Eradicating Poverty

In Allegory of the Cave, Greek philosopher Plato distinguishes between real (objects in front of a fire) and not-real (shadows cast on the wall).  Prisoners in this cave can see only the shadows, restrained, as it were, from turning their heads.  Many of us, the well knowing and duly enlightened, undoubtedly make a tacit, if not stated, value judgment about which is better:  We want to get at the reality of things and the truth about our circumstances.  So if a prisoner were to exclaim, 'That's a man' on the wall, we'd say 'No, it's not. That's merely the shadow of a man.'

Allegory of the Cave (image credit)

In Theory of Algorithms, I posit as a central tenet:  taking reality as it is, viewing things as they are.  But the fact is, there are many realities and many viewpoints.  Our knowing, enlightened lot is one collective reality and viewpoint.  But the prisoners themselves are another collective in their own right.  Allegory of the Cave is a metaphor for all sorts of circumstances we find themselves in:  Some are free from restraints, some are bound by restraints.  So if we are truly to understand certain people and their circumstances, and perhaps help them in whatever way they may need, then we must, first and foremost, view things from their vantage points.

In brief, then, reality isn't just constructed in the physical world, but also conceived in the human realm.  Human reality constitutes very much a part of what we call reality.  So for that prisoner, that is a man standing or dancing on the wall.

So it is with the poor

Among the seven billion of us in the world, one billion souls live in abject poverty.  Among us, there are researchers and scholars, leaders and citizens, and organizations across countries that are concerned about, and committed to, helping the poor.  I encourage us, at the very outset, to put the poor first in mind, that is, before our knowledge, dollars, and initiatives.

Let them speak, let us listen.

1. What is it they want to do with their circumstances, and how do they understand their circumstances?
2. What are the ways to accomplish what they want to accomplish?  What can they do, and what do they need help with?
3. How can they go forward with these ways, with what they can do and with the help they get?

The Core Algorithm

These three points comprise The Core Algorithm.  It is a meta-methodology that, along with the poor, helps us determine the best strategies, methods and process to help particular collectives of the poor.  The Core Algorithm does not presuppose a methodology, but instead takes an end-in-mind, problem-first approach to determining the right approaches.

Step 1.  Begin with the end in mind

Let the poor speak.  Let the problem of poverty speak.

Letting the poor speak for themselves may be easier said than done, when there are so many of them and they live in so many countries.  Where do we begin?

We may choose to travel far from our home, if we have the means, or simply begin at home, that is, in our neighborhood or town.

When I lived in Dubai, my charitable efforts meant, in one set of initiatives, giving workshops to the Filipino community on jobs and career.  I was a member of the Philippine Business Council, and guidance and support on these subjects were a need that we knew the community had.  Many of these overseas Filipino workers (OFWs) came from impoverished households, and were earnest to make a living and send money back home.  Indeed, we tapped into such a need:  Word got around so quickly that by the third workshop, we had to limit enrollment and create a waiting list.

I was fortunate as well to have the opportunity to travel far from Dubai, that is, to Malaysia, where as part of a Gulf for Good charity challenge, we raised money to help the Borneo Child Aid Society.  Many workers hailed from Indonesia, Philippines and Malaysia itself, and worked the plantations of Borneo.  They were not expected to have children, but of course they did. Unfortunately, for years, the government did not acknowledge these children as beings.  They were effectively non-existent, so their families were not eligible for services such as schooling.  BCAS provided such services. 

While at the Sabah Tea Plantation, for example, I met a family of school teachers, Filipinos like myself.  We talked at some length, just to get acquainted.  At the end of it, I asked them what their students needed most. In my mind, I thought, probably books or maybe computers.  No, they needed pads and pencils.  As simple as that.

Circles of Constituents

Poverty is centuries-old, multidetermined, multifaceted phenomena.  But for illustration's sake, let's keep our graphic simple.  These are circles of constituents, and also circles of responsibility and intervention for eradicating poverty and engendering prosperity.

