Sunday, March 15, 2020

The pandemic response in the USA and what might be coming

Along with public health interventions,  policy makers and the general public might consider the reshaping of American society and re-balancing of global societies that this single pandemic is causing.  I wanted to reflect on that a bit,  and encourage your to make comments below!

We know from past experience that interest in pandemics has a clear panic-then-forget cycle,  typically moving on to new topics before many lessons-learned can even be defined, let alone be implemented.   So, a question: Aside from inside the government, where are lessons-learned actually being incorporated into social infrastructure during this pandemic that will improve our odds of surviving the next global crisis?

One thing that bears watching is how we manage "risk communication" on both the sending and receiving ends, since they are intimately linked. This regards improving the sensing process by which important things are noted and sent "upwards", the sense-making process at "the top", the process of sharing "the big picture" with the wider public of what is going on, the formulation and issuing of guidance and/or orders to various levels about what to be doing today and next week ( on a moving basis ), and the fabric of compliance with those orders.

In short, these are really the component of the most fundamental cybernetic control loop that defines "living": sense your environment, decide what it means, decide what to do, try to do it, watch how well that works and what new stuff breaks loose, rinse and repeat.


The 2020 elections in the USA may reflect people’s conclusions, by then, regarding how well our country’s “cybernetic loop” has served us in this pandemic, who offers what ideas on how it can be improved, and how high a priority that is among voters among other issues and values.


Some countries, most notably authoritative China, are very strong on connecting what is ordered to happen and what actually happens. With strong surveillance state technology China also keeps tabs on what is actually happening on a daily basis.

The USA probably is at the far opposite end of the spectrum from China, since between distrust of the government, the perceived meaning of “freedom and liberty” and "rugged individualism", many people will do whatever they feel like regardless what they are told to do by the government, public health, or anyone else.    

As a consequence,  if we believe the published numbers,  the fact that China seems to have managed to get the pandemic under control with under 100,000 cases provides very little reassurance that such a strategy would work in the USA.

One huge reason for concern is that, with an epidemic,  “almost contained” is a world apart from “contained.”   Epidemics can and do start with a single case - one solitary human being.   That’s enough.    So for containment to work,  not one single human being can escape quarantine.

The Washington Post just ran some very nice animated graphic illustrations of how the infection might "leak out" of a small hole and continue to spread.  See Why outbreaks like corona virus spread exponentially, and how to “flatten the curve”


So, in my mind, the odds of containment working inside the USA seem close to zero.  Clearly other people's opinions vary, and how likely you are to believe this analysis may be related to the costs you will incur if your judgment is wrong in that direction.   In fact, even with draconian measures,  one suspects the government will be continually playing “whack-a-mole”,   stopping the outbreak in one place only to have it reappear in another place.  Already counties that take strong measures are frustrated by neighboring counties that take weaker measures, but that's how things operate inside the US.



Photo: TPapi under Creative Commons license (https://creativecommons.org/licenses/by-nc-sa/2.0/)

The fact that Covid-19 has a long period where it is infectious but not contagious really does not help design strategies that stop it without overkill blocking everyone regardless of symptoms.

Following that logic, it seems to me, at least today, that the most likely coming scenario is that the epidemic will grow,  authorities will squeeze tighter,  the epidemic will slow, then break out anew in different places,  those will get squeezed,  the epidemic will slow, then break out anew in yet new different places, etc.

So I suspect that, at some point,  just as “containment” has been abandoned as hopeless,  even “mitigation” will be recognized to be enormously expensive in both dollars and social costs,  and failing to work well enough to justify the costs,  and so some new strategy will be sought.  One can imagine the case where mitigation will be applied for at least a month,  when it might be declared successful, or when social pressure declares it too expensive and disruptive,  causing it to be removed, at which point the infection may start again, followed by a renewed imposition of measures, etc., a dance lasting many months.

What can we expect? What can we do?

Well,  trying our best to make mitigation work despite doubts is a good start. We should at least try.  I believe I will request an absentee ballot for the November elections, just in case.

One thing that comes to mind is that there will be a growing body of people who will be immune to the virus or no longer carriers if they are recovered victims.   These will heavily be young people, apparently, as the virus strikes most heavily at the older population and mostly spares children.

So, there is no reason if they are recovered and no longer contagious for such people to be subject to quarantine measures.   They can come out of quarantine and run vital services,  shop for others or themselves,   and for that matter go to concerts or sports events of their own kind.

Meanwhile, the older population seeking safety will continue to self-quarantine even if they are not ordered to quarantine,  erring on the side of caution because their risks are higher. Besides, if you get hospitalized and end up in a nursing home, no one may be allowed to visit you.

Visible society will become substantially younger.  The people working behind the counters and the customers will be mostly younger, at least for a while.  Generation Z will dominate the visible world.  One suspects they will take delight in that and possibly be reluctant to give it back.

Greta Thunberg, outside the Swedish parliament. 

After a year or two most people will have ended up getting the virus, the population at large that has survived will be mostly immune to it,  and it will join the other annual flu viruses as something we are warned about but most people ignore.  Perhaps there will be a vaccine, but efforts to develop one for SARS and MERS have been unsuccessful so it seems illogical to count on it.

Meanwhile — working from home, telecommuting, classrooms from home will all be permanently ramped up and, to a large extent, having been funded, stay ramped up. Commuting will be substantially reduced,  carbon emissions reduced,  central urban populations reduced, etc.  These changes will delight many young people and advocates of action on climate change.

In any case, a renewed interest might be paid, then, to the question of how to make remotely attended meetings at least as good as, or not better than, face-to-face meetings.

See my blog post from February 10 on that: We need serious R&D on how to improve meetings!

Meanwhile,  let’s not forget that this pandemic is taking place on a world stage,  and has substantial social, economic, and military consequences, which are not evenly distributed, and in fact may substantially change the balance of power.

In the weeks and possibly months ahead, if other countries bring the pandemic under control, and the USA does not,  we may well expect to find the travel bans reversed, either totally banning incoming passengers from the US,  or at least demanding, as New Zealand has just done, that all inbound passengers be quarantined for 14 days.    This will be a rather huge change in the global dynamic as well as a blow to how the US is regarded as a global role-model.

[ I no sooner posted this than someone brought this to my attention-- it's begun:

Norwegian university tells students in US to return home due to ‘poorly developed health services’: report

]


Therefore, in business, I hope to see a strong emphasis on Research and Development on making remote conferencing software at least as good as “actually being there” to lessen the disadvantage the US would suffer from being late to the game on dealing with its own population’s health and well being.    The large number of companies in the Virtual Meeting space is encouraging, as reviewed in the Gartner Group's Magic Quadrant diagram for 2019 for "meeting solutions".

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Friday, February 28, 2020

Thinking beyond the Covid-19 pandemic

There is bad news and good news.  The bad news is that a gigantic F-5 pandemic storm is coming.   The good news is that after a while the storm will be leave,    it will be sunny and calm again, and, if we played our cards right, we will be stronger than we are now.

