The objective of this book appears to try to help the reader become tech-literate and to better equipment them to navigate our digital future intelligently.
Another focus is on helping the Small and Medium Businesses (SMB) better understand technology to ensure they apply it appropriately increasing their revenues.
The author, John Meada, says “We already live in a world where we unlock our phones hundreds of times a day to refresh our emails, send text messages, and check social media. Even so, do we really understand how the programs we use work?”
He goes on to say a “Lack of in-depth knowledge about computers might not seem so significant right now. After all, we’re able to use apps and software in our everyday lives without ever considering what nesting or recursion are. But what happens when technology advances so much that it leaves the less computer-literate in the dust?.” He continues, “Understanding the digital world has never been more important for the average user.”
Personally, I think the lack of how technology really works is at an all-time high.
In my experience, today’s college or high school graduate will tell you that they know technology. When asked during an interview, on a scale of 1 to 10 where a 10 is having a high technology knowledge level they will say a 9 or 10 a majority of time. The problem is they base that not on having a software development, application or system engineering understanding but they base their answer because they understand how to use their phone with a social media focus. That is not the same; one is simple and lacks deep understanding of the technologies behind the scenes. What’s troubling is they lack an interest in the core infrastructures and applications that allow them to use their phones easily. It’s taken 20 years of refinement by technology companies to build out and reinvent those technologies to get them to the ease of use we enjoy today.
No one seems to want to dig deeper into the inner workings of how things work which gives them a superficial understanding of security risks and potential ways to utilize technology in more creative ways. This is where I agree with John Meada. This superficial understanding combined with a cursory technology understanding can lead to a “I don’t have time or care how things work” attitude. Therefore, the institutional knowledge of how things really work retires at alarming rate. Not everything is going to be understood by going to the web and watching a video or reading a quick article. The web with its many benefits has help create a level of “I’m an expert in something with a few clicks of a mouse.”
This book discusses how technology opens up enormous possibilities for business owners and entrepreneurs. This is very true but Small and Medium Businesses (SMBs) don’t really understand the technologies either. How to select the right technologies that seamlessly integrate into their workflow and improve their revenues while eliminating costs. The author discusses the low costs associated with getting a digital product off the ground. He goes on to say “there might never be a better time to form a start-up – but only if you know how to speak machine.”
In this book, John Meada discusses;
- how a computer program can be like a Russian nesting doll;
- when the words lean and agile have nothing to do with physical fitness; and
- how computers can be racist.
The major topics addressed are;
- Machines are good at repeating tasks endlessly.
- Computers think exponentially.
- Machines are quickly growing more and more lifelike.
- Machines have changed the way businesses manufacture and sell products.
- Digital consumption allows companies to get up-close-and-personal with data – for better or for worse.
- There’s a diversity problem in the tech world, and machines can perpetuate it.
- Machines process data, and data alone can’t always paint a complete picture.
Machines are good at repeating tasks endlessly.
Computers are excellent at performing repetitive tasks. This means they don’t get tired or bored like human employees do.
My concern at parts of the book is that the author attempts to provides an explanations of computer technology but it falls short because it’s nothing more than a cursory high-level description of a very complex topic.
He uses a gym with a track analog where the “track” is a computer program which consists of lines of code. The computer code is based on if-then logic, where if one condition is met, another action follows.
The author does a nice job of explaining loops or recursion in code. He tried to draw on his personal childhood experiences writing a simple program in an attempt to help the Small Business owner see the value and benefit of using technology in ways they can understand. I love that he said “There’s one thing that a computer can do better than any human, animal, or machine in the real world: repetition.”
Computers think exponentially.
The author says; “While we humans don’t usually view the world in terms of exponential increases or decreases, this is a totally ordinary and natural way of thinking for computers. They do this through nesting, in which loops are placed inside other loops.”
He uses the following to illustrate this concept… “To envision this, think of a single unit of time, like one year. A year is made up of several nested loops – 12 months with 30 days in each month, with 24 hours in one day, and so on. In the same way, code dealing with smaller details can be nested inside code dealing with larger details – and there’s no limit to how large or small you can go.”
My concern is that this statement makes you feel like you’re headed down a rabbit hole and the Small Business owner most likely will lose interest in reading this book further.