Circles of Constituents

Obviously poverty is not an abstraction, but in fact it has particular faces, for example, as Janice Novogratz relates in her TED Talk.  So we may begin with the individual.  We may also begin at the social circle:  family, village, community or neighborhood.  At the government circle, we may speak to a constellation of organizations of varying authority, commitment and integrity, which can stretch from town or city, to state and nation.  Beyond the government circle, of course, are other sets of circles, non-government organizations (NGOs), scholars and philanthropists alike.      

Because of the complexity of poverty, these circles actually overlap and collide in dynamic ways, keeping in mind that there are hundreds of circles of constituents.  Two points are crucial, then, from my standpoint:  (a) Our efforts to eradicate poverty must mirror its multifaceted nature.  In other words, our collective efforts cannot focus on just one circle, but on multiple circles.  (b) Nevertheless, we must pay primary attention to the smallest of circles, so we are certain that efforts to help the poor actually help the poor.

We may have a lot of knowledge at our disposal; a lot of desire, commitment and dollars to help; a lot of initiatives and programs poised to run, if they aren't in place already.  But the abiding questions and issues are these:

• How does each circle define poverty, and what is it like to live in poverty?  
• What does prosperity mean for each circle?  If they can picture being out of poverty, what would that look like?     
• What is the end in mind for each circle, that is, what is it in particular they want to do?

These questions are as much about conversation, as they are about research; as much about practical issues, as academic construction; as much about seeking to understand, as sharing what we understand.  Eradicating poverty is the overarching end in mind that a number of us have posed.  But the nuts-and-bolts of it, so to speak, have to do with what poor individuals and communities want to do.  

Of course we do not live in a perfectly benign, humanitarian world, and again hundreds of circles overlap and collide in ways that sometimes conflict and sometimes prey on the poor.  So, in Step 1 of The Core Algorithm, the answers to the questions above must be reconciled sufficiently and successfully enough, before we take next steps.  

Paradigms for Reconciliation

Understanding

I created the Tripartite Model, an integral aspect of my Theory of Algorithms, as a way to house the totality of knowledge we have gained and knowledge we have yet to gain.  Knowledge is an imperative in solving problems.  So, in this respect, the Tripartite Model aspires to be a complete epistemology.  

The Tripartite Model

In the graphic above, Science, Art and Religion are broad labels, whose meanings or implications are far more important than the labels themselves:

• Some people may emphasize, and turn duly to, Science, to know ourselves, each other, and the world around them.  Across all sciences, it's about taking an analytic, logical and systematic approach.  
• Some people may draw on Art, not just for expressing ourselves but also for exploring our situations.  Across all arts, it's about an intuitive, creative and open-ended approach.
• Some people may have more of a spiritual, metaphysical or philosophical bent, so Religion offers them insight that neither Science nor Art can.

Perhaps mostly in Western culture, we would like to believe that each individual is rational, straightforward, and benevolent.  This way, we can take a predominantly analytic perspective to understand him or her.  In actuality, each individual is sometimes illogical, ambivalent, and conflicted.  Still, depending on our preferences, beliefs and values, some of us may choose at stay in one 'camp,' and carve our profession as scientists or artists or theologians.  

That's well and good.  But I argue that to truly understand poverty, eradicate it, and lead the poor to prosperity, we must take the more holistic view and approach that the Tripartite Model offers.

With any particular constituent, in their given circumstances, we need to bring to bear whatever knowledge is at our disposal.  This knowledge may range from scholarly to anecdotal.  So as long as it is pertinent for serving the purpose of that circle of constituents, then it is valuable, and must be accessed, drawn on, and built.  

Relating

In the algorithms I created for top leaders and their organizations, I fashioned a sub-algorithm that I call the Galileo Algorithm.  It draws primarily on one of The Seven Habits of Highly Effective People, by Stephen Covey: namely, Seek first to understand, before being understood.  

The Galileo Algorithm is the first iteration of the more complex Human Algorithm that I'm working on, where I aspire to reformulate and expand on what psychology, for one, has found about people.  I called it after the famous astronomer and philosopher, because he was one pivotal figure in altering our notion of the universe, that is, as heliocentric (revolving around the sun) and not geocentric (revolving around the earth).  