Will the storm cause damage?  Yes.    Possibly a lot.   It happens.

[ NOTE - According to the World Health Organization's public meeting just now,  as of 4 PM Greenwich Mean Time, 28-Feb-2020,  it is not yet 100% certain that this pandemic will materialize.

But, the W.H.O. raised their level of concern today from "high" to "very high".
W.H.O. still emphasizes that Covid-19 has been successfully shut down by very aggressive containment efforts in China, Singapore, one country I couldn't hear,  and Vietnam and the 'window of opportunity" is still open for countries experiencing their first case or cases to get it stopped.  It is not yet "a pandemic" in the sense that it is not yet time to abandon containment efforts and move on entirely to mitigation. 23 of the 46 countries with cases have only one case.  As far as W.H.O. is concerned,  we are near the watershed point where this will run out of control worldwide,  but not yet to that point. ]

Can the survivors repair the damage and get on with our lives?  Yes, provided we systematically pay attention to using the pressures of the storm to drive us closer together, not further apart.



Here's an analogy. I know of two families, each of which had a young child die.  In one family the result was anger, depression, conflict, and divorce -- the most common outcome of loss of a child.  In the other family the result was resolve, bonding, and a renewed intense joy in life and each other.




Life is a choice.   Happiness is a choice.  We can pull together or we can pull apart -- it's ours to choose,  but we will surely be pushed to do one or the other by this coming storm.

In reality there will be more periods of sunny weather, and more storms -- possibly some stronger than this one.  Again, if we set our minds and hearts to it, we can end up being made stronger and stronger by that sequence of challenges -- or,  we can end up being devastated.



We can view each other as a source of strength and a resource, or we can view each other as competitors, enemies,   threats.     To a large extent, whatever we pick will become a self-fulfilling prophecy.    People live up to, or down to, expectations.   It works both ways.





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Monday, February 10, 2020

We need serious R&D on how to improve meetings!



The Bill and Melinda Gates Foundation's 2020 Annual Letter titled Why We Swing for the Fences is posted, and I wanted to respond at greater length than their comments section would allow, so here it is.  A subtitle might be: We need serious R&D on how to improve meetings!

Executive Summary

I present a case that, while funding initiatives into high-profile problems is a good idea,  in addition serious funding should be considered for the cross-cutting unsolved problem of making great decisions come out of small group meetings.  In my own opinion, easily half, if not more than 90% of the funds going into business and public initiatives is wasted by the present dismal state of group decision making,  especially where the rubber meets the road, at the front of local decision groups.  The $100 million sent this week to combat the corona-virus pandemic, for example, is really trying to fix a problem caused by a poor decision of a Chinese censor group to suppress the observations of a doctor who spotted the problem early when it could have been fixed for probably under $1,000.  Business meetings I have been in seemed to be so preoccupied with 51% of the room battling 49% of the room that only 2% of the mental bandwidth was left to use for actual thinking, with the expected result of no decision made.  The universe of problems mankind faces, and their solutions,  do not fit well through the tiny keyhole of this sort of "meetings".  There must be a better way. Technology of super-computing, cockpit-management, and very high performance teams which have been observed in practice suggests there is.  Few problems would have more leverage, per dollar spent, of improving mankind's chances of survival than this one.




Introduction

First let me say how much I appreciate and applaud their past efforts in the often contested areas of global public health and public education.   I spent 50 years in academia myself and recently went back to school to get a Masters in Public Health from Johns Hopkins,  because, to put it bluntly, if we're all dead then solutions to the other problems don't really matter, do they?

Sadly, many people mistakenly believe that "Public Health" is a term that simply means free health care for poor people, or something like that, instead of grasping that it is really about the Health of the Public,  the global concern for all of us on the planet and the things that make us unhealthy ( or dead ) which includes diseases and disorders, physical and mental, but it also includes responses to the "agents of death" such as tobacco,  weaponry of all scales from handguns to tactical nuclear weapons,  and, yes, the change in the climate, again hotly disputed as to cause, but hardly disputed as to the devastating impact it is already having on world populations,  starting with poor people.

Weather after all has profound effects far from the source.  It was a drought in India that raised the price of tea which caused England to raise the tax on colonists which led to the American Revolution. Everything is connected.

And now we have a new global pandemic at the gates,   the novel corona virus ( aka Covid-19 ),  ringing echoes of previous pandemics,  from SARS to MERS to HIV to the Spanish Flu of 1918.  I see the Gates Foundation has already chipped in $100 million just this last week.   See Bill & Melinda Gates Foundation Dedicates Additional Funding to the Novel Coronavirus Response

And if you look at the map of the corona-virus cases and deaths, updated daily on the World Health Organization's website,   you see not a single case in Africa so far.    There is deep speculation that this is not due to there being no spread of the virus into Africa and its densely crowded poverty-stricken large cities,   but that the public health capacity there to test for and diagnose the virus has been lacking.    

 Their neglected and impoverished health care system and poverty are very likely to soon become "our" problem in the USA -- if not on this pandemic, then perhaps on the next one.   This problem is "silent" and ignorable here in the USA until suddenly it won't be, but that time will be far past the time we should have acted.   Again, thank you Gates Foundation for stepping up to the plate.

[ post-comment: I learned today (24-Feb-2020) from the WHO briefing that much of Africa actually has quite good syndromic surveillance on diseases like Polio, Hemorrhagic fever,  Cholera, Lhasa Fever, and Yellow Fever, but their system for tracking pulmonary diseases still needs work ]

Also Melinda said in the letter, "But we’ve also developed a major sense of urgency around two other issues. For Bill, it’s addressing climate change. For me, it’s gender equality."

The issues around adapting to climate change,  and/or combating it, depending on which of two polarized camps you are in,  has spread not only to the rest of the world, but has also become a major psychological concern of Generation Z - our young people today.   The Washington Post magazine had a piece this week " The Environmental Burden of Generation Z / Kids are terrified, anxious and depressed about climate change. Whose fault is that? ( apologies  -that site might require a subscription to see. )

I am a member of the Baby Boomer generation myself, who grew up in constant fear of global thermonuclear war breaking out,  which it almost did in 1962 in the "Cuban missile crisis" when only the decision of one Russian submarine captain to go against policy and not fire his missiles stood between us and Armageddon.     The very real fears these children have of climate change,  that they will never live long enough to have their own children, will certainly mark them forever, even if we resolved the problem itself tomorrow.

So kudos to Bill for addressing climate change in the coming decades.  

I am an absolute believer in the need for gender equality and the religion I belong to, the Baha'i Faith, has been working tirelessly on this front for over a century.  ( See The Advancement of Women )    The newsletter didn't mention the studies which have shown, by the way,  that the profitability of companies, the bottom line, seems to be proportional to the number of women on their Board.      See for example "Huge study finds that companies with more women leaders are more profitable"  and a quote from that piece: 
 The evidence on women in the C-suite is robust: no matter how we torture the data we get the same result: women in the C-suite are associated with higher profitability,” Marcus Noland, director of studies at the Peterson Institute, told Quartz in an email.

