Book : What to do when machines do everything : How to get ahead in a world of AI, Algorithms and Big Data by Malcom Frank, Paul Roehrig and Ben Pring

As soon as I selected this book on Amazon.in, the site’s recommendation engine popped up another book as something I would also be interested in: ‘The Industries of the Future’ by Alec Ross. I was surprised and a bit disappointed at the same time. That’s a book I not only love, also I bought it from the very same Amazon last year. So while I was happy that the platform could predict what I will like to read, I was disappointed that it should have known that I won’t buy the same book twice, especially the Kindle edition. This possibly portended what the book 'What to do when machines do everything' was about: AI is already here. But it’s far from perfect. And it’s going to take a lot of hard work and right strategy to pull it off right.

Like the authors, I am a fairly good student of history and I am deeply aware that tectonic shifts in human societies due to scientific advancements and industrial revolutions are not new. But I don’t remember reading about any period in the past where so many innovations are about to change the society so profoundly within a blink of a couple of decades. Robotics and Automation, supported by AI and Big data, is only one piece of the tectonic puzzle that’s being assembled with rapid hands by humankind. This book covers it extensively and we will see how, in detail in a few moments. Among others round the corner are advancements in Genome research which may let us have children with designer genes (sic) that may prevent many health problems and the Crypto currencies which may blow the fig leaf of control that governments have over the economy in the capitalist world: supply of currency. While all of them can raise moral, ethical and existential questions today, none of that is going to stop even if you wish hard.

“What do to…” is distinctly a ‘practitioner-experts’ written guide book on AI and its impact on industries and societies and the authors have refreshingly abandoned ambivalent arguments and give some convincing answers to existential questions about job loss and jobless growth. In the first part of the book, the authors have thrown away the kids gloves to deal firmly with the negative hype around automation that’s now become the rant of the CEOs and politicians alike to hide their non-performance. The authors do so as much with their intellectual prowess as with impressive data.

They emphatically establish that AI and automation will result in net addition of opportunities and urge us to avoid the static hypotheses like ‘Assuming everything else remains constant, we will lose…”. It’s simple: everything else will not remain constant. It never did. Humankind will indeed be enabled by AI and automation to do much more with much less and that will add to prosperity. New jobs created by digital explosion will more than compensate for the ‘lost’ jobs, which any way deserve to be lost and also make the new jobs much richer in content. And finally, they urge us to approach the whole issue with faith in the future and open mind to immense possibilities than with FUD (Fear, uncertainty and doubt). As I said earlier, they have done this with quite impressive data sets that’s hard to refute and in my opinion, in fact quite conservative.

With that, I will move on to part 2 of the book, where the authors’ professional consulting experience comes alive in full. The transition to part two is a transition from ‘what’ to ‘how’, the declarative knowledge to the imperative and from poetry to prose. The authors have handled the transition quite smoothly. And the imperatives are dealt with very specific examples and use cases that are invaluable to a (near) future enthusiast. They define AI in the most succinct manner and they say what matters now is the narrow AI or ANI. They resist from indulging in sci-fi and singularity. And in essence, are quite practical. 

They outline their AHEAD (Automate, code Halo, Enhance, Abundance and Discovery) model to deal with AI and its implementation. The whole model has been extremely well articulated and presented in an actionable way. Whether you are leading a fledgling start-up or trying to steer a huge corporate ship, the guidance by Malcom, Paul and Ben will provide deep insights and even suggest what to do on Monday next when you turn up to office. They are pragmatic (and in fact I was reminded of Steven Levitt) in advising us that not every initiative needs to be a result of ‘Thinking Big’ and boiling the ocean. There is value in taking small but successful steps towards the digital journey. With that, and with no further spoilers, I recommend that this is a must read book for 2017 for anyone who doesn’t plan to spend rest of their lives in a cave.

I did feel that the authors missed some opportunities. One is obviously on cyber security. I fully agree that muck or hack will hit the fan once in a while when you are transforming and if you get fixated with it, you may miss the bigger opportunity. And that’s why the authors may not have a distinct place for ‘Secure’ in their model right now. But, I will look at it slightly differently. Bad guys will exist. And they will use the same AI and algorithms to get better at their trade and it won’t remain a one off issue soon. In fact, like Lee Sedol learnt from DeepMind AlphaGo after a string of defeats while playing Go, there may be very valuable lessons for humans to learn from the machine in protecting our digital borders and that can be a big business and job opportunity. 

Secondly, they seem to caution us against the ‘silicon valley is eating the world’ type of thinking and rightfully project that many centuries old organizations will have an immense advantage in the digital age, if they pull it off. While I have no qualms with this, I do read (between the lines?) that they subtly indicate that FANG type vendors may be just an ephemeral spark that lights up the digital revolution but will eventually play only a marginal role compared to the industry heavy weights. My view is that the Silicon Valley titans will continue to expand the digitization of human societies in equally big ways that are impossible for the traditional companies to do. Facebook and WhatsUp are already revolutionizing how societies and even crowds behave or how quickly justice is delivered etc. I found the comparison a bit unfair.

Thirdly, some data points on how AI is effecting the demography change in the working population would have given some more color. Will the word ‘retirement’ cease to exist, as more and more of the back breaking mundane tasks get automated? As one of my older uncles said “If I can use the shower, I can work as well”. Will we see a far broader spread of age groups that are gainfully employed as opposed to the 25-60 today? Will it change the millennial mind set of ‘get rich early, retire early’?

Finally, I must admit that I immensely enjoyed reading this book and I appreciate Malcom, Paul and Ben for producing this wonderful piece.