In brief, if we are to solve problems, we must step outside of ourselves - and our valued perspectives, knowledge, and methodology - and quite determinedly step into the problems themselves.  We encounter shortfalls or failure in solving problems, when we get virtually locked into our self-centered (i.e., geocentric) views.    

The Galileo Algorithm, essentially, is about the human being.  It's about our humanity, as a whole.  It's about acting humanely, for after all such efforts are called humanitarian.  In this vein, engaging actively, building trust, and promoting dialogue are key, as are forging meaningful relationships, reaching collective understanding, and undertaking coordinated effort vis-a-vis the poor.  

Questioning

We can be as thoughtful or careful, as smart or systematic, and as strategic and planned as we would like.  Still, we cannot know everything; our knowledge is imperfect and may be inaccurate; and our efforts are prone to mistakes or diversion.  In other words, once again, we are human, and whether it's Science, Art or Religion, it is all inviolably a human endeavor.  

Consequently, we must assume a hovering, questioning mind over what we know, what we do, and what we find.  As difficulties, contradictions, or failures arise, we must pause and reflect, and perhaps alter our course.   More formally, I call this extracting the algorithms, in order to make sure that our efforts progress toward our purpose.

In sum, then, what we ought to have arrived at, to this point, are (a) a clear, working agreement on the end in mind and (b) a reasonable, collective understanding of the problems at hand.

Step 2.  Walk backwards to map pathways

Identify the most direct, most workable steps to solve the problem of poverty.

These steps are determined, and guided, by the end in mind and understanding of the problems.  I argue that mapping pathways backward, beginning with the end in mind, takes a heliocentric (i.e., others-focused, reality-emphasized) viewpoint.  It requires us to step outside of ourselves, and peer in to the future, and visualize as clearly as we can:  being freed from poverty, at the doorstep of prosperity.

These Immediate Impact steps are followed by Intermediate Impact steps. In other words, now that we have identified what will work most directly to resolve poverty for a particular constituent and their end in mind, we must determine what we need to do, on that pathway, which lead directly to, or bring about, those Immediate Impact steps.

Continuing to walk backwards, we map pathways to where we are:  in the present, back to the here-and-now.  We determine what we need to do at the very outset, what I call Catalyst Impact steps, which lead to those Intermediate, then Immediate Impact steps.  The following slides illustrate this backwards mapping.

Immediate Impact steps

Intermediate Impact steps

Catalyst Impact steps

Identifying efforts 

My efforts here are not the first, of course, and mine will not be the last. More accurately, however, mine are meta-efforts and are algorithms in nature. What does this mean?  As I continue to serve the community and help the poor, I extract the algorithms of what I do and how things turn out:  How well are things working out, and what are the mechanisms that make things work?

Moreover, I extract the algorithms of what others do and how things turn out for them.  From Philippe Diaz and Anil Gupta, to Muhammad Yunus and Bono, we see the tip of the proverbial iceberg, but know that scores of efforts comprise the bulk of the iceberg that lies below the waterline, hidden from view.  To the extent that we identify any and all efforts to eradicate poverty, perhaps from repositories or databases of efforts, then we are very much in the process of mapping pathways.

In other words, the circle of poor that we are focusing on, in a given initiative, advise on what steps will actually improve their circumstances.  But we also want to know, as much as we can, what others are doing with different constituents across different situations.  We must assess the effectiveness of others' efforts vis-a-vis the end in mind we are focusing on. The algorithm here is simple:  Adopt what actually works, dismiss what doesn't work.

Once assessed, these efforts may benefit from modification, enhancement or strengthening.  Of course, those engaged in these efforts may or may not want my perspectives, guidance or assistance, in particular.  By and large, the friends and colleagues I've talked with, concerning Theory of Algorithms and The Core Algorithm, have understood the essence and are keen to hear more.  A few, however, have felt threatened apparently, and recoiled with muted violence (just verbal, thankfully) at what I've said.  After all, who am I to tell them how to solve their problems?

Dealing with obstacles

In The End of Poverty? Diaz relates economic and historical factors that underpin poverty, along with those having to do with policy, culture and religion.  These factors have entrenched circles of the poor further into dire circumstances, and therefore pose as veritable obstacles to any new or remobilized efforts to help.

