Archives for category: Books

And the winner for most on the nose book title of the year goes to…

Sarah Wynn-Williams’ recounting of her time at Facebook (now Meta) is at times funny, horrific, and plain sad. From true Facebook believer, who pitched her dream role, international governmental policy, to at first disappointed employee trying to change things from inside, to full blown dissenter, and (spoiler) ultimately fired whistleblower.

There are few familiar names that come of well in Ms. Wynn-Williams’ telling. Mark Zuckerberg and Sheryl Sandberg come off particularly badly with their clueless and tone-deaf behavior being only the start. It is also telling that there are currently no slander or defamation suits against the author for the memoir, only an order enforcing her NDA (Non-Disclosure Agreement) signed as part of her separation agreement.

Ignoring for a moment the wider societal issues with Facebook that are the main thrust of the book, what the author shows off is the often-dark side of the Silicon Valley myth. That while the pay and benefits may be great, the workload is deliberately punishing as an instrument of control. That anything outside of work is seen as an almost disloyal distraction. What is often portrayed as quirky, is often just mean behavior and nepotism with a significant dose of classism and well – carelessness. That it is far better to ask for forgiveness than to ask for permission, regardless of the potential consequences.

Where this volume really scores is in exposing just how deliberately powerful and impactful Facebook can be when it comes to manipulation. That Meta just does not care about the consequences of this or the impact around the world. It cares about getting new users to generate more business and that’s it. Whether it be vulnerable teenagers, peoples struggling to wrestle democracy from authoritarian regimes, or actively embedding staff with political campaigns to spread false information at home, Facebook seems to play the worst role possible. It is illuminating how the lessons learned from real world events are the worst lessons possible and that these are the last people we should be letting have oversized roles in our society.

The public face and social engagement of the leaders of Meta is all front. Sheryl Sandberg’s “Lean In” book and subsequent foundation are shown to be shams by people who not only do not practice what they preach, but also would be horrified by the mere temerity of the idea of being called out on this.

This is a book that exposes titans of Silicon Valley as not only shallow and immoral, but without any ethical framework or even basic decency. The very worst of the “let them eat cake mentality.”

While the book has a little of the “this was awful, but I did not say anything” that is often found in whistleblower accounts, this is kept to a bare minimum and while Ms. Wynn-Williams comes out of the account pretty well, she freely admits to her own naivety, and her wide eyed idealism.

This is a book that will make you think long and hard about your own Facebook usage but it really is about just how out of touch tech leaders can be, even with basic HR norms, and just how much the people who unleash technological forces just do not care about anything other than their own interests.

Careless in other words.

“The gradual degradation of an online platform or service’s functionality, as part of a cycle in which the platform or service first offers benefits to users to attract them, then pursues more and more profits at the expense of users.” – Dictionary.com definition of enshittification.

Originally coined by the author, Enshittification has entered the lexicon as it has struck a chord with everyone who feels, or is beginning to feel, that the maturing of the technological internet revolution is, well, shit.

Almost a companion work to Yanis Varoufakis’s Technofeudalism, which it references in several places, Enshittification is an easy to read take down of the business model of the internet giants that rule our lives. That those same internet giants deliberately make our lives worse due to their constant drive to extract profits and that this is at the expense of the user experience and the experience of the business customers who pay for it.

Doctorow’s basic premise is as follows:

1: Attract users by making a useful, responsive, and fun product usually at a loss.

2: Attract business customers by selling the user’s data, even if you’ve promised not to, creating a powerful tool for selling to users and driving other forms of sales channels out of business.

3: Squeeze every last dollar out of both users and business customers since you now have a monopoly in the space and the costs for switching are too high.

While Mr. Doctorow makes a great case for the macro-economic models for technology companies being fundamentally broken at best and downright predatory, immoral, and possibly illegal at worst, his hyperbole sometimes gets in the way of detail.

Veterinary medicine, my own former industry, gets a line in the book. Accusing corporate consolidators of paying veterinary staff minimum wages and then demanding that they pay thousands of dollars if they want to leave. While the consolidators and venture capitalists in veterinary medicine have a lot to answer for, I don’t recognize this particular piece of enshittification. Yes, some of them do pay staff minimum wage, but the repaying thousands of dollars sounds like repayment of school loan payments or signing bonuses which usually only applies to DVMs and perhaps LVTs/RVTs/CVTs. None of those are getting paid minimum wage. I guess it could be a reference to repaying money for vet services, but it is hard to imagine any company not wanting paid for services delivered.

