The Great Books Project

The book is about a boy who was charged with the murder of a classmate. The father of the accused, while a state prosecutor, couldn't be disinterested enough to still be in charge of the investigation.

I guess despite one's love towards friends and family, objectivity should never be lost. I still have a lot to learn in terms of objectivity- but it has gotten me started.

Cheers!

Thanks!

2. The authors provide a very clever and useful framework for thinking about new jobs roles as people and Smart Machines increasingly work together. This framework is richly illustrated with many real-world examples. People at all stages of their careers, from university students, to those just starting their employment, to mid-career people, to senior executives, can use their framework to figure out how to position themselves and their organisations as we continue to move forward into this age of Smart Machines.

This book is a great starting point for gaining a managerial perspective on how Cognitive Systems and Smart Machines are actually being used to transform the world of work.  Tom has tremendous depth in how corporations used advanced IT to change and improve their capabilities. As such, the book is very insightful, and quite on target (as in, accurate) in terms of content.

The book is very well crafted. One of the co-authors (Kirby) is a senior member of the editorial team of the Harvard Business Reivew, and she knows how to write for the business oriented reader.

His Joint Special Operations Command forces and organisation were designed for one type of environment. While they had the world’s most capable people and organisation for conventional warfare situations, they were facing an adversary that operated in totally new and different ways, and the much smaller, less well equipped and less “efficient” adversary they were facing was getting the upper hand, and could not be contained.

The book takes you through the story of the transformation of his organisation in Iraq during that 2002 through 2007 period. The beautiful thing about the book is that the story is supported by strong principles. He helps the reader  understand the difference between organising and functioning  as a rigid and efficient hierarchy (his existing organisation)  versus organising and functioning  as a fluid and dynamic network (his adversary, and what he needed his organisation to become).

If you are interested in large-scale organisational change in contemporary situations, you do not want to miss this book.

Some of the examples are from the private sector. Others are from the public sector.

Gillian is a writer for the Financial Times, so she has a great ability for story telling.

This book helps to remind us all of the importance and necessity of working horizontally across organisational boundaries. The book provides excellent examples of innovations that can occur when this happens, and how innovation is stifled when this does not happen.

He was able to motivate the Intelligence Advance Research Projects Agency (I-ARPA)  unit under the US Director of National Security Office to run a large-scale, multi-year “Forecasting Tournament” in order to provide a large data set on how well people forecast a range of  socio-political events.

This book is based on the results of this I-ARPA Forecasting Tournament. Tetlock focuses on those participants who consistently outperformed all the other participants in terms of forecasting accuracy. Tetlock delves into the issues of why a small percentage of people systematically and consistently did a better job of forecasting. Through this book, he elaborates on the work practices and mindsets of those who were the “Superforecasters.”

If you are interested in decision making under uncertainty, and in forecasting under uncertainty—especially in the realms of common and highly relevant socio-political affairs over near and medium time horizans---- then this book is a must read.

From what I understand, this is the only large scale field study of this kind, where there was a large experiment (in this case, a Forecasting Tournament) specifically set up to create a data set that would enable the systematic study of forecasting and decision making for the types of events that were of interest to this community.

Tetlock’s co-author, Dan Gardner, is a journalist and writer, and helps with making sure the book is that well organised and well stated and edited, and very easy to follow and understand.

As this is the eight edition of this text, it is very well structured and carefully presented. Afterall, Professors Bazerman and Moore have been able to refine this text over eight major iterations.

If you are looking for a guide to behavioural aspects of judgement and decision making, this is a great starting point. As both authors teach in business schools, they use a lot of relevant managerial examples.

I like the way this text is organised. If you read through any of the chapters, or through the entire book, it will provide you with an excellent introduction to the foundations of behavioural aspects of judgement and decision making.

As Professor Bazerman notes in the preface of this book (page XX), “…the concept of bounded rationality and the influential field of behavioural economics have largely defined problems according to how we misuse information that is right in front of us. By contract, noticing concerns our bounded awareness, or the systematic and predictable ways we fail to see or seek out critical information readily available in our environment.”

As such, this book is a wonderful complement to the Bazerman and Moore text on behavioural aspects of judgement and decision making. In this book on The Power of Noticing, he focuses on the systematic ways people avoid looking for relevant  information available in the environment that is not right in front of them as they consider the problem at hand.

If you want to further expand your understanding of behavioural aspects of judgement and decision making, to include how people mis-use information that is available to them, as well as fail to use information that could be available to them, then this a great book to read.

The author is a well known research and author in Machine Learning, his widely known text, Introduction to Machine Learning, published by MIT Press,  is in its 3rd edition. So he is a very credible source of information on machine learning ideas and concepts.

He states the purpose of the book as follows in the Preface (page Xiii):
“The aim of this book is to give the reader an overall idea about what machine learning is, the basics of some important learning algoritms, and a set of example applications. The book is intended for a general readership, and only the essentials of the learning methods are discussed without any mathematical or programming details. The book does not cover any of the machine-learning applications in much detail either; a number of examples discussed just enough to give the fundamentals without going into the particulars.”

In other words, if non-computer scientist, especially people from the management or social science areas, want a sound introduction to machine learning concepts, this is an excellent and reliable book to get started with.

The 28 page introduction of this textbook provides the most authoritative and insightful overview to Deep Learning (including the historical evolution of Deep Learning) that you are likely to find anywhere.

As this is a serious text, it will take work to go through each of the chapters. Just by reading the intro in detail, and thenk skimming each of the chapters, and selectively reading more deeply in those areas where you are most interested, you will tremendously deepen your understanding of the state-of-the-art of Deep Learning. Rather than just hearing and understanding the buzz words, you will really understand what is happening, and what these algorithms and systems, together with their data sets, are actually doing.