Last summer, my family and I drove from Chicago to Washington DC.  Not ones to use a hardcopy map anymore, we had two navigational systems at our disposal.  I checked MapQuest online, and it offered a specific route for us.  The problem was, it didn't anticipate a long stretch of construction, which, as it turned out, added two or three hours to our travel.

We used the other system - dashboard GPS - and this actually gave us a more direct, therefore shorter, route back home to Chicago.  In fact, it did a fine job of offering alternative routes, as we ran into one or two construction slowdowns.  The problem?  This route was mainly toll-based, so it became more of an expensive trip than we had anticipated.                

Now that we've had these experiences, I've extracted the algorithms of those two navigational systems, and can better plan for our next road trip.

Experts in Diaz' film noted that the economic engines of wealthy, developed countries in the Northern hemisphere run on natural and human resources of the impoverished countries in the Southern hemisphere.  Moreover, monetary policies engineered by the US, viz. neoliberalism, leave certain countries not just duly indebted but also arguably controlled.

I believe in the sanctity of self-determination, -governance, and -sufficiency. That is, teach people how to fish, rather than giving them fish, and they have food for a lifetime.  As Gupta demonstrates, the poor can be quite inventive in crafting and sustaining a small but viable business to support themselves and their families.  For another, Yunus has shown that micro-financing, that is, very small loans to would-be entrepreneurs among the poor, paid dividends to the lender, while giving the keen businessman or woman the means to self-sustain.

But the predatory nature of some wealthy countries, businesses or leaders means that the disadvantaged and the vulnerable need protection. Corruption, for one, is internalized oppression:  That is, leaders binding and bleeding their own people for their own gain, which is, I've argued, how the Spanish colonized the Philippines for centuries, even beyond their 350-year tenure.

The inequities of wealth distribution are well-known, even if facts and figures escape us.  We know that a tiny minority of people own a vast majority of the riches.  I know that the poverty is far more complex, but there is probably a good amount of truth to the saying, the rich get richer and the poor get poorer.  The philanthropy of billionaires like Warren Buffet and Bill Gates can noticeably move the needle toward a more equitable wealth distribution.  But the obstacles that paralyze the people into poverty may have largely to do with predators' greed.

Many more millionaires and billionaires can help, and must help, but how do we persuade them to do so?  No doubt, it's about appealing to their humanitarian side.  But in the realm of algorithms, I ask, What will it take to get them to help more?  It may mean finding ways to give them more of what they may want, such as more money and more power, rather than, or instead of, outright plea for what they see as an unappealing wealth surrender in the service of wealth redistribution.

So, as it is with my two navigational systems and the roadblocks we faced, we must extract the algorithms of whatever obstacles we face in helping the poor, manage them in ways that work, and thereby ensure that our pathways are truly passable.     

Drawing on influencers

From celebrities with star power and business people known for philanthropy, to those scholars with deep knowledge on poverty and prosperity, to online mavens who command large followings on social media, we must find ways to tap their reach, knowledge and influence.

Remember, it's a heliocentric, not geocentric, universe.  In other words, it isn't about me, or any one of us.  Rather, it's the imperative of drawing on others, taking a backseat, and facilitating those efforts that work vis-a-vis the end in mind.

So, for example, as I clarified for my two Saudi friends, who were living in Bahrain and were fearful for their family's safety, it will probably not be me who speaks with the ruler King Hamad about the conflict in their country  It'll be someone whom he knows and trusts, and is in a position of persuading him sensitively but forthrightly.

Step 3.  Walk the pathways

Do what you need to do to serve your purpose and reach your end in mind.  

The problem is complex, and the situation is dynamic.  But the algorithm at this point is simple as pie:  Just walk the pathways.  We spend a good amount of effort into Step 1 and Step 2, and the more effective we are at these steps, the better we can walk the pathways that lead to our purpose: getting out of poverty, getting into prosperity.

In the US, we call taking action on crucial issues as the 'rubber hitting the road.'  For a car to run, and get where you need to go, its tires must be on the pavement itself.  It's when talking stops, and doing begins.  Of course, we have to have a practical, workable travel plan.

