Tag: democracy

Text Analytics Tools for Deliberative Democracy

In our last post, we spoke about various control mechanisms that can be implemented to support direct democracy (which we  interpreted to mean the control of the allocation of common resources by the people who pooled in).

We also examined how these controls could be used to curtail man-in-the-middle corruption.

In this article, we examine a more sophisticated form of direct democracy called a deliberative democracy.

In a deliberative democracy, in addition to the control mechanisms prescribed for direct democracy, there need to be mechanisms to allow deliberation (discussion) before a referendum or any other action is taken.

I quote from the Wikipedia article on deliberative democracy:

Deliberative democracy holds that, for a democratic decision to be legitimate, it must be preceded by authentic deliberation, not merely the aggregation of preferences that occurs in voting.

In elitist deliberative democracy, principles of deliberative democracy apply to elite societal decision-making bodies, such as legislatures and courts; in populist deliberative democracy, principles of deliberative democracy apply to groups of lay citizens who are empowered to make decisions.

The article on direct democracy had the following to say:

Democratic theorists have identified a trilemma due to the presence of three desirable characteristics of an ideal system of direct democracy, which are challenging to deliver all at once. These three characteristics are participation – widespread participation in the decision making process by the people affected; deliberation – a rational discussion where all major points of view are weighted according to evidence; and equality – all members of the population on whose behalf decisions are taken have an equal chance of having their views taken into account.

(Aside to computer scientists: doesn’t this trilemma remind you of the CAP theorem that applies to database systems? Here’s a simple explanation of the CAP theorem: http://ksat.me/a-plain-english-introduction-to-cap-theorem/).

So, for example, representative democracy satisfies the requirement for deliberation and equality but sacrifices participation.

Participatory democracy allows inclusive participation and deliberation but sacrifices equality.

And then there is direct democracy which supports participation and equality, but not deliberation.

The problem seems to be that when a large number of people are invited to participate in a deliberation (and given that deliberations take time), it will not be possible to compensate them all for their time. Consequently, only those more interested in the issue being debated (or more likely to benefit from one position or the other) are more likely to participate, biasing the sample in their favour (all sections of the population are no longer equally represented in the discussion/decision).

So, it seems that all the three properties desired in an ideal democratic system – participation, equality and deliberation – cannot be present at the same time in a real democratic system.

But then, a while ago, we began wondering if this trilemma is merely a result of the lack of suitable technology and not really a fundamental property of democracy.  So, we proposed a design for (though we have not yet realized it) a tool that can support the participation of a large number of people in deliberations.  We call it the MCT (Mass Communication Tool).

It could be used as a method to enable direct democracies to support deliberations in which all citizens can participate, ahead of a vote on any subject.

It uses text clustering algorithms to solve the problems of volume as well as numeric asymmetry in the flow of communications between the deliberating participants and the moderators of the communications.

There’s a brief overview of the system in our lab profile.

MCTs are bound to have a huge impact on our experience of representative government.  A typical use case would involve a public figure, (say President Obama), sounding out the electorate before introducing legislation on say healthcare reform.

 

By first discussing the competing proposals with large numbers of people, it might be possible for the initiator of the discussion to get a sense of what might or might not work and what the response to the legislation was likely to be.

 

An MCT would have to be capable of supporting a live dialog involving a large number of people.

It would use natural language processing and machine learning to enable a few moderators (for example, the CEO of a company) to interact with a large number of people (for example, all the employees of the company) in real time (for example, during a virtual all-hands meeting), get a synopsis of a large number of concurrent discussions in real time, and participate in a significant fraction of the discussions as they are taking place.

The system would consist of:

  1. an aggregator of messages (built from natural language processing components) that groups together messages and discussions with identical semantic content;
  2. a hierarchical clustering system (built from natural language processing components) that assigns aggregated messages their place in a hierarchy by specificity with more general messages closer to the root of the hierarchy and more specific messages closer to the leaves of the hierarchy;
  3. a summarization system (built from natural language processing components) that creates a summary of the aggregate of all messages in a sub-tree; and
  4. a reply routing system (built from natural language processing components) that routes replies from cluster to cluster based on their relevance to the discussion threads.

Direct Democracy and Implications for Research

Direct democracy can be broadly interpreted to mean the control of the allocation of common resources by the people who pooled in.

One common resource is tax money.

In most countries, those who pay taxes only have a say in whom they can elect to power.

