Life Stress, Death and Psychological Coherence

My wife died August 23, 2009, after three years of cruel disease (ALS) - slow death, switch after switch of her life switched off. Now what? Her electric stair-case climbing chair is empty, and much more is terribly empty after 41 years of good marriage: Pls see the photo at the cemetry chapel.

Now what, Walter?

In the book "Fantastic Voyage - live long enough to live forever", the authors Ray Kurzweil and Terry Grossman cite a table of stress factors titled "Stressful Events and How They Rate":

I proudly own currently with the factors 'Death of a spouse' and 'Retirement' two of the main negative (killing) factors - and with Christmas I will get another one!

How to survive? fortunately, I understand at least rationally what to achieve and what to do: the psychological theory of Salutogenesis helps defining as goal (for feeling healthy resp. being healthy) the status of coherence and a 'sense of coherence' (SOC). Coherence in this sense of the sociologist Aaron Antonovsky means

• Comprehensibility:
  The cognitive side - understanding the situation with underlying reasons and the naturality of the process (apart from all the contingencies of life and this "why she"?),
  
• Manageability:
  Being able to work through all consequences - from administrative work to a rearrangement of life as far as possible,


• Meaningfulness:
  Accepting some meaning and significance of continuing, e.g. re-finding some directions or detecting new meaning.

This Sense of Coherence is a key notion of the theory of "Salutogenesis".

Although a very, very large portion of human activities in politics, in religions and pseudoreligions and even around science is certainly desastrous, there remains hopefully enough trust in continuing, personally and in general! But this will probably become my 3rd book.

Are there proofs in science? e.g. "the babies of smooking mothers are healthier"

Strong proofs, weak proofs, and very weak proofs: Strong proofs can be seen as adding a burdock to a cluster of burdocks ... in mathematics in particular but (in a somehow softer meaning) also in physics:

The term "proof" is often used in science - but in what sense?

Everybody knows mathematical proofs: A mathematical proof has to be precise and convincing - and then the mathematical lemma is proven for all cases and all times. There are just two minor blemishes:

• Some proofs are so complicated that they are very difficult to comprehend even for the best specialists (and to be proven as proofs),


• more and more proofs are by computers (and mainly by brute computational force): These proofs check e.g. thousands or even million of cases which are all components of the subject lemma (e.g. as has been the case with the four color problem).

In any case, a mathematical proof is interwoven in the system of mathematics (which is for a physicist (see Einstein) as a system and in its perfectness a magic secret):
In this sense, a proof in mathematics is always “strong”.
On the other side, refutation is unavoidable if there has been found at least one case violating the lemma – then the lemma is not in the system of mathematics.
In science we have to be even more careful: If the term “it has been proved” is used, it can only mean:
1. One (or a small number of) experiment(s) with measurements of some precision deliver(ed) in their limits the claimed property.
2. Then we claim that the experiment could be repeated as often one liked to do (and where you would like to do) with the same results in the experimental limits.
Disproof (falsification) means that we have a problem with at least one failing experiment and we have to go “back to the drawing boards”).

Two examples from physics:

• Newton used the solar system and Kepler’s (i.e. Brahe’s) data, and the Jovian satellite system, as the experiments to derive celestial mechanics – and he had, as we know, the magic feeling to have found a law valid for the entire universe, earth and heaven.


• Cockroft and Walton initiated a nuclear reaction by bombarding Lithium with protons and observed experimentally (“proved”) the validity of the equivalence of matter and energy according to the famous formula
  E = m c² .
  

But there are invisible interconnections within many proofs:
The statements and the experiments are often not isolated but networked and parts of “the system”: We have in science therefore marginal statements which are loosely coupled with the system, and substantial statements that are tightly coupled:

• Loosely coupled statements can be falsified without general impact,


• Tightly coupled statements (as E = m c² ) hold the system together. Falsifying means a revolution (probably a Nobel prize).

Through this integration and the securing through the system by many bolts clicking in, we can call this second class a “strong” scientific proof – the hooks to the network give strength (and the looser proof is just a “weak” one).

In another Blogpost, we have introduced the notion of “scientific hardness” - this is just another view of the hardness of a scientific area.

But we have also “very weak” proofs through a practical issue:
Often, experiments and statements use statistical data – and this makes it very difficult to achieve “proofs” even for a singular experiment:

• “hard” (and reliable) are statistical experiments with very large numbers, e.g. in classical physics with 10**23 or more objects, or experiments in the Internet, e.g. by Amazon, with millions or hundreds of millions of clicks,


• “weak” (or just invalid) are experiments with small numbers and by depending on small differences for the proof, as, e.g.,
  o “leukemia in the proximity of high tension lines
  (or mobile ground stations)”,
  o “cancer in the proximity of nuclear reactors”.