Re-framing "the problem"

So while every one of these issues,  from global health to climate change to education to women's roles is important,
I want to suggest that the global situation we are in today is akin to a sinking boat with 200 holes in the bottom, and we are arguing over the priorities of which four holes to address first.  
There is always a natural inclination, when overwhelmed, to "prioritize".  What's wrong with that?

The problem with that approach is that it only works out for situations where we only have a handful off key issues,  and if those are addressed the others can be mopped up later.     With the complexity of the globe today, and the accelerating progress of change  we a simply making new problems for ourselves faster than we can solve them.

The problem, in other words, is that prioritizing doesn't work in that situation. 

The boat will still sink, from the other 196 holes, while we are prioritizing those four holes.   I'm not saying these are not big holes -- I'm just saying that there are now so many holes that even if we fix those four,  we're nowhere near done.  We will still sink.   We need in addition to those initiatives, something that addresses all of the holes at once.

What might that be?

I raised that question and a tentative answer in this weblog in 2006 and 2007 in a post titled "Houston, we have another problem" and illustrated it with a simple graph with profound implications:

The graph is simply a visualization of two curves -one showing the wisdom or intelligence required to solve today's problems on a generic "wisdom scale" , which is heading exponentially upwards at an ever faster rate,  and the other curve showing the peak IQ or wisdom of the smartest person on earth, which I was generous and put at an IQ of 250.

The problem illustrated is that sometime before the year 2000 these curves have crossed and will never meet again.   The problems are already beyond what the smartest human can get her head around, and growing rapidly even worse, as everything is tangled up into everything else, and every time we humans try to solve one problem we seem to create two more, and in fact the solution to our first problem becomes the new problem.    This sort of thing happens regularly with "complex adaptive systems", and the wonderful thinker Lewis Thomas put it so well in Lives of a Cell

When you are confronted by any complex social system, such as an urban center or a hamster, with things about it that you're dissatisfied with and anxious to fix, you cannot just step in and set about fixing with much hope of helping. This realization is one of the sore discouragements of our century. You cannot meddle with one part of a complex system from the outside without the almost certain risk of setting off disastrous events that you hadn't counted on in other, remote parts. If you want to fix something you are first obligated to understand... the whole system.. Intervening is a way of causing trouble.
Are we doomed then?  Is there no hope?

Actually, there is not only hope, there is a clear path to a solution on the table in front of us.
A single root-cause problem that would address all the other problems at once is figuring out how to dramatically improve working together in small groups.
 It turns out that our computer scientists ran into a similar problem last century.  They kept trying to make larger and larger computers  ( remember "mainframes" ? )  to solve problems, but were running into all sorts of technical issues, when someone finally realized that they did not need a single cpu ("central processing unit") large enough to do everything with almost infinite speed -- what they needed instead was a community of small, cheap, easy-to-build computers which worked together to solve problems.

That solution worked.  Today's so called "supercomputers" are actually villages of tens of thousands of small computers that have learned to work together on common problems.

It's  good solution. It's a good pattern. It works.

Humanity's problem has been that trying to put together many people to make a sort of larger entity, a meta-smart-person,  has to date, until recently, been sadly lacking.

We've tried "committees" but those have a rather dismal track-record, and making one larger than, say, a dozen people,  seems to only worsen the problem.

In other words, we haven't solve the problem that I can tease out as follows:   
How do we consciously design a decision making architecture that has the property that if you need it to be wiser or smarter, you can just add more people.
We can do that sort of thing now with "The Cloud" --  we can synthesize however much computing power you need on a problem,  and just keep adding more physical computers under the covers.  It works.  Again, we have a physically real model, a design pattern, that actually works in practice to draw from.

On committees and meetings, endless meetings

Part of the problem of committees,  and of almost every organization imaginable today, is the primitive design of what are called "meetings"  -- an interaction supposedly designed to produce light but that typically produces only lost time, boredom, or outrage.    More heat than light.

This "meeting" idea was designed several thousand years ago, and to be honest, aside from the addition of better lighting and power-point slides,  hasn't really improved much since then.  Real time visualization and interaction tools like Tableau help some, as do "mind-mapping" tools for debriefing crowds to try to tease out underlying mental models from fragments of knowledge.

But our experience with meetings and committees and our expectations are best captured by the cartoonist Scott Adams in his series Dilbert -- namely, rampant dysfunction.

That needs to change. That's where we need to focus some serious energy.  Of all the places in the world with a huge leverage, a huge potential payoff,  making "meetings" even 10% more effective would have an absolutely enormous downstream effect.     Making them 250% more effective might solve our problems overall.   Meetings are on the critical path to essentially everything we do.

We need better decisions,  and we need innovation, desperately.  Both of these things can potentially arise from small groups working together.

And times have changed since when we grew up.   The "cheese has moved."  Our expectations are way out of date.

A vast amount has been learned in the past 20 years about how decisions get made in mission-critical environments,  such as airplane cockpits or surgical operating rooms, and dramatic improvements in performance have resulted, with dramatic reductions in what were unimaginably ( if not real ) stupid errors, like cutting off the wrong limb.

As a side note, a result that showed up in my Artificial Intelligence courses, was that many if not most business failures were due to bad decisions - and more particularly they were caused not by a failure to be a genius and solve astounding problems, but by a failure at the bottom end, a failure so basic, so stupid, that you just shake your head at, or maybe say "I could have told them that!!!" or maybe even "I did tell them that, in fact, but they didn't listen."

Recent financial collapses come to mind.  Climate change, pandemics,  water supplies,  social unrest and riots and change of governments face us daily -- as do the products of insanely bad decisions somewhere upstream in the ether.  Our children blame us for the problems by the way.  This is no longer simply a standing joke or something we see in a Scott Adams Dilbert cartoon and laugh at and then simply forget.  That time is past.

Some of these issues are things that Artificial Intelligence might solve because so called "Rules-Based Expert Systems"  are not necessarily great at the top end, though some are  but they work quite well at the dumb end of the spectrum.

[ aside: One could imagine, say, replacing a fixed written policy document, or emergency-response handbook with a set of rules which in good times produces exactly the same handbook of situations and responses, but in times of crisis or war, when the core assumptions turn out to be false, as they always do when the first shot is fired,   could have the assumption set tweaked, the crank turned, and a new set of guidelines for response generated.    That could work in many circumstances and has the advantage that it can explain how it came to a conclusion, so a human can look at it and accept or over-ride it, unlike the output of, say, a neural net.  The nice thing is the computer does not get tired after 72 hours of solid crisis, unlike humans.   And pandemics last well over 72 hours. ]

Still, those are just specific instances of decision-making that can be improved somewhat.

I'm talking about making a factor of ten improvement in the actual productivity of "meetings." 

What scale change are we looking at?  What's a possible "future state"?

I'm reminded of the time I lived in Ann Arbor, near Detroit, and General Motors was trying to figure out how to get the transition time between models on the assembly line down from 6 weeks to maybe 5.7 weeks.     Someone was sent to see how Toyota did it, and discovered that Toyota did their assembly line model changeover in something like 4 days.