I mention, and examine, this single veterinary medicine sentence because the conflating of two different facts to paint a picture which I should, but don’t, recognize gives me pause when considering the veracity of the book. Given I don’t know the business models of Amazon, Facebook, and Google nearly as well as veterinary medicine, should I take this as a poor bit of research or an example of flawed thinking?

And it’s a shame, because I buy Doctorow’s arguments otherwise. While the style and language is friendly and accessible, this book does deal with a number of complex anti-trust issues which the author masterfully navigates and explains. If not for the vet med line I would be bought in hook, line, and sinker. It is certainly possible that I’m bought in anyway.

One of the issues that books of this type can sometimes have is that they are either overwhelmingly positive or negative. While there is a lot to feel negative about in Enshittification, Doctorow does map out a pretty good manifesto as to how to reign in these tech giant monopolies. Unfortunately, advice on how to fight back at the user level is a little thin on the ground.

If you have the feeling that the internet is dying and the technology you used to love no longer seems to love you, then this is the book for you and it is a rallying cry for how we might fix it. Because if we don’t fix it nobody else will. The technology firms are just too powerful and there is too much money at stake for them to let anyone else clip their wings.

However, we made them, and we have the power to break them – but only if we try.

And try now.

“Why Superhuman AI Would Kill Us All” is the subtitle of this surprisingly grounded and tempered look at AI safety – despite the hyperbolic title.  

Being an AI critic, I have written extensively on this site and elsewhere as to why our current seeming infatuation is dangerous for our culture, counterproductive, and almost certainly a giant Ponzi scheme. What I have neglected, for the most part, is the very real danger of Artificial Super Intelligence (ASI).

What we call AI today is machine learning that uses Large Language Models (LLMs) to summarize and average data – usually with little to no regard to privacy, copyright, or other intellectual property issues. While we can use LLMs to converse with, to write for us, generate images of us, and seemingly provide insights they are just feeding us back the data that they have received in a different form.

Artificial General Intelligence (AGI) is an AI that is as good as a human in almost all cognitive tasks. In other words, it thinks as well as we do.

Artificial Super Intelligence (ASI) is an AI that exceeds humans in most or all cognitive tasks.

Our current obsession with AI is based on the idea that investing in machine learning will lead to AGI and then to ASI. This is disputed by some researchers who consider LLMs a dead end. A dead end that could potentially collapse the economy – but that’s a different story.  

Messer’s Yudkowshy and Soares hypothesis is simple; that an ASI would consider humans a threat, or just an impediment to its aims – and of whom we would have little to no knowledge or understanding. Therefore, the ASI would have no reason not to wipe us out in furtherance of those goals. In many ways it is similar to the deadly probes hypothesis which has been popularized as the Dark Forest theorem through the Three Body Problem books / TV Show. The Dark Forest Theorem states that the universe is a dangerous place and that if a species reaches out to other potentially intelligent species it runs the risk of encountering an unfriendly species who could be more advanced than them. Much like why it might be more sensible for someone lost in a forest to keep quiet in case they attract predators.

An ASI could easily conclude that it would just be more expedient to remove a potential threat instead of running the risk of our potential future interference or our creating another ASI which we felt was better.

Being a devotee of science fiction is hard to not think of this issue in terms of the books and movies that have inundated us for decades; however, as the authors point out, an actual ASI would have goals and ways of thinking that would be dramatically weirder than we can imagine or understand or be able to understand.  

It is unfortunate that films such as 1970’s Colossus: The Forbin Project are not more widely appreciated today. Sure, it’s a little cheesy in places, but the scenario it presents could be all too real and we tend not to treat ASI issues with this level of seriousness:

As Yudkowshy and Soares point out, we do not craft AIs today, we grow them. We do not understand how they work. If LLMs do lead to AGI which in turn could lead to ASI, something we may not be able to detect until it was far too late, how are we to ensure that they will not work against us? Most leaders of AI companies today dismiss these concerns. But their reassurances do not seem to hold up under even the most basic of scrutiny. “Because we won’t make them that way,” is not reassuring when no one can control how something grows. The book also makes a great case that ASIs’ will not have allegiance to any nation state and so the argument for continuing research because other countries are doing it is easily discredited.

