Book Review-Make it Stick

Make It Stick-The Science of Successful Learning

By Peter C. Brown. Henry L. Roediger III, Mark A. McDaniel

A friend recommended that I dive into this book since I was hoping to learn about the latest theories on learning and cognition; one reason for my search is to be a better coach with volleyball athletes, but as it turns out, this book is helping me become a better college professor.

The authors devoted the opening chapter to the myths and sacred cows that we carry in our minds about how we learn and how to best create an environment that is suited for teaching.  They recount the large number of beliefs that many hold dear as the absolutely truth and then give evidence which debunks them one by one.

The central tenet for the book is stated clearly very early in the first chapter:  learning needs memory and the ability to recall from the memory; people will need to continue to learn and remember throughout our lives in order to function; and finally learning is an acquired skill, not a natural skill, one that need to be practiced.

Very early on in this book, the authors laid out their own beliefs. The first is that learning needs to be effortful in order to be effective, that is, we learn better when learning is difficult. They also believe that people tend to be poor judges when it comes to determining how well we learn a subject; we often overestimate our learning prowess. One of their biggest pet myths is that rereading and massed practices - the perennially preferred studying practice of most people - is the worst and least effective practice habit.

What do they believe in? They believe that learning comes from our ability to retrieve knowledge from our memory, and that we need to exercise that memory retrieval constantly in order to makes sure that it is always there for our recall. They believe that the exercise of retrieval and recall needs to be done with built in gaps in timing, i.e. they need to be spaced; they believe in making the repetitions be unpredictable and irregularly spaced in time, i.e. interleaved.  They believe that before being shown how to resolve a problem, the learner needs to wade into the problem without any clue as to how to solve the problem. They believe that searching for and discovering the underlying reasons for a piece of knowledge is much more important that just being able to perform a skill repetitively, although they do acknowledge the importance of being able to repeat a task procedurally.

Although the ideas and methods that is covered in this book is not all completely new to me, the presentation and organization is quite interesting. They can cite a great number of studies in the scientific literature that effectively and sufficiently support their arguments against the stated myths while citing enough studies which also amply support their arguments. The most interesting part of the book came to me after I had read it from cover to cover and was sitting down to review what I had learned. What the authors cleverly did is to use the very desired practices that they are espousing in structuring the book. They spaced the same descriptions of the desired practice repeatedly through the text, they interleaved certain arguments in all the chapters, they gave the reader time and room to discern the underlying principles, and they motivated the reader to elaborate on what they had learned to themselves, at least I did.

I am relatively certain that this was deliberate.  Indeed, I followed the rut that they had called out in their recitation of bad learning habits and strategies as I was reading, rereading, and taking massive amounts of notes in order forcefully lever the ideas into my head. Little did I know that the authors had, by the nature of how the book is structured, created an opportunity for the reader to practice what they had preached.

As I stepped through my memories of the time that I was reading this book, along with a couple of other books on how to best learn, I unintentionally spaced and interleaved my learning from this book because I was switching between books, a practice that I had picked up as a matter of habit as my learning habit throughout my life. The real question is then whether this tactic was successful: did it accomplish the goals in the way that the authors had intended? I can’t speak for the longevity memory retention of the lesson from the book, but I can say that I did spend a lot of time thinking and understanding the underlying principles. I will be able to speak to the longevity of my learning with their preferred methods when someone asks me about the book in a few years, but as of now, I had worked long and hard on learning from this book.

Book Review-Hello World By Hannah Fry

The idea of artificial intelligence, particularly the application of artificial intelligence algorithms in the service of human activities that have always been human based both scare and fascinates us, that idea being a fecund field to harvest for popular literature and films.  We humans, with some of us relying on overdeveloped imaginations, dreams of AI as the solution for everything that ails us. While for other humans, those with an overdramatic sense of pessimism, have nightmares about how human society will be conquered by droids who will eventually destroy us.

The truth I believe, is somewhere in between. One of the problems is that the general layperson has no idea what AI entails and how it works, not how well or how badly it works in real life. The popular media is of no help as they are wont to lean towards the sensational, in both the optimistic and pessimistic directions to enable the selling of papers or website subscriptions.