That's what we need for "meetings" -- not at 5% improvement around the edges, but a thousand percent improvement,  using the new understandings we have about how people think, and new computer-assisted technology,  and God knows what else we have to bring to the problem.

We need to start by re-conceptualizing what a "meeting" is supposed to accomplish, on the one hand, and then looking at what tools are available today that were not even a decade ago, and do some brainstorming, innovating, and experiments.      I recently saw a demonstration of Adobe Connect and I'm impressed with even that much improvement in ability to connect in real-time, share voice and data and applications, get real-time feedback about who has fallen asleep and stopped participating allowing for reactive facilitation, etc.   Much more functionality could fit in that framework with their plug-in architecture.  Dig here, people!!   And no I have no connection to Adobe.  I just think they did a really nice job with this product and it's a potential framework for two huge new "use-cases" to add a new functionality "app" plug-in to monitor how well a consensus is being formed, who is backing off from it and who is moving towards it, who just got mortally offended,  etc.
  • professional global meetings on pandemic outbreak response  , and
  • local community multi-stakeholder public meetings about local pandemic response.
[ Note - after the above was written I did check the Gartner Group's "Magic Quadrant" analysis of the best on-line-meeting support tools.  The 2019 ratings are here:
https://www.uctoday.com/collaboration/exploring-gartners-magic-quadrant-for-meeting-solutions-2019/
The best product ratings there are for Cisco and Zoom.

I am not shilling for a particular product. Any product that is actually swung into wide use would make me very happy!
]



Meanwhile -- what's the "present state"?

In general,  we have not only contentious small meetings, but meetings where multiple stake-holders, or the public are involved,   where action decisions are called for on something,  and people can't even agree on terms and definitions, or mental frameworks or value systems to use, or on the credibility of the data, or the legitimacy of the rules they might use to process that data into conclusions and an action decision and plan.

This seems in the last decade in fact to be getting decidedly worse.  Outrage is the norm and civility, not one's weapons, are checked at the door.     Not too suprrisingly even less gets resolved, and what does get resolved does so in such a way, such as a 50.1% majority overruling a 49.9% minority, that permanent damage is done to human relations and odds of everyone agreeing on anything ever again have gone downhill as an unintended but persistent side-effect of the "meeting".

Properly conceived,  what we need to optimize, or at least improve significantly, is an entire string of meetings, not just one meeting-event.

It's an extreme position, but the Baha'is consider the impact of a meeting on group unity to be more important than the ostensible product of the meeting, such as a decision on something,  to the point that a wrong decision that improves unity is urged instead of a contentious meeting which produces a right decision;   the logic is that wrong decisions can be quickly detected and fixed, whereas hard feelings become permanent feuds and prevent any more decisions of any kind to ever be made -- far more damaging than one wrong decision.      In support of that position,  many CEO's operate from information they know perfectly well is imperfect, and take probing steps while braced to quickly undo that if it turns out to be wrong, which allows them to continue to operate in territory with weak data where academic analysis paralysis would result and where "no action" or "no decision" is, in fact, an action and a decision in its own right.

Meeting over the web, or via social media,  does not appear to have solved this problem, but in many cases seems to have only worsened it.

On Tackling Big Problems

One attack approach to large problems is to try to "divide and conquer" or at least break one large problem to be solved into multiple smaller ones, and then reassemble the results into an effective larger result, solving the big problem.

One attempt to break problems apart is the classic hierarchical tree of management, with one all powerful decision maker at the top, and a branching network of smaller and smaller units reporting upwards and taking orders downward.

That model has largely broken down today, because it assumes that there is one human being that can get their head around a problem, the expert,  and that sensor data flowing upwards is properly summarized and distilled at each level, and that orders down wards are properly interpreted and executed at each level going down.    None of these assumptions proves true in practice.  Problems are so complex and fractal-shaped that the expertise has to be be out in the field, at the end of the branches, and even then may not be up to actually understanding the local circumstances in which operations are taking place.

Regardless, it is clear that local circumstances are really important, and widely different, and mostly or totally invisible at the top, or made invisible by successive operations called "summarizing" that removes all the salient details and leaves only a residue that fits on one power-point slide,  repeated at each level of management.   Thus, very large organizations are quite well known to have top management that appears to be living in a different world than the people at the bottom or on the front.

As a result, even for a very large company or military, say, decentralizing a great deal of the decision making to the front, to where the actual circumstances are clear and known to the decision makers, is becoming more common.    Decreeing a one-size-fits-all policy based on the world seen from the top doesn't seem to work well for that situation.

So, again, we are down to how to make those decisions well, matters.  How do small groups of people get together,  using "meetings" or something else,  to combine views, frameworks, perspectives, values,  sensor data,  hunches, smarts,  spreadsheets, visualization tools, etc. to emerge from the room with a "good action decision" in hand?

Interestingly the Baha'i Faith,  with a strong interest in Social and Economic Development, has urged for over 100 years as a major central pillar the idea of "consultation" -- the role of very local decision makers getting their heads together and addressing local problems in such a way that not only are the problems solved, but everyone comes out of the room feeling closer to and more friends with everyone else as a side effect.    Despite the "common wisdom" that this is not possible, it is in fact quite possible. it's possible in high-tech countries, and it's possible in dirt-floor villages.

In some ways all that is needed, aside from some guidance and training,  is figuring out how to counter-balance and overcome the deeply paralyzing belief that this task is hopeless. 
 That's the sort of task that a funded study could evaluate,  determine what is valid and portable and reproducible,  and craft basically a marketing effort around, seeking an intervention to change a cultural belief. A lot is known about that now.  Best practices that work in reality can be collected and rebroadcast.  Training can be created.

Virtual reality may help - as well as emotional channels 

Personally, I'm of the belief that a lot can be done by holding meetings in virtual reality -- just the flat-screen desktop version, not anything that requires expensive googles and high-end workstations. Many of our meetings today involve people distributed around the planet,  or even around the city or the campus, so being on-line is not a barrier. Cheap commodity laptops are adequate for this purpose.

Many meetings already use technology such as Skype or Discord or GoToMeeting or many other products to actually have video conferencing, globally, for essentially zero incremental cost.  Video conferences are somewhat improved over audio-only conferences if the bandwidth is there, because much of the critical interaction between human beings in any meeting is not captured in the text-only transcript -- the volume, tone, pauses, timing, intonation, all form part of one channel of communication that it turns out is simply crucial to humans reaching an agreement with each other.

Similarly video conferencing in large, with one screen showing the whole room, is pretty unsatisfactory for communication of critical honest signals of body language ( described by Alex Pentland) , facial expression, and micro-expressions and micro-interactions that occur when people are face-to-face and can, literally, see each other's faces and detect microscopic changes in everything from posture to the size of one's iris in response to a statement or question or even a "pregnant pause".