The ICD Model

Even though planning and execution make basic sense for any effort, there are all sorts of difficulties that complicate such effort:  partly having to do with our circumstances, partly having to do with human nature.  For one, we delude ourselves into thinking we can actually script the future with an elegant action plan.  For another, we often underestimate how long it will take to get something done.  Furthermore, we neglect the human aspects of things more than we realize, rendering our stated values about 'people first' merely as 'lip service.'  

So I created the ICD Model in an effort to remedy the ails of efforts to date.

Initiative

I unpack the plan (initiative), from the action (delivery), to remind ourselves that we're dealing with two linked but distinct activities.  Now that we've mapped the pathways from where we need to be, backwards to where we are now, concerning poverty, how we actually go about it is the thrust of creating the right initiative and planning actions accordingly.  

For example, once we clarified what the Filipino community in Dubai needed (guidance on jobs and career [Step 1]); and identified how we in the Philippine Business Council could actually serve their need (a series of workshops [Step 2]); then we rolled up those proverbial sleeves and got really busy planning our workshops [Step 3].  This was a laborious but necessary effort in designing the workshops, creating the materials, coordinating co-trainers and speakers, and managing schedules and logistics.

The following is a simple planning template, revolving around fundamental questions that we have to answer vis-a-vis poverty and our purpose:

1. Why (purpose)
2. What (objectives)
3. How (actions)
4. Who (people)
5. When (timeframes)
6. Where (location)

Communications

Our communications strategy requires planning, in and of itself.  In a way, it has to be the very first thing we deliver on (i.e., take action on).  It's about letting the key stakeholders know what we're planning to do.  Let's keep in mind three points:  One, communications ought to have been taking place all along, preceding Step 1 and moving on to Step 3. So those stakeholders, including the poor themselves, have been duly informed.

Two, communication is 'a two-way street,' both outbound and inbound.  How often do people forget this fact, and go about the process as if it were only about what they have to say (outbound)?  Instead, listening actively and asking earnestly (inbound) are very much a part of it.  The reason we have two ears, and just one mouth, is that we must listen twice as much as we talk.  Alas, for many people, it's often the reverse.  More than just informing our stakeholders, then, we must keep them engaged in genuine (two-way) dialogue.

Three, our communications strategy is the means by which we get buy-in from stakeholders.  Neither planning action nor taking action is a single-handed effort.  To the extent that others speak up, offer their ideas, and agree on their own volition, the more likely they will embark on those pathways to serve our purpose.  At the same time, this is the means by which we can, and ought to, surface concerns, queries and hesitations, and work earnestly and diligently to resolve them.  Tacit, unacknowledged resistance may be small to start, but they can be formidable obstacles down the road.      

Delivery

In one respect, communication is the bridge from initiative to delivery. Once everything has been effectively mapped out, duly agreed on, and sincerely committed to, up to this point, then delivery will follow suit in good fashion.

However, just as we tend to underestimate how long many things will take to get done, we seem prone to over-promise what we're going to do.

I led a consulting team in coaching and developing the top 20 leaders of a major company.  The newly appointed CEO was inspiring and engaging, and gave a keynote to launch our program.  His problem, in a nutshell?  He set those BHAGs (big, hairy audacious goals) that got everyone excited, but the company consistently fell short.  The goals were unrealistically big and hairy, plus there were deep rifts in his executive team, and it all led to under-delivery.

Within two or three years, the Board ousted this CEO, and his successor set challenging but more realistic goals and moved the company as a whole to more disciplined execution.  After missed targets, the company had a string of quarters where they delivered on their numbers.  He was no where nearly as visionary or exciting as his predecessor, but clearly he knew how to engage and mobilize his executive team and frontline staff to get done what needed to get done.

While wise CEOs and organizations may employ an alternative algorithm, that is, under-promise and over-deliver, I advance the notion of promise right, deliver right.  The effectiveness of this notion depends, practically speaking, on a clear end-in-mind (purpose) and well-mapped-out pathways (immediate, intermediate, and catalyst impact).

The MAE Model

While the ICD Model is a team, community or organizational effort to get things done, the MAE Model focuses more specifically on each individual.