Those who pay taxes rarely have a say in how the tax money is spent.

There is a middleman (someone who works in government) who decides how the tax money is spent.

The problem with having a middleman decide the allocation of common resources, is that the resources could end up being allocated very inefficiently due to man-in-the-middle corruption.

Here is an article about man-in-the-middle corruption:

The way out is to let the people who contributed to the common pool decide on how the resources are allocated.

Control Mechanisms

Tool 1: Apportioning

One way to do this is to embed direct democracy mechanisms into the contribution mechanism.

For example, tax-payers could be given the ability to tie a portion of their tax contribution to expenditure categories.

They could be given the right to apportion, out of every $100 that they have paid in taxes, a certain amount to each of the following major categories: education, healthcare, social security, infrastructure and defence (leaving a certain percentage to the finance minister’s discretion).

It could also be left to the tax-payers to specify how much money the government may borrow on their behalf.

This direct control could very likely have prevented the debt crises of Greece and Ireland (and especially in countries where people are averse to taking on debt), and might also have given people in the USA some control over their government’s borrowings.

Tool 2: Referendum

Another mechanism is the referendum.  It is already being used in all democratic countries, but mainly for the selection of the middleman.

Fortunately, things seem to be moving well beyond that stage.  In India, baby steps are being taken towards bringing about a direct democratic model of government.

A new political party came to power in Delhi on an anti-corruption platform.  The first thing they did was conduct an informal referendum to ask the people of Delhi if they should form a minority government.

So, referendums are one of the mechanisms of direct democracy.

This mechanism can also be used to prevent or reduce man-in-the-middle corruption.

Take the example of a road that needs to be surfaced.  Normally, a government official would have issued contracts based on the bribes paid to him by the contending contractors (rendering a selection on the basis of quality very unlikely).

If instead, the people living on the street that needed to be surfaced had been given all the relevant information needed to make a good choice and asked to select the best contractor for themselves instead, the middle-man would have been eliminated and the quality driven up instead of down.

Now, I am going to talk about some problems that I think affect research funding in the USA (and other countries with government-funded research).  Most research funding in the USA comes from government bodies like the NSF, the NRO and DARPA.

Now the following is only my personal opinion, but I think that research efforts in some fields in those countries might be distorted to some extent by the needs of these funding bodies.

Well, I can only speak for the research areas in which Aiaioo Labs is active.  We focus on a narrow research space – predominantly on text analytics and natural language processing.

In this space, I see a lot of low-hanging fruit that nobody in the USA or Europe ever picks.  And that’s quite inexplicable as these are often problems with very obvious applications to the software products space.  And yet I see no papers from California on them.

There are topics on which all the papers I see are from India (often by students who don’t even publish them in international conferences) and sometimes by researchers from Singapore – completely ignored by the main research community.

At other times, I’ve noticed areas of research that DARPA had spent much money on in the 1970s and that researchers had pursued very enthusiastically in that decade.  I’ve seen those lines of research being abandoned in the 90s (possibly once the funding priorities changed) and not being revived again, though product firms are working on those technologies again in California in 2013.

I find it hard to explain why these areas of research are being ignored, except by the remote possibility that they have passed under the radar of the guys in the Naval Research Office which makes it unlikely that grants will be provided for them.

That is again, if my conjecture is right, a man-in-the-middle problem.  The agenda for research is possibly not being driven by the research community or by the market (the needs of start-ups in California) but by people guessing at what sort of proposals might get funded (and that might be encouraging people to stay with what government knows).

So, I shall propose another direct democracy tool to solve this problem as well:

Tool 3:  Suggestions + Referendum

Here, each of the participants (researchers) bidding for the grants would put in suggestions about what the next important thing to focus on as a research community might be.  Then they could all vote on the suggestions.  The allocation of research grants could then be guided by the suggestions and the votes received by each suggestion.

Controls as Rights

In a sense, you can think of these three control mechanisms as three rights that people who contribute toward a common pool of resources will have in a direct democracy:

1)  The right to apportion

2)  The right to be consulted

3)  The right to suggest

There is a nice article on Wikipedia on direct democracy.  The article talks of two of the control mechanisms proposed in this article – referendum and initiative (which corresponds somewhat to suggestions) – and proposes one that I hadn’t mentioned – the right to recall.  It doesn’t talk about apportioning.