Timing matters.  A question answered by "Yes"is not the same answer as the same question followed by a 30 second pause, and then a hesitant "Yes", even though they show up the same on a meeting transcript.    I recall a description of a psychiatrist meeting with a patient where a researcher was given consent to record and transcribe the meeting.  The researcher showed the transcript to the doctor who looked at it in shock and replied something like "You missed everything!  All you did was write down the words! "

The importance of picking up on and consciously emitting emotional content has shown up in the evolution of  "emojis"  or emoticons,   designed to send information to the part of the recipient's brain and body that text-only does not reach, thereby improving the conversation even of "text chat".

Humans are remarkably good,  hardwired as it were,  at picking up any sort of pathway or signal which reveals the honest emotions and what is going on inside the head of the other person in a conversation.   We're built for it.   It can be enhanced -- for example, wearing a large hat would amplify tiny moves of one's head.  

These signals can be consciously sent by people willing to at least try to reach a decision together. I was in a training session,  a so-called "T-group",  during the Vietnam protest days,  that lasted 96 hours and had about 20 people on the floor of a large room discussing issues.   We had an expensive trainer from the Esalen Institute in California as I recall,   who was our emotional disk-jockey and managed the intense emotions unleashed in the room to prevent them from zeroing in on and psychologically damaging any participant.     He also had us all agree to do a few simple things to make it obvious to everyone where we were on the topic and what the person speaking was saying. As they talked, if we were interested we moved closer to the speaker in the center of the room; if we were not interested, we backed away.  If we were totally disinterested, we lay down. .  If we agreed with what was being said, we faced forwards,  as we were ambiguous we faced sideways, if we disagreed we turned our back on the speaker.

The effect was dramatic, and amazingly different from business meetings where people are playing their cards close to their chest,  poker-faced,  if they are paying attention at all.

I call attention to the fact that rather than suppress emotions,  emotions were encouraged and brought to the front.  ( but under a safety-measure of a central facilitator ).
Emotions were seen as a feature not a bug.
Virtual words oriented heavily to social interaction, such as Linden Labs Second Life,  are popular and have quite advanced levels of high-resolution graphics for avatars to represent people, including all types of body language and facial expressions now.       The advantage of meeting in a virtual world would include the fact that the room design can be as nice as possible, from a mountain top to a Buddhist temple,  making use of ambient background sound engineering and lighting to set a mood, or feng shui if you prefer, that is conducive to making friends and making serious and good decisions.   We had one meeting room in a place I used to work that always seemed to generate hostility and bad decisions - and we did our best to not have to be scheduled there.  It matters.

The fact that the room also served double duty as a storage place for dead furniture and boxes of xerox paper did not improve the mood.  No living thing in the room, no plants, did not help.  Sadly, I've seen public health facilities where the environment reflected the minimum funding level, and it just about held in hallway with a desk made up of an unused door stacked atop boxes of some kind of forms or records. These things have a very real effect on the tone of the meeting which has a very real effect on the outcome, and the human side-effects of the meeting.

Making a spectacular meeting space in Virtual Reality costs a few dollars, if that.  It's doable.

In addition,   I took Professor Gary Olson's course "Computer Supported Cooperative Work" when he was at the University of Michigan back in 2006 or so.    One of the great research papers we read in that class was titled  "Global Tele-Immersion: Better than Being There" ( I think I pulled the right cite) and had the novel hypothesis that

computer-mediated conversation should not aim at being "as good as" face-to-face meeting -- it should aim to be much better.  
I may trigger a firestorm with this next comment, and it's risky, but it needs saying. I believe that women may in fact be hard-wired to be better at establishing non-verbal rapport with another human being, because they have evolved to do that with infants and children.
Because women are more adept at this emotional channel, and, anecdotally,  often discussing issues among each other "in order to decide what they think",  instead of a classic ( stereotyped?) male pattern of wanting to figure out what they say before they say anything.   What I've observed i my life supports this sex-linked difference, although I'm not sure if it's gender-linked as well.    Women, famously, are said to be much more willing to ask directions when lost than are men.

I speculate that one reason women have trouble breaking into an otherwise all-male leadership gang is that (a) they won't approach things the same way as the men will and (b) the behavior of "one woman", in a way,  is sort of impossible or at least uncomfortable, because it actually takes two or more women to actually wake up the recursive interactive conversation style and channel.  Therefore there is no way that trying out women,  one by one, in the Board Room,  would ever reveal what power three of them say, would have.   You can't extrapolate from one.  It's a system group effect.  The whole feedback path is structurally different.

The role of diversity in meeting member composition

I am always surprised at the number of people who seem to confuse diverse thinking, and people from diverse cultures and viewpoints,  possibly of different races or sexes or socio-economic status,  with legally mandated requirements and giving important slots and limited chairs to, you know, "those people."

I don't want to go into that here, but I think the literature and example from Radio Astronomy is exquisitely relevant.      Astronomers want to get a good picture of the sky, and for this they need two things -- a lot of surface area of the "dish" or "array" they use to collect the weak signals,   and, often overlooked by non-astronomers,   a large diameter of the "dish".     Usually these two things come bundled together, but someone figured out that they can be separated.    The resolution of a combined radio-telescope,  that is the ability to separate two objects that are close together in the sky and realize there are two things there, not just one larger fuzzy thing,  is simply proportional to the diameter of the dish, or, more precisely the resolution along any specific direction is proportional to the distance apart of the two most remote chunks of the telescope along that axis.

So,  you don't need all the middle of the telescope.  You only need parts that are far apart, in order to get good resolution, and to see what's really out there.   I've oversimplified, but you get the idea.

New Mexico's Very Large Array, pictured below, is an example of a single "radio telescope" entity composed of separate pieces that can be widely separated in space.  This is the one featured in the movie "Contact".


In reality the largest such "synthetic aperture"  radio-telescope in use today is roughly the diameter of the planet Earth.   Parts are located all over the globe, from Sweden to Chile, giving a very long "baseline" and therefore very great "resolution of details" and disambiguation of nearly similar sources in the sky.

The math is exactly the same for people,  people.  If you want to get good resolution of the fine structure of a problem,  you need to get individuals with as wide a difference of viewpoints as possible,  and then carefully and correctly "synthesize" them.

Note importantly that the signals are not added, or averaged -- which might result in garbage or zero result because one signal might be going up while another is going down, and the net result is zero.  And the "conflict" between different signals is not resolved by letting the stronger signal "win".

What is required, when the signals are recorded and then brought to one physical location to be processed,  is that the exact "phase" of the signals be recorded,  the exact timing, and not just the amplitude.     This makes all the difference in the world.   Dedicated supercomputers then process the signals to resolve a unified coherent high-resolution picture of the sky.

There is both diversity and unity, but not uniformity, in the mix.

I keep looking for such physical design patterns that work that can be ported over to the question of how human beings can be put together to achieve such an "aperture synthesis".  It's interesting to me that details of timing are as important as "the signal" in the same way that hearing the exact timing of a human conversation is filled with honest signals about what's really going on behind the words.


