# Beginning a book has always been a tougher one and if good, finishing it off is that much easier. This one starts with a few flashes of things around our lives, exemplary classified into technical and logical terms. I was captivated by much of this book wherever the author used past events to tune into the future with more coherence, citing several laws unknown to me. Although this book is subtitled 'the computer science of human decisions, it's really about the intelligence of human decision-making (which is often supported by computers) - I suspect the 'computer science' label is to make it more attractive than boring old mathematics. The book tends to skip over the mathematical workings, concentrating on the outcomes and how they're relevant to the kind of decisions we make in everyday life - and it is that application side that makes it particularly interesting.
Here are some chapter-wise (book) markings:
# The ‘Secretary Problem’ deals
with when should you stop interviewing a secretary candidate because the last
one to be interviewed is just based on time and not on talent. It might seem
there can be no sensible advice, but mathematically it's very clear. You wait
until you've got through 37% (an empirical rule) of the choices, then pick the
next one that's better than any you've seen before. It's not that this will
necessarily deliver your best of all possible worlds. But it will give you a
better result than any other mechanism for deciding when to go for a particular
option. The authors point out that there
are approximations to get around this, which include that the approach can also
apply to the amount of time available for the process. There are several such
corollaries in our lives nowadays, particularly the feeling that if we could
have waited a few more days we would have got a better mobile.
Gold digging is more likely to succeed than a quest for
love. The author stresses the need to
evaluate the choices. Some problems are better avoided than solved.
Quote: Stopping early and starting late are two ways to
fail.
# Explore / Exploit: Gathering
information (by all means) is all about the second chapter. You are more likely
to explore new restaurants when you are moving into a city than when you leave.
There is this mention of clinical trials which have often been the subject of
some movies and the author points here to the 40 years of trial on human syphilis
that was halted as it was notoriously anti-health and is a grim reminder
of the uncertain ventures which humans always do.
Who would you like to spend time
with – family or friends. Older people preferred family and young ones not,
but they later changed their opinion after some ordeals. So, experience counts.
Quote: To try and fail is at least to learn: to fail to try
is to suffer
# Cache: The concept of caching
can revolutionize your filing system. The Akamai is into the caching business
and has been a pioneer in the system as it handles about half of the entire
internet traffic in the third world. The problem is not storage but organizing.
This section is reveling to read. There is a reference to how IBM evolved.
Quote: Forgetting is as important a function as
remembering – the mind has an infinite capacity for memories but only a finite
amount of time to search for!
When you
switch tasks you pay a price. Humans have this tendency and the author comes up
with the mention of a few rules such as Bayes’s Rule (communicates a sensible
strategy for gauging your expectations and then revising them as new
information comes in), Laplace Law, and Copernicus principle. The Laplace law
was interesting to me as it gave a simple formula to win; (w+1)/ (n+2) – where
w is the winning ticket and n is the number of attempts. While talking about these
things I had a slight notion that the author was talking about order and
disorder of things and in thermodynamics we have the third law to govern these
things (read entropy). Things that tend towards some kind of natural value and
things that do not, are the two types of things.
Then this Multiplication rule
made an interesting entry – the total wait people expect is one and a third
time as long as they have waited for. Marshmallow test over children who wait
suggested that slow learners or those who wait had better future or rather
mature future.
Occam’s razor principle,
nevertheless old, has a new foray “all things being equal the simplest possible
hypothesis is probably the correct one’’.
Quote: Things which matter most
must never be at the mercy of things which matter least. Do the difficult
things when they are easy and do the great things while they are small.
#Relaxation: It teaches us to
simplify problems to gain traction on them, to not let the perfect solution be
the enemy of the good enough, and when to disobey the law. There is Lagrangian
relaxation, where the main idea is to relax the problem by removing the “bad”
constraints and putting them into the objective function, assigned with weights.
Randomness
encourages us to lean into the role of uncertainty and to latch onto small
improvements and happy accidents. This section also deals with the ‘Monte-Carlo’
method and its origin. Stan Ulam, who also helped develop the atomic bomb suggested
this method based on the famous card play pop-ups in Monaco. That sampling can
succeed where analyses may fail is the heart-line of this concept. Replacing
exhaustive probabilities and calculating with sample simulations have been very
successful and we use these methods in Quantum Mechanics still.
Quote: The perfect is the enemy of the good.
# Networking is a fun dive into the world of communication,
and the algorithms that govern our interactions online. From Packet-Switching
to Circuit-Switching the section deals with the advent of networking, and wireless
as well. There is a mention of the paper by Gordon and Prabhakaran on the ecological study that relates an algorithm on networking to be about a million
years old. Obviously, humans have been on the logic route for long!
Peters’ principle that we often
hear made a sensible end to this chapter: Eventually every spot in an
organization will come to be filled by someone doing that job badly. I enjoyed
a loud laugh in my mind because is it not this thing that is happening
everywhere now!
Quote: Now is better than never - Zen
# Game theory is about the mind
games we play when trying to anticipate the thoughts and actions of others, and
how those mental models play out from poker to work schedules. I know, you know
that I know, I know that you know that I know, the three levels reminded me of
six types of personalities clashing when two persons talk. Dominant strategies
avoid recursion altogether. The optimist proclaims that we live in the best of
all possible worlds: the pessimist fears this is true. The Game theory offers a
suitable answer – Happiness is the lock.