Here is an interesting video of a Mohalla Sabha (it’s an interesting participation mechanism that a political organization is experimenting with in Delhi).

Using text analytics to prevent O(log n) failure of democratic institutions

In this article, we discuss an Achilles’ heel present in many democratic institutions.  We claim that many democratic institutions can be made to fail in ‘log n’ time (exponentially fast) if patronage (nepotistic) networks are allowed to grow unfettered.

We then support the claim using real-world examples of the failure of democratic institutions (political and otherwise) and discuss why such failure has not been observed in polity in India.

We also look at how text analytics can be used to detect (and consequently enable steps to be taken to prevent) such failures.

The Weakness

In democratic institutions, voting mechanisms are used to confer upon one individual (from a field of eligible candidates), powers and responsibilities as specified in the charter of the institution.

In some cases, the powers that accrue to the elected individual are so great that they enable him to use them to ensure his or her re-election.  There are two methods available to such an individual.

The first is to pay off the electoral college and secure re-election.  This method is an O(n) algorithm.  The quantum of resources required to secure re-election is proportional to the number of people who need to be suborned.  So, this method only works in cases where electoral colleges are small (for example, in the case of committees deciding job appointments).

A faster method of suborning large numbers of people exists.  The establishment of a hierarchy of patronage can leverage the dynamics of social networks to speedily (in log n time) corrupt very large numbers of people.

It works like this:  The person who is elected to head the country appoints as immediate subordinates only people who are on account of tribal or ethnic affiliations expected to be loyal to him/her. This appointment is often accompanied by a monetary exchange in the form of a bribe paid by the appointee to secure the post.  Such a monetary exchange helps cement the loyalty since the person making the payment becomes dependent on their superior’s continuation in power to recoup the money spent. In other words, the immediate subordinates are forced to invest in their superiors’ careers.

The subordinates so appointed in turn appoint people loyal to themselves to positions below them, in order to recover their investment in the person above them and so on.  Very soon, the entire government machinery becomes beholden directly or indirectly to the person at the top for their jobs and has a vested interest in keeping the person at the top in power.

In some countries, this effectively transforms the democratically elected ‘president’ into a dictator for life. 

Example 1

The first example of such failure is possibly (and I am just illustrating a point – no disrespect intended) the government of Cameroon.  The President of Cameroon has been in power since the 1980s.  The President is impossible to replace in spite of rampant corruption and economic mismanagement because all the tribal chiefs and officials in Cameroon are beholden to the President.

All these officials and chiefs try and recoup their investment by rent-seeking behavior (you will need their good offices if you wish to do any business in Cameroon).

The resulting economic climate doesn’t necessarily encourage the growth of entrepreneurship or investment in Cameroon.

Example 2

Iraq for many years was ruled by a dictator who had managed to suborn an entire political system.  Iraq once had a participatory democratic system.  But the use of patronage by Saddam led to Iraq coming under totalitarian rule.

Similar failures can be seen in post WW2 Libya and Syria, and in Stalin’s Russia.

India

One common feature of many of the countries where such failure has occurred is that they have hierarchical social structures in which respect and obedience can be commanded by people higher in the hierarchy from people lower in the hierarchy.

Cameroon has a culture of veneration of elders and tribal leaders.  So do the countries of the Arab world.

India also has somewhat similar cultural traits.  So, it is very interesting to see that a similar process of deterioration of democracy has not been observed in India.

One explanation is that India was saved by its own heterogeneity.  India is made up of distinct linguistic regions and ethnic groups.  It would be impossible for tribal and ethnic hierarchies to span India’s many linguistic and ethnic boundaries.

So, even if one province has failed, that would not trigger failure in neighboring provinces, and the regional despot would not be strong enough to change the Indian constitution.

Examples of such failure can arguably be observed to have happened already in Karnataka and in Tamil Nadu.  In Karnataka, a couple of mining barons managed to become ministers in the government and managed to exercise a lot of control over it for a number of years. Had Karnataka been an independent political entity, they might at some point have attempted to change the constitution to give themselves more power and possibly unlimited tenure.

In the state of Tamil Nadu, the ruling politicians are suspected of building patronage networks around themselves in order to facilitate rent-seeking behaviour.  If Tamil Nadu had been an independent political entity, I suspect that it might have lost its democratic character, since the number of people below the Chief Minister with a vested interest in keeping him/her in power would have become too big to permit free and fair elections to take place.