While the authors’ overall case is compelling, and one we don’t hear often enough, even from AI skeptics like myself, they hurt their case with some lazy analysis. Using World War II as an analogy as to how the world came together to fight fascism and so therefore the world can come together again to fight the potential threat of ASI holds almost no water. The British and the Soviet Union both tried appeasing Nazi Germany, and the USA only came into the war when one of their colonies was directly attacked by an ally of Germany’s: Japan. Yudkowshy and Soares use of the world reaction to CFCs and Unleaded petrol / gasoline works better, but one only has to look at the world’s reaction to climate change to see the holes in this example. Likewise, the inconsistencies in the implementation of non-nuclear proliferation do not bode well for using it as a model for controlling research into ASI.

While the book makes the case for a moratorium on all AI research, it is hard to imagine anyone doing this with our current AI obsession and our willingness to ignore all the other great reasons why we should turn away from this technology: intellectual property theft, the impact on personal cognition, hallucination / bad data problems, and an unsustainable economic and ecological model.

This is a great book that focuses on one argument and makes its case. It’s unfortunate that it will almost certainly take a lot more for their advice to be heeded – hopefully the cost is not human extinction.

It is a hard time to be a skeptic about Artificial Intelligence (A.I.) or to give it its more proper title in its current iteration: Machine Learning. What do I mean by hard time? Well, there are plenty who accuse those who do not wholly embrace A.I. tools as being modern Luddites, people against any kind of progress (that is a slanderous gross misinterpretation of the position the Luddites held, but I digress…). Just look at the stock market and all the money pouring into A.I. research say the true believers. For those who have never heard of a bubble; I have a bridge to sell you.

Then we could ask, what do I mean by skeptic? This is a surprisingly nuanced question when it comes to Machine Learning. I believe Machine Learning can do some interesting and useful things in our world. However, I do not believe that we are in any way asking the right questions or placing the right guardrails to protect those without whom these machine learning tools would not exist. I’m talking about those whose work is used to train A.I., are given no credit, and stand to suffer the most from a race to the bottom to find a machine that can do a good enough job to replace a costly human and make someone else a billionaire. I’m not a skeptic about Machine Learning. I am skeptical about people and our seemingly limitless capacity to exploit any opportunity, disguise it as something else, and then abdicate any responsibility for the consequences.

Mathematician Marcus Du Sautoy in an entertaining book, The Creativity Code: Art and Innovation in the Age of AI, acts as a proponent of Machine Learning. At the same time the author is having a self-confessed existential crisis over whether he is being put out of a job as a mathematician by A.I.  Ultimately, the book fails due to the author’s lack of an ethical framework for this discussion. Written in 2019, that’s before the days of Chat GPT kiddies, Mr. Du Sautoy uses Eva Lovelace as a jumping off point for his existential exploration of all things Machine Learning.

Eva Lovelace, born in 1815, was an English writer and mathematician and is frequently called the first computer programmer. She was also a colleague of Charles Babbage, the inventor of the Difference Engine and proposer of its follow up the Analytical Engine. It is Lovelace who is credited with the intellectual leap of understanding that the Analytical Engine was not just a calculation machine. That once a machine understood numbers it could be applied to all sorts of subjects where numbers could take the place of other values. She is also famously known for a quote seeming to pour scorn on A.I.

 “The Analytical Engine has no pretensions whatever to originate anything. It can do whatever we know how to order it to perform. It can follow analysis; but it has no power of anticipating any analytical relations or truths.”

Mr. Du Sautoy ultimately believes that Ada Lovelace was mistaken, but I feel this is more down to interpretation rather than to clinical facts. What the author does rightly acknowledge is that data is the fuel of A.I. That access to data will probably be the oil of the 21st century. Where he fails is in not grappling with the consequences of data as fuel and its ethical ramifications. “Don’t worry about all those people in the Middle East, they don’t matter considering all that oil that’s right under their feet,” the writer seems to be saying.