Motivation

How much do the poor want to help themselves, and how much do we want to help them?  We're all human, so our motivation will naturally wax and wane.  What do we need to do to optimize this cycle, and keep ourselves moving forward in the right direction?    

Ability  

Can the poor do what they need to do, and can we do what we need to do? We need to take honest stock of our knowledge and skills, resources and support, and take realistic measures to bridge gaps in any of these that are crucial to serving our collective purpose.

Energy

Will the poor do what they need to do, and will we do what we need to do?  If our heart is willing (motivated), and our mind knows it and can do it (able), will our hands and feet move forward with sufficient physical energy?

I avoid legislating or dictating what constituents in various circles ought to do.  Again, The Core Algorithm is a meta-framework for them to determine, decide, and plan what to do.  So at the end of the day, it's a matter of choice.  The choices any of us make depend on motivation, ability and energy.

Black Swan Algorithm 

In their action planning, some prefer to include:  (a) contingency measures, in case obstacles arise; (b) clear accountability, so there is follow-through; and (c) indicators of success, so they know whether or not they've achieved their objectives.

I account for these three things in the Black Swan Algorithm.  It's another sub-algorithm in the consulting I do for top leaders.  The term comes from the 2007 book by Nassim Nicholas Taleb:  The Black Swan:  The Impact of the Highly Improbable.  

We seek a line of sight to the future, so we love to draw on the crystal ball of pundits.  But Taleb argues that predicting the future is a haphazard, if not hazardous, effort.  Experts and laypeople are just as likely to be right (or wrong) in their predictions.    

Our history is hallmarked by inventions and events, which are so monumental, as to disrupt the existing state of affairs and, more so, alter it altogether; and which we evidently did not anticipate, and could not have imagined in 100 years.  From Facebook and the iPhone, to the global downturn and Arab Spring, for example, there is no one who can deny how tectonic these have been in our day-to-day lives and work.

Such inventions and events are Black Swans.

I crafted this algorithm to remind us that (a) we cannot possibly know everything and plan for everything, but we can monitor our activities, evaluate our progress, and adjust accordingly; (b) the future becomes present at each and every moment, so we know more and more about it; and (c) unexpected things happen, so we must keep a hovering mindfulness over what we're doing, and indeed expect the unexpected.

Abiding Questions

Poverty as Purposeful?

I wonder why poverty has existed so long, well before the 500 years that Diaz set as a parameter for his film "End of Poverty?"  As our population grew, formed civilization, and developed industry, we segmented ourselves to a small minority with vast portions of the wealth and to a large majority with mere portions of wealth or virtually none at all.  Such segregation and division are so entrenched in humankind.  

In this respect, then, is poverty somehow an integral part of human nature? If so, can we truly eradicate it?  What purpose could it possibly serve humankind?   Science can identify its causes; Art can move hearts and minds; and Religion can extol the virtues of helping.  But what do these disciplines say about its purpose?

I have no definite answers to these questions, except I believe posing them in this article and at some point in a discourse helps us arrive at answers.  My bias, at the very essence of The Core Algorithm, is to solve problems and to say 'Yes' to the question 'Can we eradicate poverty?'  God gave me knowledge, ability and determination, and I believe it is my purpose, among others, to help eradicate poverty.

But only time will tell how much I can actually help.  In the meantime, I will work at getting a grip on the larger why of poverty.

Wealthy as Wealthier?

I weighed this question earlier:  How can we get the wealthy and powerful to do more to help the poor?  Among billionaire philanthropists, Gates and Buffet have led the charge by donating large portions of their war chests to charitable endeavors.  I hope to know more about what these charities are doing and, more importantly, how well their efforts are working out.  I believe that with my mind 'wrapped' around these efforts, I can find ways to enhance and extend their benefits and perhaps even eradicate poverty altogether, for example, with the approximately $35 billion that Buffet contributed to the Gates Foundation coffers.  

