is an interdisciplinary field concerned with the statistical or rule-based modeling of natural language from a computational perspective.
There are many different controlled natural languages
First I would like to discuss the fact that controlled English is not the only controlled nature language and Attempto Controlled English is only one particular controlled English. For example 1 there is RuleSpeak which is a controlled natural language for business rules. Another example2 is Quelo Controlled English which is a controlled English for querying, where you would say statements such as: "I am looking for something, it should be located in a city, the city should produce a new car, the new car should be equipped with a diesel engine". In addition to these examples we also have Google which uses Voice Actions where you can speak into your android phone and say something like: "Create a calendar event: Dinner in San Francisco, Saturday at 7:00PM". All of these are examples of controlled natural languages and reveal just how powerful this could be for users and developers.
What is Attempto Controlled English (ACE)?
Attempto Controlled English also known as ACE is a specific controlled natural language. It is likely that at some point in the early stages of development this controlled natural language will be implemented on Tauchain. ACE is like English but relies on following certain rules with a restricted vocabulary.
Rule subject + verb + complements + adjuncts
All simple ACE sentences have the above structure of subject + verb + complements + adjuncts. An example would be the following sentences below:
A customer waits.
To construct sentences without a verb you can rely on:
there is + noun phrase
There is a customer.
And you can add detail with:
A trusted customer inserts two valid cards.
And you can use variables:
How does Attempto Controlled English help with Knowledge Representation?
In specific because anyone who speaks English can quickly learn Attempto Controlled English it will mean anyone will be able to contribute to the process of knowledge representation. Contributing to a knowledge base becomes very easy when you can simply describe in plain English (with restrictions) exactly the knowledge you want to represent. A semantic Wiki can be built out of this process rather easily.
How does Attempto Controlled English relate to Tauchain?
Tauchain requires input from the users to determine a formal specification. Attempto Controlled English is simple enough that anyone can describe a formal specification. For example sentences like:
Every customer inserts a card.
As you see above, we are dealing with types. Human is a type. Human is divided at a minimum between male and female subtypes.
And ACEWiki gives an example of what a formal specification could look like in Tauchain. The example being country, where the knowledge in this case is the concept of a country. Then we describe a country by filling in the Wiki collaboratively, where we know first of all that every country is an area, but then collaboratively we fill in the list of current persons who govern a country. Through this method we add to the knowledge base using the knowledge representation language ACE, and in the case of Tauchain we would be adding to potentially a formal specification which eventually is synthesized (program synthesis) by the Tauchain automatic programmer.
To learn more about Attempto Controlled English Wiki watch the video lecture
Kuhn, T. (2009). Controlled English for knowledge representation (Doctoral dissertation, University of Zurich).
Kuhn, T. (2014). A survey and classification of controlled natural languages. Computational Linguistics, 40(1), 121-170.
Kuhn, T. (2009). How controlled English can improve semantic wikis. arXiv preprint arXiv:0907.1245.
Ranta, A., Enache, R., & Détrez, G. (2010, September). Controlled language for everyday use: the molto phrasebook. In International Workshop on Controlled Natural Language (pp. 115-136). Springer Berlin Heidelberg.
Ross, Ronald G. 2013. Tabulation of lists in RuleSpeak—using “the following” clause. Business Rules Journal, 14(4):1–16.
White, C., & Schwitter, R. (2009, December). An update on PENG light. In Proceedings of ALTA (Vol. 7, pp. 80-88).
Web 2: http://attempto.ifi.uzh.ch/site/resources/
Fuente / Source: Original post written by Dana Edwards. Published on Steemit: Using Controlled English as a Knowledge Representation language. April 4, 2017.
Logo by CapitanArt
Enlaces / Links
Logo by CapitanArt
Archivos / Archives
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.