He goes on to say;
“If one computer’s ability to examine infinitely large and small scales isn’t impressive enough, guess what happens when groups of computers communicate with one another? Right – their collective computing power is increased exponentially. If one computer can’t handle a task, it just outsources it to another machine or group of machines to which it’s connected.”
It’s not that simple, if the application is written in such a way to decompose its code into variant lines of decent then multiple computers can be used to get more work done faster than single threaded programming architectures. But we’re going to deep into the logic architecture for the SMB business owner to understand and how to turn that thinking into their money-making model.
In this section he also covers a very interesting and important topic about cloud computing. He discusses how “companies like Google and Microsoft control clouds consisting of hundreds of thousands to millions of computers. These clouds can run loops in any dimension and ask each other for help millions of times per second – and all of our devices are connected to them. In a sense, each individual computer is a tentacle invisibly connected to the giant, powerful octopus of the cloud.”
I wish he would have touched on the cyber security issues of using cloud-based applications of and putting all your critical data in the cloud. Yes, it’s easier and provides great cost savings but at what cost. No mention of cost benefit analysis with a concern for security is addressed.
Machines are quickly growing more and more lifelike.
The author addresses that “some AIs have already been able to imitate humans convincingly. Dr. Joseph Weizenbaum’s famous computer program from the 1960s, Eliza, could carry on a conversation in English. Eliza’s responses were coded to follow a simple set of if-then rules. For example, if you mentioned something about a relative, like your mother, Eliza would respond, “Tell me more about your mother.” These responses mimicked real human conversation realistically enough that Weizenbaum’s students thought Eliza was an actual person.”
The author touches briefly on the subject of deep learning. This is a type of machine learning in which computers are taught to “think” by repeatedly observing a behavior and then figuring out how to execute it on their own. Now, AI can beat human grandmasters at chess just by watching them play.
The author asks “So does this mean artificial intelligence will eventually exceed human intelligence?” This theoretical point in time, is known as the Singularity. However, if you understand that computers think and grow exponentially, it starts to seem more realistic. Computer experts think so too – inventor Ray Kurzweil has founded Silicon Valley’s Singularity University, where he and others study this potential future.
Based on our knowledge that computers never tire and work to execute their tasks more effectively than humans we can surmise what will happen as AI becomes indistinguishable from human intelligence.
the author suggests that “While humans sometimes read each other’s emotions incorrectly, AI won’t – which means they’ll be highly likable. And they won’t just be able to beat us at games like chess – they’ll be beating us at almost everything. Soon, machine-speaking humans will have the power to design and maintain the AI destined to replace us.”
Machines have changed the way businesses manufacture and sell products.
In the days of digital products, tech companies are able to do just that.
Back when companies only sold physical goods, the goal was to create as perfect a product as possible before shipping it to any customers. But with hardly any associated manufacturing costs, tech companies are able to release different variations of a product before deciding on the final version. This is called A/B testing, and it lets companies see which one customers respond to best.
The author provides the following example to illustrate this point, “President Obama’s fundraising team carried out a successful example of an A/B test during his 2012 campaign. The team selected random groups of people from their mailing list to test the effects of different email subject lines, with the goal of determining the most profitable one to send to the rest of the list. The winner? “I will be outspent,” which ultimately generated over $2 million more in revenue than another variant.””
But while minimal manufacturing costs make this kind of testing possible, they also mean that old models of a product quickly become obsolete. This has given rise to the lean or agile business model, where products are released in a bare-bones state, or at least somewhat incomplete, and then improved later. Lean refers to keeping the product as simple as possible, while agile refers to a company being able to respond to customers’ needs quickly.
Thanks to the lean and agile model combined with information from A/B testing, companies can send out incremental updates to their products over time. While these allow your device to be constantly improved, they can also give companies unfair leverage. Consider Apple, which regularly releases software updates that get downloaded while you sleep. That’s very convenient – until the latest version causes your device to run sluggishly, forcing you to buy an expensive new model with a faster processor.
Digital consumption allows companies to get up-close-and-personal with your data – for better or for worse.