In the Creativity Code, there is some interesting exploration of how the use of algorithms is teaching us about how humans think about subjects and how we go about creativity. To unlock the human algorithm. It is particularly insightful to recognize that the creative leap is not to create new things, but to recognize when one of those new things may have value to others.

While Mr. Du Sautoy worries about his own profession, he is all to ready to write off whole armies of other creative people because he does not consider the work they do to have value. Whether that is to write business articles or reports, or to write background royalty free music. He fails to realize that it is this “bread and butter” creative work that allows writers and composers to work on projects more dear to their hearts. The author seems to believe that this “drudge work” is holding them back from doing more interesting things. No, it’s the money these creatives charge that has an impact on the bottom line and Machine Learning is cheaper. These creative people will not have more time for more interesting work. They will be unemployed. That the previous work of the creatives is used by machine learning as part of its training data, its fuel, is of course just salt in the wound.

Indeed, Mr. Du Sautoy blithely admits that he asked a Machine Learning tool to write a section of the book for him. In a fit of worry about plagiarism, he hunts down an almost identical article on the internet – but then keeps it in the book saying; “if I get sued for plagiarism, we can then agree that this is a bad idea.”

This book probably suffers from being a book of its time, before there was seemingly endless hype and not enough skepticism surrounding Machine learning. And it is such a shame as the book is genuinely entertaining. The section on the game Go in particular raises some interesting questions. However, the lack of ethical awareness is unforgivable and tarnishes this otherwise interesting and entertaining volume.

Blood in the Machine cover

What comes to mind when you think of the term “Luddite?”

For the more historically minded of you it might be that they were a British 19th-century grass roots movement that were opposed to, and smashed, technology due to losing their jobs at the start of the industrial revolution.

More usually, “Luddite” is used as an epithet to describe someone who refuses to embrace change, usually technological, or insists on doing things the hard way when a simple technological solution exists. Reactionary idiots who were doomed and dumb. Malcontent losers.

These are both corruptions that were deliberately foisted on the public by those who had the most to gain by discrediting the movement: the State and the “big tech” entrepreneurs of their day.

In “Blood in the Machine: The Origins of the Rebellion Against Big Tech” Brian Merchant does a most remarkable thing for a book on a historical subject. He places events from the beginning of the 1800s in context with the events of today and the same challenges we currently face when it comes to technology and work.

The first half of the book is a history of the Luddite rebellion. Its early beginnings with workers refusing to cooperate with inventors on the design of machinery that was clearly created to put them out of work, to civil disobedience and protest, and then ultimately to the very brink of civil war. While the first half of the book does occasionally highlight just how close some the challenges that 19th century weavers were facing are to modern day concerns, it is the second half of the book which focuses on the “gig economy,” A.I., and other forms of modern automation.

What becomes clear throughout the book is that the Luddites were not sheep afraid of change. This was a nuanced, decentralized movement that had clear goals and wanted to embrace technology and change, but wanted their needs and livelihoods taken into consideration. Weavers were artisans who worked for themselves, setting their own hours, and involving the whole family in their work – but on their own terms. The industrialized mills that replaced them employed mostly woman and children working long hours for low pay and producing a lower quality product that was “good enough.”

A theme that crops up both in the 19th century section and the 21st century section is the concept of the replacement of skilled workers with cheaper lower skilled workers. Mr. Merchant also spotlights the outsized role that venture capitalists play in this dynamic – financing a cheaper alternative to one industry to the point of bankruptcy and then either raising prices or lowering wages of those now forced to work for the bright and shiny new thing: Uber and Lyft I’m looking at you.

The Luddites were met with brutal resistance. Factories became fortresses and soldiers were based in every northern town. This was a time when Britain was in a deeply unpopular War with France and was losing its American colonies. Dozens of Luddites were hanged, mostly for the breaking of machinery, and those who took the Luddite oath were often transported to Australia – a life sentence at the time. All for opposing profit over people.

While not only warning of the impact that disruptive change, both in the past and the present day, the author also adds the note of caution about how people are already pushing back against the same type of change as the Luddites fought against over two centuries previously. The strikes, organizing, and protests by Uber and Lyft drivers to be considered employees rather than contract workers. The organizing at Amazon during COVID-19 over safety concerns. The Hollywood writers strike over using A.I. technology.