Summary

Without taking away from current funding priorities,  I am suggesting that finding ways to make human-human interactions at meetings dramatically more productive could be a funded research aim.

Every other initiative, from dealing with debriefing public opinion and wisdom, to innovation, to adapting to climate change,  would benefit from any results from such an initiative.   It is in my mind a "friendly amendment".     I also believe that figuring out how to add more women to the conversation, successfully, without squelching their diversity,  would immediately emerge as a necessary component and change the whole torque of why and how that could and should be done, advancing that cause.

There seems to me to be every reason to believe that a dramatic leap forward in productive meeting technology should be possible, if we can simply overcome our bad experiences with committees and classic meetings and dreaded "group work" in school,   and focus some serious attention on it.





picture credits - the pictures of the pole barn and the radio telescope were found on the web many years ago and aren't mine but I can't locate the originals.  The graph for "Houston, we have another problem" is my own art work.  Image from FOMC meeting in Washington, D.C., Federal Reserve Bank of Philadelphia ( public domain );  Huntington town meeting (CC-by-SA);   image from Tropentag 2018 meeting on how to solve wicked problems.  Fossil Creek Public Meeting ( public domain) 

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Tuesday, February 04, 2020

Systems Thinking about Outbreak Science versus Business as Usual

The novel corona virus pandemic has arrived and, as expected, we are not prepared.  So, while 98% of the effort should go to executing current protocols,  we should still dedicate 2% of our time to keeping notes as we go, and reflecting on how well current systems are performing, and what we might consider doing so that they perform better next time.

There will always be a next time.

I'm bringing to this analysis an undergraduate degree in physics,  an MBA, and an MPH -- Three very different worlds with very different mindsets.   The overlap of those worlds makes the job of any decision-maker much more complex.

Recently there has been a movement to delineate a field called "outbreak science" and get some momentum behind improving things.   Here's an excellent introduction to the idea, in a piece by a very impressive set of contributors.    The paper mentions difficulties where the scientific (and possibly academic ) worlds of the modelers come into contact with the social, business, and political worlds of the decision-maker(s).  My discussion below argues that these difficulties are far more fundamental in nature than can be resolved by having the two groups spend more time together - but I agree heartily that interaction should be practiced with a learning curve on both sides.

Rivers, C., Chretien, J., Riley, S. et al. Using “outbreak science” to strengthen the use of models during epidemics. Nat Commun 10, 3102 (2019). https://doi.org/10.1038/s41467-019-11067-2

Glance at the authors and their institutions here to see who has gotten behind this movement.
https://www.nature.com/articles/s41467-019-11067-2#author-information

In pondering the penetrating power of "Outbreak Science", it would help to have a visual diagram of the parts of the overall system we are talking about evaluating, understanding, and altering via some intervention.    We will be looking at a socio-technical subset of a complex adaptive system,  after all, and there are definitely interactions within that which are not easily captured by our current scientific models and methods.   

 In fact business and politics operate with cultures, values, practices, and  mindsets that are startlingly different from those used in Science,  and that is a substantial factor to reckon with when trying to lay this model out flat for inspection.    

Going into this, I have to bring to mind a quote from Lewis Thomas,  who said this so well in his book The Lives of a Cell: Notes of a Biology Watcher  ( 1971-73)

When you are confronted by any complex social system, such as an urban center or a hamster, with things about it that you're dissatisfied with and anxious to fix, you cannot just step in and set about fixing with much hope of helping. This realization is one of the sore discouragements of our century. You cannot meddle with one part of a complex system from the outside without the almost certain risk of setting off disastrous events that you hadn't counted on in other, remote parts. If you want to fix something you are first obligated to understand... the whole system.. Intervening is a way of causing trouble.
So let's back up a few steps and consider what the boundaries are of "the whole system" - the complex web of interlocking, overlapping, and hierarchical systems from which we are trying to extract one piece to study.

I'll borrow a diagram from the following paper

Shearer FM, Moss R, McVernon J, Ross JV, McCaw JM (2020) Infectious disease pandemic planning and response: Incorporating decision analysis. PLoS Med 17(1): e1003018. https://doi.org/10.1371/journal.pmed.1003018


Situational Analysis

 The lower left grey box,  labeled "Situational analysis",  is the part of the world most amenable to Science,  and with the power of computers and the amount of "big data" available today,  the easiest to expand and improve.    Classic techniques of gathering data are rapidly being supplemented with everything up to Artificial Intelligence scanning store purchases, airline tickets, social media text analysis looking for mention of symptoms, etc.  

The state of the art is startling. 

See:  Mohanty, B., Chughtai, A. and Rabhi, F., 2019. Use of Mobile Apps for epidemic surveillance and response – availability and gaps.. Global Biosecurity, 1(2), pp.37–49. DOI: http://doi.org/10.31646/gbio.39
 
Intervention Analysis
The lower right grey box,  Intervention Analysis,  also is much more amenable to computational modeling today than it was even a few years ago.   Agent-Based Models can simulate social responses over tens of thousands of possible parameters in an afternoon, fit big data to the results,  and convert knowledge into broad statements about response options and likely impacts, as well as helping define what real-world data is simply not known, or only known very poorly.    

Here, however, there are huge uncertainties about how people, companies, and entire nations will behave that dramatically affect the outcomes of given actions or policies.   A freeze on airline travel for example changes everything,  let alone events generated primarily by an effort for Presidents or Kings or Rulers to look good, or stay in power, or shift blame.    

This presents a substantial problem, in that most adult humans are remarkably bad at describing, understanding, or dealing with uncertainty.     Many people, and perhaps particularly high ranking politicians, are loathe to say "I don't know" as that is considered a weakness to be attacked.   The civilian population has no mental framework for understanding even simple statement such as  "Event A has a 30% probability of occurring".    In fact studies have shown that people react quite differently to being told "Event X has a 30% chance of occurring" versus being told "Event X has a 70% chance of not occurring."  

In one hospital I worked at the Biostatistics Department worked out what the odds were of cancer progressing based on pathology and histopathology data, and we asked the doctors for feedback on being provided those numbers.   They didn't want to know about probabilities. They wanted a simple yes/no decision.  


Humans are demonstrably far worse at understanding situations where there are low or very low probabilities of events with very high costs.    For example, what if there were a 1 in 10 million chance that rocks returned from the moon would contain something that destroyed DNA and if released would probably destroy all life on earth?      The quarantine of the returning astronauts wa sort of a joke, as they were put into isolation after floating around in the warm waters of the Pacific Ocean.

Furthermore -- almost any realistic metric of social interest is multidimensional not scalar.  And any sort of value system used to compare options will be multi-objective.  At a minimum there are competing health outcomes and financial impact outcomes,  with different "winners" and "losers", and stakeholders with different amounts of political power and sway. 

What that means,  and this is often missed entirely, is that outcomes cannot be meaningfully ranked mathematically.  They are "non-transitive".   There is no such thing, even conceptually, as "best".

There is therefore no such thing as "optimization", which by itself would require a continuous, differentiable, single-valued "fitness space" over which to optimize.  Social reality has none of those properties.

