#Algorithms_to_Live_ by - Brian Christian & Tom Griffiths - Review

# 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!

 # Scheduling: This section deals with interesting aspects of timing or prioritizing and mentions the “Gatt chart” that was used to build the Hoover dam and has assisted IKEA, Amazon, and SpaceX in scientific management. The author suggests that the earliest due date is optimal for reducing maximum lateness. An interesting incident of priority reversing caught my attention. The incident is related to Perseverance – the spacecraft to Mars that was programmed to take and send pictures from 309 million miles. The high priority of the robot was to move the data in and out of the information bus. But due to scheduling, the robot was neglecting as the system resources were prioritised over that. The multimillion-dollar project would have failed if the engineers from the Earth did not re-program it to re-schedule and change priorities (read IRQ).

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.

 Christian and Griffiths conclude with a pitch for "computational kindness" where we can use our knowledge of algorithms to reduce the amount of mental work we have to do. We can design a society with optimal laws and incentives that make the right thing the easiest thing. At the end of this session of the book, I just felt I have sharpened my approach to what logic is and I feel that this book lives true to its title. A lot of work and plenty of biblical references make this book worth keeping, reading, analysing, and diving into all sorts of logic.