These are not isolated incidents.

They form a pattern of how technology is often imposed on people without thought as to its impact. That the technology that is supposed to alleviate work often just degrades it. Just the lexicon of Silicon Valley points to this: “disruption,” “move fast and break things,” “Revolutionize.” To ignore these warning signs could quite possibly doom us to repeat the mistakes of the past.

There is often, from both Hollywood and the media, a hysteria that “the robots are coming for your job.” As Brian Merchant points out; the robots are not coming for anything. It is the people who run companies and implement technologies that decide the impact they will have on peoples’ jobs, and ultimately their lives. This needs to be a discussion, separate from the also highly needed discussion on how machine learning is trained, and how venture capital distorts the business landscape. All these discussions are related, but we have real choices ahead that we will all need to make.

It is interesting to reflect on what might have been if the Luddites had won. There would still have been an industrial revolution, but perhaps the assumed antagonistic relationship stances between management and employees, whether real or perceived, might have had a very different starting point. We can’t change what happened to the Luddites, but we have all the indicators that we have an opportunity ahead of us now.

This is a book for our times and a warning about one possible future.

There are a lot of books about Twitter out there right now. That is perhaps not a surprise given (Spoiler Alert) that it has become a corporate / Silicon Valley dumpster fire.

Mr. Wagner’s account is balanced and well researched; however, one cannot feel while reading the work that it is missing the insider juicy details that make tech CEOs squirm. Perhaps because so much of Twitter’s (now X’s) dirty laundry has already been aired there is little new revelations in the work.

What” Battle of the Bird” does do is provide a clinical timeline from Twitter’s founding through to the events leading up to its purchase by Elon Musk and the unravelling of the technology institution under his stewardship. This in turn provides insights into the failure of Jack Dorcey (Twitter’s former CEO and co-founder) and Elon Musk’s failures with X.

As I talked about in my review of “Kingdom of Happiness” by Amiee Groth which referenced the failures at Zappos and the Downtown Project, both Dorsey and Musk in hindsight have had a failure of leadership due to a lack of management. It is all very well being able to persuade people to jump out of a plane, but you have to ensure that they have parachutes and know how to use them.

There is no doubt that Dorsey and Musk both do, or more appropriately have at one time, loved Twitter and what it has brought to the world. While Dorsey, according to Mr. Wagner’s book, seems to have lost interest in Twitter as a company once the reality of being a public company set in. Musk on the other hand, seems far too interested in his own press and ego once he understood the challenges Twitter faced and continues to face even after his pointless rebranding to X. It is hard to feel sorry for billionaires when the world does not work the way they want it to.

There is a theme throughout the book that perhaps Twitter can’t be a company. Dorsey in particular laments that what Twitter should be is a technology like email, that allows for the exchange of information, but that is not gatekept by any one platform. This is the kind of wishful thinking of people who have been made rich by the decisions to take their company public and have second thoughts. That they wish the world could be a different place. It can be, but only if different decisions are taken – the kind of decisions that don’t make entrepreneurs and venture capitalists rich.

Like I said, it is hard to feel sorry for billionaires when things don’t go their way.

Mr. Wagner does go into some reasonable depth as to the ethical dilemmas brought up by Donald Trump’s tweeting and his eventual banning from the platform. These are bigger issues than Twitter, but the impact on Twitter for both Dorsey and Musk were profound and still rancor the platform to this day. I’m not sure I want a committee of Twitter employees making decisions on whether what a world leader says is appropriate for public consumption, but at the same time I am positive I don’t want Elon Musk making those decisions.

As a grounding in the backstory and drama that is Twitter, now X, Battle for the Bird is a great document. Not a thrill ride or exposé, but a methodical grounding in the facts.

This is probably for the best given its subject matter and the turgid realities of Twitter’s recent past.

Perhaps this is the account we need rather than the one we might want.

Want to read a takedown of the leaders of the tech world, that calls them out for their hypocrisy and recklessness?

Of course you do.

Burn Book is, for the most part, that book. A book that at its most fundamental says “you promised us a brave new world – and what you delivered us was a more rapacious form of capitalism.”