But what is interesting is that in India, though democracy could have failed at the level of the states (controlled by politicians who had suborned a large part of the mechanism of government) the possible failure did not take place or proved reversible.  That is probably because no kinship networks extend to all parts of India.

The fragmentation must have protected the constitution and the electoral system.  That in turn allowed constitutional and legal frameworks and electoral politics to correct the failures.

In Karnataka, the corrupt mining barons and the Chief Minister who supported them ended up behind bars.  In Tamil Nadu, some family members of the corrupt Chief Minister ended up behind bars.  In both states, the parties that had engaged in corruption were voted out of power.

So, failure through networks of patronage might be difficult to engineer in India because of the extremely heterogeneous nature of its society (a result of size and diversity).

Nepotism

Why would someone intending to build a patronage network only elevate kith and kin to positions of power?

As in, why did the dictators in Iraq and Syria choose to pack the governing organizations with people from their own community or tribe?

One possible answer emanates from the work of George Price (http://www.bbc.co.uk/news/magazine-24457645), who showed that altruism exhibited towards close relatives can have concrete benefits for a selfish individual.

I quote from the article:

Price’s equation explained how altruism could thrive, even amongst groups of selfish people.

It built on the work of a number of other scientists, arguably beginning with JBS Haldane, a British biologist who developed a theory in the early 1950s. When asked if he would sacrifice his own life to save that of another, he said that he would, but only under certain conditions. “I would lay down my life for two brothers, or eight cousins.”

Here is the Wikipedia page describing the Price equation (http://en.wikipedia.org/wiki/Price_equation).

So, it is possible that the elevation of kith and kin minimizes the possibility that the people so elevated might one day turn against their patron (they might be more likely to exhibit non-selfish behavior towards their patron).

Detection using Text Analytics

One is tempted to ask whether it is possible to detect at an early stage the process of failure through patronage of a democratic system.

The answer is yes.  It appears to be possible to build a protective mechanism that can uncover and highlight the formation and growth of nepotistic patronage networks.

The BBC article on nepotism in Italy examines research on the detection of nepotism in Italy, and I quote:

Prof Perotti, along with others, has published revealing studies of university teachers, showing the extraordinary concentration of surnames in many departments.

“There is a scarcity of last-names that’s inexplicable,” says fellow academic, Stefano Allesina. “The odds of getting such population densities across so many departments is a million to one.”

Take the University of Bari, where five families have for years dominated the dozens of senior positions in Business and Economics there. Or consider the University of Palermo, where more than half the entire academic population has at least one relative working within the institution.

I happened to find one of Allesina’s papers titled “Measuring Nepotism through Shared Last Names: The Case of Italian Academia” on the internet.

Here it is:  http://www.plosone.org/article/info:doi/10.1371/journal.pone.0021160

I quote from the paper:

Both types of analysis (Monte Carlo and logistic regression) showed the same results: the paucity of names and the abundance of name-sharing connections in Italian academia are highly unlikely to be observed at random. Many disciplines, accounting for the majority of Italian academics, are very likely to be affected by nepotism. There is a strong latitudinal effect, with nepotistic practices increasing in the south. Although detecting some nepotism in Italian academia is hardly surprising, the level of diffusion evidenced by this analysis is well beyond what is expected.

Concentrating resources in the “healthy” part of the system is especially important at a time when funding is very limited and new positions are scarce: two conditions that are currently met by the Italian academic system. Moreover, promoting merit against nepotistic practices could help stem the severe brain-drain observed in Italy.

In December 2010, the Italian Parliament approved a new law for the University. Among other things, the new law forbids the hiring of relatives within the same department and introduces a probation period before tenure. The analysis conducted here should be repeated in the future, as the results could provide an assessment of the efficacy of the new law.

This analysis can be applied to different countries and types of organizations. Policy-makers can use similar methods to target resources and cuts in order to promote fair practices.

The analysis that Allesina performed (a diversity analysis of last names) is a fairly easy text analytics task and provides a clue to the solution to the problem.

Such an analysis can unearth nepotism and allow steps to be taken to prevent it.

Extensions of the method can also be used to determine if, as in the case of Iraq and Syria, a certain community or ethnicity or family has taken over or is beginning to take over the governing mechanisms of a country.

And if the problem is identified early enough, it might give the constitutional, legal and electoral institutions of a democracy a fighting chance at protecting themselves and lead to a correction of the failure.