That said, how can we get more of the wealthy and powerful to help as well? We know that some of them, even regions of them, are perpetrators of poverty (rf. neocolonialism and neoliberalism).  If experts speaking in Diaz' film are indeed correct, then we're talking about some government and organizations as culprits.  Some of us prefer, and have the means for, activism, even militancy.  If their efforts in fact work, and serve the greater good, then let's support them.  Calling the wealthy and powerful to the carpet, so to speak, is part-and-parcel of enabling a long elusive redistribution of wealth.

But instead of taking away some of what they have, can we not engage them in finding alternative ways to build their wealth and retain their power, that is, without plundering the poor?  In other words, can we draw on their business prowess and their voluble authority to problem-solve poverty, while serving what may be their singular need?

Across the world, they belong to their own circle of constituency, so I encourage us to let them speak, listen actively to them, and understand their reality.  There is no reasonable way to legislate them to help more or to coerce more of them to help.  But this platform of engagement positions us better for the right solutions vis-a-vis poverty.    

Help as Exponential?

In recent years, I spoke at two memorable occasions about my philanthropic aims.  One was my 50th birthday celebration (July 2009).  I was living in Dubai, and a couple friends and I did last minute planning, and managed to get 30 other friends to come join us.  Another event was at work a year later (July 2010).  Our company created a challenge program to help disadvantaged young people in Dubai get on-the-job training and experience, and we held a graduation ceremony.

Here is the gist of what I said:  We can reach every single person in the world, numbering seven billion of us now, and help them, if they need it.  How?  Well, no one person can do it.  But if each person helped, and at the same time got others to help, then it's possible.  This is obviously not going to happen overnight, I emphasized, and it will probably take a couple of hundred years.  So inculcating the value of helping in our children, and guiding them on ways to do so effectively and purposefully, is nothing short of crucial.

I am still working on this, but here are four areas that I believe give me clues to formulate an exponential algorithm for helping vast swaths of our population:

We must think geometric progression (i.e., exponential, curvilinear), rather than arithmetic progression (additional, linear).  Some of us focus on helping directly with dollars and time, and may therefore neglect the multiplier effect of getting more of others to help, too.  In sports, the MVP is not just the high-performing player, but also the player who gets others on the team to performing highly.

The Fibonacci sequence in mathematics begins with 0 and 1, and the sequence is to add the previous two numbers, thus:  0, 1, 1, 2, 3, 5, 8, 13, 21, and so forth.  You see how quickly the numbers grow.  Graphing these numbers end up looking like a nautilus shell and other things around us.  So I wonder if there is something in nature, maybe in the people themselves, that leads to wider, far-reaching help.

In the film 'Amadeus,' Mozart explains that if you have a room full of people simply talking, and doing so loudly, you have cacophony.  But put the talking to music, and you can harmonize large groups of people into an opera.  The Virtual Choir is one amazing online effort to gather people across the world and sing together.

Finally, the Rubik's Cube is a curiosity.  I've never solved it, and haven't yet put forth concerted effort to do so.  But over time, I believe I can extract its algorithms to figure out enough of its solution, not for its own sake, but for the sake of the poor.  Its common shape is 3 x 3 x 3, but I know there are larger cubes, such as 7 x 7 x 7, and on to computer-generated models of even larger cubes.

These four areas are not important, in and of themselves.  Rather, I am 'mining' them - conceptually, mathematically, and practically - to figure out ways to scale our efforts and thereby help seven billion people.  

Closing Remarks

There is a lot to digest here, a lot to look further into, a lot to do to eradicate poverty.  The Core Algorithm for eradicating poverty and engendering prosperity will take me more time, thought and effort to formulate.

But keep in mind that an algorithm, in the way that I define it, isn't necessarily a solution.  Rather, it's a meta-solution.  It's a solution (framework and process) for determining the best possible solutions (a) for any given circle of constituents, (b) for their stated purpose, and (c) in their particular situation.

In summary, then:

Begin with the end in mind.  That solution begins with understanding what poverty is, as best as we can, largely by letting the problem speak.

Walk backwards to map pathways.  The solution is formulated, first, by identifying the most immediate, direct impact to help the poor, then discerning intermediate and catalyst impact steps.

Walk the pathways.  The solution is game-planned, essentially, and is done so in smart fashion and in ways that ensure effective delivery.