The author, Kara Swisher, is a long-time journalist and analyst of the “tech sector” – particularly in Silicon Valley. She is also the co-founder of the Recode conference and the co-host of the Pivot podcast.

Burn Book, through the narrative of an autobiography, is her journey into the San Fransisco technology sector and her gonzo view of the events that, for better or worse, have shaped the world we currently live in – particularly its technology.

Where Burn Book really scores is in its view of characters such as Elon Musk, Bill Gates, Mark Zuckerburg, Steve Jobs, and Sergey Brin. From their early days, the beginnings of their success, through to their either refusal to accept the damage of their legacy, or the issues with how that legacy was formed, but also for some of them; their efforts to make amends. One is left with a sense of these figures riding waves that they barely understand or control. That often these figures are deeply flawed individuals who’s flaws have help lead to their success, but that long term they themselves are unrecognizable from the people they once were. Changed by wealth and power and all its trappings.

As Swisher mentions in the introduction; “move fast and break things” is in retrospect indicative of the tech scene entrepreneurs and their willingness to not think through the consequences of their actions. (Move fast and break things was an early internal Facebook slogan that was widely adopted by the tech sector).

Where the book becomes annoying is the author’s habit of “I told you so.” While this may well be true, and the whole purpose of the book is essentially to name drop, and let’s be honest that’s why we are reading it, it can become a little frustrating and seemingly self-aggrandizing. Swisher has earned the right to trumpet her vision and does have a record of putting billionaires on the spot, however, she does seem to fail to see the larger picture of the issues with this kind of innovation model.

Swisher is a self-proclaimed “believer in tech,” and this leads to the impression that she feels if only developers and tech titans were nicer then the world would be a much better place. This is quite possibly true, but one has to wonder about an industry who are happy to undermine industries and even societies, while failing to follow the basic rules that everyone else follows.

To Swisher’s credit she recognizes how close she has become to the tech sector and how that potentially impacts the objectivity of the analysis she gives. Of late she has made efforts to put distance between herself and her subjects. It would be easy to see this book as one of those efforts.

Burn Book is for the most part an enjoyable read with lots of moments to savor for those who want to see the self-proclaimed “Masters of the Universe” taken down a peg and be held to account. It does also do a pretty good job of exploring the duality of some of the complex individuals who run or formed some of the largest companies on the planet with little to no oversight. The author lauds Steve Jobs, for example, but does point out some of the flaws and cruelty that mars his legacy. It is not an in-depth analysis of all that is wrong with tools such as Facebook and the tech sector as a whole, but then it does not set out to be.

This is an autobiography and a story about being in love with an industry. The all too predictable break up, with the realization that who you were in love with is not quite the person you thought they were, is just another part of that love story.

As that, Burn Book succeeds admirably.

It seems that everywhere one turns today artificial intelligence (AI) is being added to every aspect of daily life. Whether it be the arts, education, entertainment, search, or the workplace – AI is everywhere.

Often, those of us who are distinctly dubious about the claims that are being made about the current generation of AI, more appropriately labeled machine learning, can often feel like Cassandra of  myth – fated never to be believed. At worst we are labeled as luddites, rather than as people who believe that technologies should earn their places in our lives and societies rather than being instantly adopted after being told by people hoping to get rich that they work great and everything will be fine.

Ms. Schellmann’s exhaustive exploration of AI in the workplace is pretty damning.

It catalogs how Human Resource (HR) departments have been adopting technologies that are often little understood by their users and are often working under misapprehensions as to the scientific backing of the ideas behind these tools. The fundamental problem is often one of garbage in – garbage out; a phrase that has been with us from the dawn of the computer age. For more on this I recommend the excellent “Weapons of Math Deception” by Cathy O’Neil which I reviewed here. The majority of AI tools are black boxes that we can’t look inside to see how they work. The manufacturers consider the algorithm’s inside these black boxes proprietary intellectual property.  Without being able to look inside the magic black box, it is often impossible to know whether an algorithm is biased inherently, whether it is being trained on biased data, or just plain wrong.