It is very easy to make wrong statistical experiments and to draw wrong causal conclusions, and very hard to conduct and analyze correctly. There are many cases where claimed pro-results (e.g. “magnetic fields increase cancer risk”) after a professional analysis on the same data proved clearly the null hypothesis!
Never believe statistical medical studies where only one or two cases more or less make the difference: Try to make experiments under trivial conditions where possible.

The probably most striking wrong and even counter-intuitive “proofs” are examples of Simpson’s paradox which are true ("proven"):
“The mortality in Sweden is higher than in Costa Rica” (in spite of the extraordinary Swedish health care system) – is it really healthier to live in Costa Rica?
Or:
”The mortality of babies with low birth weight of smoking mothers is lower than the mortality of low-weight-babies of non-smoking” – is it healthier for a baby to have a smoking mother?

The explanations are:

• In all age groups in the population, Swedish mortalities are lower than the Costa Rican' - but the Costa Rican population in total is so much younger that the total mortality is higher,


• Smoking mothers are from all parts of the population, mothers with low-birth-weight babies have probably some serious health problem. The mother's smoking affects the birth weight more neutral – together, this gives the observed crazy statistics.

If there are underlying unknown degrees of freedom, the statistical result can be completely nonsense – again: make things simple as possible (but not simpler), a quote loaned from Albert Einstein.

IT: Status and Outlook of AI

Forbes recently had a nice collage of articles on AI and the status of AI :
http://www.forbes.com/2009/06/22/singularity-robots-computers-opinions-contributors-artificial-intelligence-09_land.html

One problem with many critics of AI is that they overestimate the "Human Understanding"! And they are not fair to computers - finally, also we humans do not understand some words or jokes or some CAPTCHA graph (intended to inexpensively differentiate humans and simple computers).

We have to see that some appliactions (e.g. numeric computing, storage and storage-based applications as, e.g., Google) directly benefit from Moore's law and grow exponentially, others only much weaker and grow only linearly in power (as, e.g., speech recognition and natural language understanding).

Therefore, Computers can often directly solve problems by "brute force", e.g. in translation by learning from all accessible sentences Chinese-English. In this Forbes series, Peter Norvig from Google describes this as "unsupervised learning": Given a sufficiently large base of material, e.g. master chess games or spoken English, the computer solution becomes great! The computer is in many cases by orders of magnitude better in pattern finding and association detection!

But orthogonal to this success is improvement by method i.e. in software:

Every software programmer knows that the performance of a simple approach and a better programmed approach can differ by many orders of magnitude even in elementary tasks!

The Turing Test will go the same fate as other negative predictions e.g. "computers will never be able to drive a car" (I remember hot discussions on this): The issue will just become meaningless and uninteresting because it will be obvious that computers can. Then the next human task will get in the focus, e.g. (some degree of) creativity or biomimetic personal robots as Kevin Warwick explains in the parallel article. And finally, there will not be "natural" and "artificial" intelligence, just intelligence - if you use some paper and pencil to make notes and support some thoughts, you are not ashamed either.

Private: ALS and Dog Therapy

There is nothing positive to report from the ALS disease of my wife - it is just strugglng with more and more problems. Now she cannot even stand any more, I have to carry her. It is now very difficult to put clothes on etc..

One highlight was yesterday: our friendly neighbor visited us with the wonderful huge white dog Don Merlin. This Pyreneen shepherd dog is so friendly and beautiful - this was for my wife (and me) a great highlight! Don Merlin is a therapy dog mainly working with disabled children.
A wonderful creature - hope to see you two again soon!

Physophy: The computer science paradox - negative view and less interest, more important

Computer science (I prefer the European term "Informatics") has a strange position in science and society: Everybody agrees that IT is ubiquitous -
but Informatics is less and less visible in the society:

Where are big inventions of computer science visible? Internet and computers are no real computer science results (maybe Google's search is ?).

And Informatics is less and less appreciated: See also the decreasing number of students!
Just saw a note by a scientific colleague working on history and future of science: Computer science is not on his radar - "it is just some auxiliary tool".

Indeed, for many practical purposes, the current IT progress and the professional work done by IT people for business is commodity:

the same ideas as 30 years ago, new trials, and cost reduction is the main driver!
There are people stating that computers anyhow have only two hand full of ideas which are repeated over and over since 30 - 40 years, e.g.

• virtualization,
• caches and working sets,
• hierarchies,
• distribution of control and work (local - remote),
• componentization and integration,
• simple structures (no goto's, today no threads) .

Three more negative arguments:

Informatics builds large systems - in order to do this, it must be strictly and simply structured; this implies a lot of repetitive work (it does not help that this is automated - automation is just lifting the level, the simplicity at the human interface has to remain by definition).

For many applications, IT is under the surface, and the applications are in the foreground (and are visible, and in a company will earn the career).

IT is so popular and fast progressing, that a large part of the pragmatic progress is known to almost everybody who wants or needs to, computer scientists or laymen, - with a relatively low entry level (cp. this to quantum physics, for example!): the professional advantage is often small.