See the wikipedia article on NonTransitive Dice for more information on that.

Furthermore,  my personal opinion is that the immense number of active feedback loops in real, global social systems means that even the concept of "causality" may not be meaningful.  It is far more likely that entity A is in a closed feedback loop with entity B,  probably multiple feedback loops with different time scales and delays in them,   and it is not possible to say that A causes B, or that B causes A,  because it is really the system structure of feedback which is causing the observed outcomes.  

( See Peter Senge's "Beer game" developed at MIT to demonstrate this phenomenon.)

Again it seems to me to be little appreciated that such feedback loops violate the core assumptions of what in statistics is known as the General Linear Model,   on which many analyses such as multiple regression and published papers rely.    There is no such thing as a "dependent variable" or "an independent variable" in such a feedback loop.   Those terms are meaningless.  Statistics based on them are invalid,

Finally, almost all global social phenomena, probably all, are scale dependent.  Long-term consequences may be completely opposite to short-term consequences.  

Add all those up,  and throw in the fact that the person or persons doing the modeling may, in fact, make a mistake in even the equations for the small part of the universe they select to model.
In my day,  and I grew up with a slide-rule,  we had to learn to estimate the order of magnitude of things, because the slide-rule did not give you decimal points.    We got good at that.  My observation is that most people today have lost the ability to look at a number and say, with confidence, "that must be wrong!" and explain why.   The numbers are sort of a black book.   I had one student in a class I taught to use Excel compute that the unit price of a car was, I kid you not, a billion dollars,  and he wrote that down and turned it in as his answer without comment.  

Summarizing,  the input data are often sparse and uncertain;  the model for how variables interact is far too complex for the average decision-maker to follow; the results should contain certainty brackets, but most people cannot cope with those;  the results cannot be eyeballed to provide a sanity-check that the modeler did not make an error in software; embedded reasoning about causality and statistics may be invalid on a deep and non-obvious level. 

Add these up and it becomes clearer why a decision-maker or politician may be hesitant to stake their career on the trade-off curves the model generates for proposed interventions.

Decision Analysis

The following is my thinking on this subject.  Take it with a grain of salt, at least. 

This section of "the whole system" is the least understood and least discussed, yet if we somehow managed to get perfect surveillance systems, perfect disease progression predictions under various perfectly understood intervention scenarios and mutation trajectories,  we could still expect to see essentially system catastrophic failure to perform as intended at the decision-analysis stage.

To academics, the world of politicians and CEOs is a black box.   What is generally missed, in my opinion, is that a decision-maker lives in a world where uncertainty is the norm.  Most of the world is only poorly understood.   A typical CEO's process of leadership involves deciding a step to take,  taking it, gingerly,  prepared to undo it and retreat rapidly if it turns out the planning they did missed some key variable and things are not as they were modeled.     In other words, fail often, fail rapidly, and adjust your next step.   This is the basic "cybernetic" model.   

This, in fact was basically the strategy used by Loeb ( of Loeb, Rhoades & Co.) in picking stocks.  He said in one of his books that he was wrong about 80% of the time, but that when he was wrong he cut his losses immediately, while he let his winners ride. That was enough to get very rich. [ sorry I don't have the reference.]   The average investor's inability to admit they read the tea leaves wrong, or read bad tea leaves right,  and wanting to hold on to a bad stock "just until it comes back up" is what bankrupts them. 

CEO's know from experience that half the numbers they get are wrong, and the analyses are wrong, but they read them for directionality ( will it go up or down?) not the second or third decimal point of accuracy.   

But, politicians on the other hand are typically trapped by a combination of "face" and strategy that says they are never allowed to be ignorant of some fact, they are never allowed to say "I don't know", and often they are never allowed to admit that the step they just took turned out wrong.    Like doctors, politicians face an audience that does not distinguish between a great policy in an uncertain world which results in a bad outcome,  and a bad policy call.

And, to a real-world leader, there is never time to get things right the first time.  Failure to take action is itself an action and often the wrong action.   "Paralysis by analysis" is death.

So, politicians are forced to act, and forced to pretend, perhaps even to themselves, that their actions are sound.   Consequently, when the results turn out to be bad,  they are prepared to respond and survive by being exceedingly good at shifting the blame to someone else or something else which clearly intervened out of their control, and possibly even enemy action.

The providers of data,  scenarios,  modeling,  and recommendations are therefore directly in the possible line of fire.    There may be pressure for the modeler to come up with recommendations that agree with what the decision-maker, for reasons unknown,  wanted to do anyway.   These are working conditions that many modelers would not remain in long.

And, in many locales, the decision-makers are not about to be honest with the modeler, because the decision-maker has their own secret agenda, and secret stake-holders,  and secret values that may differ from the public good.  

As an extreme example,  we studied in class one cigarette company in an Eastern European country which told leaders there in private that one of its benefits was that it would leave working age people alone,  but kill off a number of them in retirement so that pensions would not have to be paid.   In the USA, there were politicians who were delighted that HIV was killing off gay people predominantly, at the start. 

On a more mundane level,  certain actions, such as arranging transportation of supplies, might need to be routed only through companies that the King's brother owned and operated.   Etc. 

Furthermore,  like all humans,  decision-makers are human.  They get fatigued, especially in some event that drags on for months or years,  instead of being over in a week.   They become overwhelmed.  They possibly or probably do not understand some or even all of what the modeler said, or the reasoning behind it.      Perhaps they cannot bear the responsibility of making life and death decisions for 10 million people.    Perhaps other decision makers in other countries visibly were removed from power or even jailed or executed for making bad decisions.  

Despite all that, politicians are people people.   They need to meet with multiple stakeholders, some with significant power or cash,  and generally in private persuade the stakeholders to go along with some plan.   Or they need to try to figure out a plan, any plan, which could be sold simultaneously to multiple stakeholders each with different needs,  value systems, and mental models of the world. And at least one of that set of stakeholders is the public at large. 

So say we have a top decision-maker who is quite bright and honest.  The area for development then would be whatever type of technology and modeler mediated process or system could bring about an action plan in the middle of such a raging conflict of interests with a limited time window.

Well, actually, for a pandemic,  this would be an 18 month, ever-tweaking process of taking one step, learning new information including the results of a step three time periods ago,  and deciding the next step to take, and repeat that loop forever.

In some venues, the stronger stakeholder simply wins and actions are taken in light of their interests, regardless what the impact is on other stakeholders  including the public and health workers.

In some cases,   these arguments about stakeholder interests have ended up, after a years long process, in the creation of fixed written policies that determine what should be done.  
The bad news as any military commander knows is that no plan survives the first bullet.  That is, as soon as the battle begins,  people look at the policies and action plans, and the plans are based on assumptions that turn out not to be true.  So the entire plan must be discarded.  And there is no time in the middle of a crisis to come up with a better one, in the standard way.