One of the things that comes up again and again in “The Algorithm” is AI’s, or the people that program it, inability to know the difference between correlation and causation. Just because a company’s best managers all played baseball, does not mean that baseball should be a prerequisite for being a manager – particularly if it means that an AI would overlook someone who played softball – which is essentially the same sport. When one considers the fact that men tend to play baseball, and woman tend to play softball, it is easy to see just how problematic these correlations can be.

The problems with correlation and causation are of course magnified when junk science are involved. Tones of voice, language usage, and facial expressions, are being used in virtual one-way interviews for hiring and have little to no science behind them. In one highly memorable section of the book, Ms. Schellmann speaks German to an AI tool, reading from a Wikipedia entry, which is assessing her customer service skills and quality of English. The tool rates her highly in customer service and English even though she is speaking a different language and does not even try to answer the questions being asked.

Where the book falls down a little, but probably says more about the sad state of business thinking, is on personality testing. The author seems to accept as scientifically valid that employees can be categorized as one of a few simple types. You can read my review of “The Personality Brokers” by Merve Emre here for more on this nonsense and dangerous business tool. As Ms. Schellmann rightly states in her take down of how AI handles personality testing, but could actually just apply to all personality testing; “we’d be better off categorizing by star sign.”

It is disturbing just how much AI has already invaded the hiring space in the HR offices at large companies and gives one pause as these tools become more mainstream. While it is true that it is often not the AI software itself that is the problem, but how the humans that wield such technologies choose to use them. There is also the problem of how hard it is for a human employee to challenge a decision that is made by an algorithm – which by its very nature is a secret. The developers will often say that these tools should not be the final word in hiring or firing; but the knowing wink and smile behind these statements tells us everything we need to know.

Ms. Schellmann’s work is laser focused on human resources, an area where bias has been and often is a significant problem. The idea of a tool that can be used to eliminate bias, and that companies want to use tools like this, is not inherently a bad idea – in fact it is admirable. The problem is that bias in hiring is often unconscious bias and tools that are wielded by those who are not aware of their own biases are most likely fated to continue to have these biases and therefore affect the process. In addition, it is often difficult to impossible for candidates or employees to challenge decisions by managers which they may feel have been affected by bias. How much more difficult is it when it is not a human making the decision or recommendation? A tool of which we cannot ask the most basic of questions: what were you thinking?

This is an important work for our time – hopefully one not fated to be a Cassandra.

As a society we tell ourselves stories that, while convenient, are not always, or even ever, true. In what is probably Malcom Gladwell’s best book “Outliers” (which I can’t believe I have not reviewed) the author tells of the often decade long stories, and tales of extraordinary advantage, of seemingly overnight successes. David Epstein, in “Range: Why Generalists Triumph in a Specialized World”, is also debunking one of the stories we tell ourselves – that to be really good at something, or to have great success at something, we have to have focused on that thing for a long time – if not forever.

Before I go any further a word to my veterinary and human medicine readers. In this post, and indeed in Mr. Epstein’s book, when we talk about “specialization” we are using it in the general sense as opposed to the legal (small “s” rather than capital “S”). Although, I do believe that there are lessons for students from Mr. Epstein’s excellent book. Don’t be in too much of a hurry to map out your career. It’s a good thing to try out different interests and to change your mind – you’ll be better in the long run for it.

The pressure to focus on one thing, whether it be in sports, music, or entrepreneurship is all pervasive and often has business interests behind the marketing of “hyper specialization.”

 It is a good story.

The Tiger Woods story is one that the author highlights. It is a story of the very young Tiger playing golf before he could talk and spending all day at the golf course. It is a story of winning tournament after tournament and having an unflinching goal of winning more titles than anyone else. Mr. Epstein juxtaposes the “Tiger story” with the far less well-known story of Roger Federer. Federer’s mother was a tennis coach but she refused to coach him and actively tried to dissuade him from playing tennis. A young Federer also seemed far more interested in soccer, basketball, skateboarding, handball and skiing. It was not until his teens that Federer started to gravitate towards tennis and then his goals were not lofty, but the rather quaint “meet Borris Becker” and “play at Wimbledon.”