Fortunately for us, there are people like Hannah Fry, a mathematician, and a hell of a good writer to explain it to us, if not the nuts and bolts of AI, then the results of existing experimental results and how the algorithms are applied to real world problems. To get Prof. Fry’s credentials out of the way, she is an associate professor in mathematics at the University College of London. I am a fan of her writing in the New Yorker, as she has a way of explaining the details and nuances of mathematical topics with great clarity and ease.

The subtitle of the book is: Being Human in the Age of Algorithms. It is both somewhat comforting and a touch menacing at the same time. I took it to be comforting. The title Hello World comes from an example in rudimentary programming classes, the very first program any neophyte programmer writes are programs that outputs: ‘Hello World’ onto the screen. I too, have had the excitement of having those two words present themselves in my computers. So, it is a welcoming sign, it is also a foreshadowing of what is in store for the reader in the succeeding pages.

The book is divided simply into nine total chapters; an Introduction and Conclusion bookends the middle chapters named after seven distinct parts of the human existence as we know it in the 21^st century. They are: Power, Data, Justice, Medicine, Cars, Crime, and Art. While the structure of the book is simple enough, the intent of the book is quite ambitious. Prof. Fry lays out the present and past excursions we humans have made into the realm of using artificial intelligence to alleviate human based computational efforts. Some reasoning which drove us to evolving our decision-making advances along this route involves the perceived and many times a real need for faster and more accurate computations. The faster part is won handily by computers, and most of the time the accuracy part is also won by the computers. What people forget is that first, the computer’s cogitations is only as good as the data and to a much larger degree, the algorithm that it is given.  It is garbage in, and you get garbage out. The parallel effect is that if you have garbage logic cooked into the algorithm, then garbage out as well. The more egregious result then is that garbage analysis and interpretation of the results mean even worse garbage out.

Prof. Fry goes through each of the seven topics and demonstrates where the human propensity for bias creates disastrous errors in inference and in computing the wrong numbers or asking the wrong questions. On the other hand, she also takes great pains to explain why computers are much better suited to not just doing the computations quickly but to also make decisions quickly and at times more accurately. One would think that the main arguments in a book such as this are all along the lines of: it is game over, let the silicon-based lifeform govern our existence, but that is not the case. Prof. Fry explores and negotiates the complex and nonlinear landscape of what we humans have done in experimentation with designing and allowing algorithms to make decisions for us in order to get at the clearest picture yet of what AI can do for and against us.

She tells us stories of how Gary Kasparov, chess master, the very epitome of human decision-making prowess, became seduced by the idea of the AI, after having been beaten by Big Blue. She tells us about how a self-driving car is supposed to navigate our highways and byways, but still can not do so safely. She, most disturbingly, tells us how our government, in their attempts to simplify and creating accurate decision-making processes had wreaked havoc in our society, thereby creating equality issues in how justice is dealt out to us. Indeed, I found the chapters on Data, Justice, Medicine, and Crime the scariest and the most fascinating because those chapters hit the closest to home. The idea that our faceless bureaucracy places their trust on unrealistic, biased, and logically error ridden algorithms to handle our privacy data, decide on long term guilt and innocence of our fellow humans, cure what ails us, and solve problems due to human proclivity to trespass on our fellow beings is decidedly unsettling to say the least.

In every chapter, however, Prof. Fry collects and organizes the stories in easily digestible and logically intuitive chunks, giving us cogent arguments for her opinions.  In the Conclusion, she lays out her case, buttressed by the facts and gave me quite a bit to think about, after of course, educating me on the nuances of the intricate and logically confounding sequence of action, reaction, and unintended consequences, which we are not very able to predict a priori.

My belief is that this is a must read for all cogent human beings who live in todays’ world of technological abundance. We can not live without fully understanding how decisions are made by algorithms, most importantly, we need to understand how those decisions can be wrong. In addition, we must also learn how we can leverage the algorithms so that the computational tools can be used in conjunction with those areas of cogitation where we human have an  advantage and succeed in creating a more perfect society.