Overall I'll give it to Leonard Mlodinow for writing a math book that's surprisingly accessible to the general public. Well, maybe it's not exactly a math book, or even a statistics book. But there's a fair amount of each and he did a fine job with keeping it generally light and interesting.
Mlodinow explains that there are basically two definitions of random, and they don't always go together (pp. 84-85). The first is by Charles Sanders Peirce and basically states that a process or method is truly random if given enough tests, trials, samples, examples any outcome is equally likely as any other (the "frequency interpretation of randomness"). In other words, regardless of how things seem (especially when you're only looking at very little data), there's nothing "special" going on that prefers or encourages one result over another. Mlodinow doesn't go in this direction, but I would say most people would relate this to/understand this in terms of neutrality, equality, fairness, balance, impartiality, etc. Setting aside debates in cognitive psychology and linguistics about modules and association, let's just say that most people would say these things are important (ideally) in business, law, politics - anywhere where people and things should be treated the same. Mlodinow then offers the second common definition of randomness, the "subjective interpretation," where "a number or set of numbers is considered random if we either don't know or cannot predict how the process that produces it will turn out." Again, he doesn't take this road, but I think most reader would relate this to things like luck, whimsy, risk, guess, judgment, odds, choice, etc.
You'd think that he'd establish these weird heavy definitions and and run with them for another 200 pages. But he doesn't. He leaves these definitions orphaned on pages 84-85, which is a shame because they seem to be the most interesting and relevant part of the whole book. What was the purpose of bringing them up at all? Better question is What is the purpose of the book? Sure, to sell books, makes some cash, and better inform the public. But more than that I think this book somewhat aims at the "big dreamers," those people who seek big success, or at least dream about it, and want to know why it works. Or why it doesn't. Mlodinow uses a fair number of examples of business stories, Hollywood stories, scientist stories, and gambling stories. It's not a glorification attempt, but to illustrate that luck has a lot to with it. From Bill Gates to Bruce Willis, Stephen King to Anne Frank, Thomas Edison to George Lucas, luck plays a role as much as hard work. He offers the advice to persevere to those who aim to succeed because often not bad talent but bad luck that fails you. Okay, fair point. I think this is the kind of stuff that people want in such books so it's included for "sentimental" reasons, but it doesn't tell us anything we don't already know.
What is interesting to me is the discussion of why we believe what we do and how we act accordingly. Mlodinow discusses factors that influence our perceptions and our ideas. He references a few studies, including Daniel Kahneman intuition studies and Melvin Lerner's Just-world phenomenon, but he doesn't really go into the details. In particular he glosses over part of Kahneman's study and overlooks a point that's essential to his own book. On page 22 he reports finds of a fictional character "Linda" described with, I guess you could call it, hippie or generally leftist leanings, and participants ranked the likelihood of 8 statements:
1. Linda is active in the feminist movement.
2. Linda is a psychiatric social worker.
3. Linda works in a bookstore and takes yoga classes.
4. Linda is a bank teller and active in the feminist movement.
5. Linda is a teacher in an elementary school.
6. Linda is a member of the League of Women voters.
7. Linda is a bank teller.
8. Linda is a insurance salesperson.
The point here was that number 4 includes number 7, but was ranked as more likely. Mlodinow used this study to show that intuition is not a reliable judge and that people tend to make obvious mistakes once they get an idea in their head. (Specifically, Kahneman demonstrated that people are more likely to believe something is the case when additional, even irrelevant information is provided. But I read something else in this study - that people probably take number 7 to mean "Linda is a bank teller, but not a feminist." Maybe the original study specifically controlled for this (I doubt it), but the point is that number 7 is not "neutral" or "interchangeable" with other items. Whether she is a bank teller seems (to some degree) to be relevant to her social-political identity, as much as any of the other items suggest. For example, if they use "Linda's new shoes are blue," or "Linda was born in July," people would say they're both totally irrelevant to the description and uninformative to where they should rank. Is this really a relevant point? Maybe, maybe not. But I bring it up to show how difficult it is to really identify what people take into consideration when making decisions, which is a big part of what the book is about - given the fact that so much is outside our control, awareness, or understanding, how do we choose wisely?
A fair amount of the book is dedicated to math and statistics. I think most people will find it manageable, or can safely skip over anything technical without missing much. About half of it is really "about" the first definition above (frequency) - and that's the heavy math stuff. The other half is about how people act and think when there is not enough information to know better, and what goes into that thinking. I don't know if this would do much to really change how people think about chance, statistics or randomness, as he seemed to specifically avoid technical issues. Most people will probably just fit each case covered into their present ideas of any of those italicized words I put after each definitions. Those are the real concerns I think most people have on this topic, and he did a fair job covering them.
I wouldn't call this a social science classic, but it was entertaining and easy enough to get through.