This wide range of experience and lack of focus is the author’s main argument – that, more often than not, it is range that leads to success rather than specialization. That depth of experience of different fields matters more than depth of experience in just one. Interestingly, the evidence that Mr. Epstein quotes, rather persuasively, is that while early hyper specialization can lead to children getting a head start in that chosen area, they tend to fall into line with their peers rather than stay ahead as time goes on.

Where the book misses, for me, is that it seems to continue to fall back to specialization being a worthy goal via a route of different experiences, rather than the range of experiences being a worthy goal in itself. However, this minor quibble aside. The book makes a very strong case for experience in general and for following one’s interests. A great example is the idea to not ask kids what they want to be when they grow up, but rather to ask them what they are interested in. Our education, and in our careers, we often ask others where they are headed and penalize them for not knowing. This may be a mistake.

When I look at my career, I’ve had very specific goals at different times and while I have met some of them, I have taken some spectacular left turns that has led me to areas I would never have even considered just a few years earlier. No one is more surprised than me that I live in Las Vegas, watch a lot of hockey, and write poetry.

This is an important book for those who mentor, or lead, others. How we choose to guide – matters. We are often a deciding factor in whether to specialize in an area or to follow seemingly unconnected interests. There is value in a range of interests and experiences that benefit both the person and the employer.

A more enlightened view of the goals of mentoring will benefit everyone.

Let me tell you a secret about most business books – they are not about business. Oh yes, they claim to be about business, how to work with people, and affect change, but in reality a lot of them are not. They are often about the hard things – finance, cost control, selling, and product development, or the soft things – people management, team dynamics, and marketing. Rarely is a book about how all these things fit together, and how to grow while at the same time dealing with the realities of business day to day.

Which is why Will Guidara’s book “Unreasonable Hospitality: The Remarkable Power of Giving People More than They Expect” is so refreshing. This is part memoir of a restauranter and part business manual on blending soft and hard skills that all businesses try to do – with varied levels of success. Mr. Guidara was the general manager of a number of fantastic restaurants, including Eleven Madison Park which became the number one restaurant in the world.

For a book that talks a length about people, values, growth, and mission it is so unusual to hear the real world politick of “I’m also clear about what my job is, which is to do what’s best for the restaurant, not to do what’s best for any of you (the staff). More often than not, what’s best for the restaurant will include doing what’s best for you. But the only way I can take care of all of you as individuals is by always putting the restaurant first.” Just wow!

And that quote really sums up the problems with a lot of books on management and leadership – they are two different things people and not mutually exclusive (I can shout that louder for the hacks with the crappy memes) – we are often being asked to hold ourselves to an impossible standard. People are sometimes not the right fit, sometimes we just have to get through the shift, sometimes we are not going to be perfect. An illuminating passage deals with the idea that while it is often trotted out that employees have a language of appreciation, they may also have a language of criticism – people may need feedback in different ways depending on their personality and work history.

I love the advise to “not let things slide – those small things become personal slights.” This is often ignored because every manager today fears being labeled a micro manager. Just like I also appreciate Mr. Guidara’s works to be maniacal on cost control for 95% of your costs and then to spurge for the last 5% to make a difference to the guest experience.

There are times when this book feels like it is written by the staff from the movie “The Menu,” yet at the same time one has to appreciate what Mr. Guidara was trying to do with his business and why he was doing it. The book says, there is nothing wrong with striving for perfection, as long as perfection is not the standard – little things are always going to go wrong. That does not mean one should not try, but it means managers and leaders have to accept realities.  

It may seem extreme and over the top, and it is, but that is the whole point of being “unreasonable.” To give people more than they ever expected in a controlled manner so it can be systemized and scalable. I’ve been banging on about scalability for years, and so to read it in this book was like having to tell the author to get out of my head.

This book should be required reading for managers and leaders of any business who want to deliver a better experience for everyone – including the owner of the business. This is appreciation that businesses are businesses. They must make money and they have to be able to work when you are not there. There has to be systems in place, protocols and procedures, so that everyone knows what to do and new people can be easily trained on what to do.

Unreasonable Hospitality is what business books should be. Simon Sinek, who wrote the introduction and I have been on record for forever as having no time for, could learn a lot from this book for example.

This is where the rubber meets the road. For those who want to add to their passion, or just rekindle it, it is hard to find a better way to do so than to read this wonderful book.