However we are in an area of advanced and accelerating Artificial Intelligence.  What this means is that it is conceivable that a rules-based expert system could be employed.   In such a system, the decision logic is coded into many separate rules, such as "If A happens, do B".    
Properly constructed, such a system would be able to apply all of the rules simultaneously to a given set of conditions and assumptions, and generate recommended actions.   If you fed it the expected conditions, it should basically generate the same results as your written policy manual.  

The difference is that, if the situation turned out to be different, that could be fed into the system and within an hour it would generate a new policy manual that fit the actual conditions on the ground.

Such a system, unlike "neural nets" which are used for much of commercial AI,  could not only generate what actions it recommended, but could explain the entire set of logic and facts it used to reach that conclusion.

Given the accelerating speed of change in the world,  and the dynamic instability of the ground situation, it seems to me that the era of written policy manuals is pretty much over.    A whole new AI-based dynamic approach to decisions regarding actions will be needed,  based on input from epidemiology modeling and intervention modeling.

Without that,  all the best Scientific models in the world at the bottom level of that system diagram are a waste of time, as they will have no beneficial impact on social actions. 





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We need to look upstream!

When things keep going wrong,  it's likely the problem is further upstream than where we've been looking.   The most important lesson from "systems thinking" is that we often need to back up, to stand way back,  and realize that.

Here's an abbreviated repost of a post from June 13, 2007 that's still relevant today.
I wrote this while in Baltimore finishing up my Master of Public Health degree at the School of Public Health at Johns Hopkins University.
===========


There's a very basic concept in Public Health known as "going upstream". The cartoon above illustrates the concept. (if you "click" on the picture it should zoom up to a bigger size.)

Imagine our hero, Tim, sees smoke coming up over the mountain, but he cannot see the source because the mountain is in the way. Say the smoke is killing the crops and Tim wants to "fix" the problem. Where should he go to start looking for the solution?

He could head towards the largest amount of smoke, to the right.
He could head towards the "center" of the problem, directly above.
He could head towards the "worst problem area" or densest smoke, to the upper left.
or
He could follow the smoke "upstream", going around the mountain or possibly over it, until he finds the "source" of the smoke.

I relate to this problem. I was in Edmonton once, visiting, and went to the top of a high rise building to catch the view. We saw all this distant smoke and asked where it was coming from. They said, "Oh, that's from a forest fire in the Rocky Mountains, about 45 miles west from here." So, we got in the car and headed west and went to fight the fire, 50 miles up a dirt logging road from Revelstoke. I'll describe our narrow midnight escape someday.

But, the point is, it is not really true that "Where there's smoke, there's fire." Many people seem to take that much too literally, and head for the densest smoke to look for the fire. Others head for the "center" of the visible problem, and others head for the largest amount of smoke.

In Public Health, we're taught to forget all that, sigh, pack a bag, and head "upstream" to locate the actual source of the problem. Often the source is not visible from where we are.

So, whether it's cancer along the Mississippi river, or developmental problems from lead paint poisoning, or gunshot wounds in the Emergency Room, we follow the Toyota Way and ask "Why?" at least five times - the same way you always got in trouble with your parents when they told you to do something.

For example - Why are so many children getting poisoned by old lead-based paint? Because the paint is peeling off and hasn't been replaced.
Why?
Because they live in terrible housing that's falling apart and neglected.
why?
Because they're poor and the poor are exploited and no one seems to care. Because despite tremendous technology, we can't make decent housing for $1000. Because despite amazing science we can't make companies and jobs that seem able to stay alive and in business. Because the people who could help don't realize there is a need, or are overwhelmed with how large the need is. Because the people who live there don't realize they could get subsidized housing in a much better place and don't know how to "sign onto our website and register for housing now!"

Why?

Now, you're getting into culture and how we distribute resources and education, and how we help or don't help each other, and how we respond to need by hiding the problem and pushing it out of our backyard into someone else's, instead of fixing what's wrong.

The Toyota Way really emphasizes that problems need to be brought to the surface, and made visible, so they don't fester and result in bad results later. Here's a view out of the window of where I'm currently writing this. Can you spot a "hiding" place and see what's happening here?


A huge pile of trash has built up just around the corner and out of sight of the main road.

In any Toyota plant, or anywhere near it, you would not find such a thing. They find they get better results if they deal with problems as they arise, instead of letting them stack up until the total pile becomes so overwhelming that no one wants to even think about it anymore.

Well, I hear a reply, that's because everyone is overwhelmed and stressed-out these days and no one has TIME to deal with "other people's problems."

Why?

This is actually a puzzling problem, related to multi-level depression or something. The "poor" in this country are poor at $10,000 a year, versus $200/year in India or China, if that. I think the figure is that something like a billion people earn less than $1 per day on this planet.

Why?

What's the most intriguing to me is that people in the US seem so fragmented and often unwilling to help each other out, or be helped, even when there are many really good-hearted people who are trying to help.

Or, even when the problem becomes desperate. A family about to lose their home because the mortgage payment just doubled on their fancy new loan would rather lose the home than try to have a second family move in and share the space and share the mortgage payment.

Why?

Because people just don't know how to get along with each other and things always turn bad.

Why?

After easily 5,000 years of written history, why is it that people haven't yet figured out how to get along with each other? If this is a big deal, here, in poverty, in Iraq, why isn't THAT what we study in school, from kindergarten through PhD level work, instead of algebra and physics?

"Because we need all this science and technology to save us from the mess we've made of things here."

Umm... Isn't the dependence or science and technology and the rejection of "learning how to get along" precisely the reason WHY we just spent $1,000,000,000,000 on the post-9/11 "homeland security" and war? That would have bought a lot of houses. Isn't the failure of management and labor to talk one of the big reasons GM lost its lead in the auto business and had to layoff hundreds of thousands of workers?

Well, for "cultural reasons" learning to get along is not a high priority.

Why?

In my book, it keeps coming back to this. We have what appear to be "technical" or "production" or "cost effectiveness" or "safety" problems, and they appear to be intractable, unsolvable by anything we can do. Then we find that "anything we can do" excludes the one thing that seems like it WOULD help, namely, putting a lot of resources into understanding how people should work together, relate, overcome conflict, and fix each other's roofs.

Why?

And that is precisely the point of the "Health, Behavior, and Society" focus on the role that "culture" and "distal factors" play on the visible immediate problems in front of us.

Don't look at the smoke. Go find the fire. Put the fire out, and the smoke will stop.

One last thought - some people argue that this kind of reasoning is no good because it doesn't involve mathematics. They've somehow deified the idea that there is such a thing as rigorous qualitative reasoning. I'm against sloppy thinking, sure.

But I've had more math than most people in this discussion. I've had 6 years of calculus, quantum mechanics, general relativity, statistical thermodynamics, etc. I taught financial modeling to MBA's.

Too often, the request for more math is an effort to avoid doing something that you already know you should be doing. We know enough now, with no more math at all, to know that a root cause of most of the mess we're in is that we don't know how to live with each other and work together. If we could solve that single problem, most of the rest would just dissolve, like a pearl necklace with the thread pulled out.

...

So, enough. I'm off to breakfast.

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