I was initially very disappointed with this book as it is not very much about algorithms. That might not be Hanna's fault as the title on the American edition is "How to be Human in the Age of the Machine".
I still would have liked more discussions about different kind of AI:s and how they are shaped, as I think this is an area where more knowledge is needed to ensure a substantive discussion. But perhaps the book Hanna has written is needed before that discussion can happen.
This book basically just state that AI have some skills, especially pattern recognition, classification and prediction. Given these skills it can do different things more/faster than humans, including mistakes.
Hanna's main point form my perspective is to help us understand that we should apply the same ethics and thinking that we have always done. AI are a reflection of us and as such will always come with flaws. But also that it is the combination between humans and machine that tend to get the best results. So we should try to design systems based on how AI and humans work together. It is a noble goal, but I would have liked to see more discussions about how to increase the probability of that happening.
What I lack is a specific discussion about the kind of flaws we need to look for in AI systems, and even more how to mitigate these flaws. There are a number of areas that could have been covered such as the role of the training data (if you only train your AI for detecting hands on white middle-aged men the AI will struggle to recognise a the hands of black young girl. Or if you only focus on the simple things that are easy to quantify and get the AI to look for, you will miss the non quantifiable aspects that are important.
As a general introduction to the field for those who are "afraid" of computers and AI I think this book might be valuable. For those who wants to dive deeper this is not the book. Being critical in the same way as we always should be is the message Hanna leaves us with, and maybe that is what is needed right now, that we "stop seeing machines as objective masters and start treating them as we would any other source of power. By questioning their decisions; scrutinizing their motives; acknowledging our emotions; demanding to know who stands to benefit; holding them accountable for their mistakes; and refusing to become complacent. I think this is the key to a future where the net overall effect of algorithms is a positive force for society."