Open up Netflix or any other video-streaming service, and you’ll be greeted with a homepage full of shows and movies you’ve already watched, plus recommendations for what to check out next. Sometimes, these recommendations are spot on, while other times, they’re way off. That’s because the algorithms that predict what you’ll like and dislike aren’t perfect. But that could soon change, as companies are able to collect more and more data about your specific preferences, background, and beliefs.
In the earlier days of tech, customers purchased CD-ROMs containing finished pieces of software. But now, software and other digital products are released before they’re fully complete, and their content is constantly shifting based on consumer feedback. So instead, customers pay a few dollars per month for regular access to a service instead of making an expensive one-time purchase. For companies, this means customers need to be pleased with their product repeatedly over time. And the best way to do that is to learn all about them, so the companies know exactly what the consumers really want.
Having a company know everything about you sounds pretty scary. But keep the benefits in mind. It’s this two-way communication between a customer’s data and a company that allows Netflix to recommend new programs, helping you discover more things you’ll enjoy, or lets Gmail learn your writing style and offer automated email responses just for you.
In exchange, every action you take on a computer can be converted into data and sent back to someone, somewhere in the cloud. If you receive a pop-up survey, for example, your actual answers to the questions might not be the most important information for the survey sender. Perhaps your cursor lingered over an image for a particularly long time, which indicates you were interested in it. The company can then advertise to you based on what it thinks you like.
At this point, you may be thinking, “how do I stop companies from learning all this stuff?” But there’s no way to turn off the two-way communication completely, and currently there aren’t many legal regulations for how companies can collect and use your data.
The first real step forward was the European Union’s 2018 General Data Protection Regulation (GDPR), which forces companies to acknowledge the fact that they’re collecting your data and ask for your consent. But the United States still has no similar legislation. More policymakers will need to learn to speak machine if we’re to avoid exploitation of our data in the future. The problem I see is that U.S. politicians and government regulators have a cursory understanding of the technologies and make irrational emotional decisions on how to regulate technologies companies. They think they’re making it better or safer for consumers to navigate the digital highway but they’re actually making it in some instances more dangerous. One could ask are they helping or hurting good companies by their desire to regulate everything.
There’s a diversity problem in the tech world, and machines can perpetuate it.
When you think of famous computer scientists, Alan Turing probably comes to mind. The author reminds us “that many of the first computer programmers were women.”
Unfortunately, many hardworking women have been written out of the history of computing, and these days, they’re being excluded from the modern tech industry. Right now, only 21 percent of people employed in the U.S. tech industry are women, even though the overall percentage of women in the United States is around 50 percent.
So, the author asks “So what could explain this gap? For one, the most highly cited reason for leaving the tech industry is harassment. Culture is still an issue and company leaders need to address this issue straight with more than just policy statements.
Machines process data, and data alone can’t always paint a complete picture.
We know that machines can run without ever tiring, far beyond a pace we humans can. And since they’re all connected to each other they possess enormous computing power. So, the general thinking is that as that power grows, and their intelligence surpasses ours, where does that leave us?
Fortunately, there are plenty of ways in which we’re still superior to machines. A particularly important one is our ability to interpret qualitative data, whereas machines can only collect quantitative data.
So, don’t be too worried about becoming obsolete — yet. With all their capabilities, machines are still imperfect – just like us.
Speaking machine involves understanding the fundamental differences between the ways computers and humans think. Machines think in logical loops, repeating tasks endlessly until stopped by a command. And they process quantitative, rather than qualitative data, which they can’t interpret in the same way humans can, at least not today. If more people learn these differences, we can confidently face a future where computers play an even more dominant role in our lives and where no one will get left behind.
Actionable advice for SMB Businesses owners and for their employees.
The author recommends disabling third-party cookies. This is a threat to your privacy.
The author goes on to say “You’re probably use to seeing a message asking you to “accept cookies” when you visit a website for the first time. Likely, you immediately click “accept,” which isn’t a bad thing – cookies help websites provide a better experience for you by learning your specific preferences.”
“However, these cookies contain your personal data, and if you’re in the United States, they can be sold without your consent to other websites you’ve never visited. To take back control of whom you allow to collect your data, go to your browser settings, and disable third-party cookies.”
Hope you enjoyed this book review. Tell me what you think, feedback is appreciated!