But apart from this unappreciative economic and social role, Informatics and IT become more and more fundamentally important: Informatics and IT are the science and the engineering discipline to organize every work done in society, and because all changes in nature can be described as ongoing work, all nature.

The scientific importance of Informatics cannot be exaggerated:

• basic infrastructure of economy and society (wait for personal robots!),


• new pillar of science and engineering (repeating nature in the computer)


• continuation of the biological evolution:
  Don't forget - life is software, evolution was and will be informatics.

Even the connection between information and physics is not satisfactorily understood - and no limits of IT systems are visible: Informatics builds ultra-large-systems and larger.
But the science behind this is just in status nasciendi!

Therefore in daily life, IT is just infrastructure - but it is also the infrastructure of the human future!

Physophy: A Scientific Hardness Index

Recently, I have read in a blog on a conference on Pseudosciences:
"Nothing against pseudosciences pls - Einstein's theories are probably also pseudosciences" - and I was shocked. (The post referred to the effect "you think about a person, and then he or she calls you", and claimed that this is causally connected).
In my understanding, we have roughly three classes of systems (or sciences):

1. Superhuman systems as, e.g. fundamental science, e.g. particle theory -
   no individual could produce it alone. Mathematics (or computer software of large complexity) is the glue,
   
2. Human systems of varying stability and hardness (established or under construction),
   
3. Pseudosciences (besides science or in contradiction to science).

To have a simple index, I propose to have a hardness scale, similar to the Mohs hardness for minerals, with:

• positive values: scientific statements
  
• zero: neither scientific nor obvious nonsense
  
• negative: non-scientific (para or pseudo).

This gives my proposed scale "Scientific Hardness Index" from +3 to -3:

+3: Fundamental science (superhuman), e.g. fundamental physics

+2: Science established, probably high precision, e.g. astronomy, evolution

+1: Scientific theory under investigation e.g. extended longevity

0: Neutral -neither scientific nor obvious nonsense e.g. visitors from other stars

-1: Beside science but not hard contradiction (e.g. astrology)

-2: Hard contradiction (e.g. predictions, telekinesis)

-3: Proven wrong (or obsolete) (e.g., "earth is a hollow sphere")

These numbers cannot show the tremendous nonlinear difference in the system strength of these levels: I would like to compare

• a level 3 - area with a world class building with concrete and steel,
• level 2 with a solid house,
• level 1 with a play with Lego blocks to try what is fitting,
• level 0 with a heap of cotton balls,
• negative levels just with rings of smoke (more or less hazardous)

I know, this will not end the discussion what is pseudoscience and not, on the contrary, - but it should make clear what one is talking about, about a 800 m height modern construction or about a heap of cotton balls (or mozzarella?) or just about smoke (unfortunately, as you know, you can earn a lot of money just with smoke and cigarettes ...).

Physophy: Evolution continues dramatically with IT

Biological evolution meets IT evolution (the flat blue arrow from the right) in this figure:



A hard consequence of evolution is a major change in the vision of human history:

Look at the historical, clear picture as, e.g., claimed by the Abrahamitian religions:

First, a world is created with a hard and fixed hierarchy of species (the humans are kings and queens and can do with the lowers almost everthing they want - and they do or did),

second, the world runs for a certain time to separate the good from the bad, and

third, the world stops with extinction and nemesis and paradis for the selected.

With evolution, the world has been created in a big bang as a basis (if you like), and then a machinery for evolution has been generated - and with this machinery, there is no reason that evolution will stop (with us "original" humans as final state).

Apart from other (more conventional) driving forces for evolution, we are in an epoch where IT technologies explicitly intervene evolutionarily and accelerate evolution:


Hitting the individual or the population altogether are, for example:

1. Understanding genetics and epigenetics (genetic engineering),


2. Enhancing humans with neuro-devices and more (e.g. neural implantations),


3. Virtual lifes with realistic minds merging to real (and competing with real life),


4. Real virtuality with personal Robots (e.g. competing with real human partners),


5. Social communities allowing collaboration,


6. Mind sharing technologies starting to merge individuas and IT.

In the figure, the evolution in biology up to now ("in carbon") and the evolution in IT ("in silicon", at least for the time being) are joining and opening a spectrum of channels for evolution, from close to IT to close to flesh and blood (in the figure, the green area): It seems that we take all of them. Nobody knows the overall outcome - this is the singularity! And we are not sure that the resulting evolution will be guided (or "intelligent") - neither biology nor IT was "guided" although the latter was even made by humans.

As Ray Kurzweil states: "Life is Software" - and when we are able to change the software of life, improve (?) or add, we perform evolution. Given the many influences and influencers of the coming evolutions made by humans, it is probably again no "intelligent design" - it will be non-intelligent, I am afraid, but it will hopefully be successful whatever this means.