Conclusion: It’s Time!

Progress is impossible without change; and those who cannot change their minds cannot change anything.

—George Bernard Shaw

Today, there is no business unaffected by digital transformation and no type of work that isn’t being changed, even if subtly, by digital tools.1 We’ve shown you why that’s the case throughout this book. We’ve also shown you why technical skills and deep interest in new technology are not enough to thrive in the digital economy. And we’ve shown that we can’t wait for someone else to deal with our digital transformation goals.

Those who will thrive in the age of data, algorithms, and AI recognize that it’s becoming less and less possible to be successful without a digital mindset.

Your Digital Mindset Shift

Each chapter in this book has helped you to reach that all-important 30 percent level of digital competence in several areas that will help you to think and act in new ways. You’ve learned how AI and machine learning algorithms work, how to interact with an intelligent technological teammate, how to establish your digital presence, how data are classified and created into data sets, what different kinds of statistical techniques can and cannot tell you about those data, how security failures happen, how blockchain creates opportunities for new transactions, how you can conduct rapid experiments and fight the bureaucracy that aims to stifle them, and how to build a culture that embraces digital change and promotes continuous learning.

You’ve learned many new skills. But as we said at the outset, having the skills to work with digital technologies is not the same thing as having a digital mindset. Remember, developing a new mindset means that you build from your new skills to see the world in a new way and to change your behavior. Your digital mindset comes when you change how you approach collaboration, computation, and change.

In reshaping your approach to collaboration, you’ve learned how AI-enabled technologies are trained to recognize text and images and classify them in certain ways so that eventually they can recognize, classify, and make predictions about data on their own. When you think about collaborating with AI-enabled machines, you can now understand how they are reaching their conclusions, even if you can’t see inside the black box to know exactly why they are reaching those conclusions. Armed with that knowledge, now you can ask how they were trained and with what data to assess particular biases the AI might possess. It will also help you to determine what level of trust you will have in AI-enabled machine recommendations, just like elite military teams do.

You know it’s better to treat AI like machines, not people. It’s easy to fall into the trap of treating AI technologies as though they are human, but as the lessons learned from using the scheduling chatbot Amy show, forgetting to treat technology like technology can pose major problems.

You’ve also learned how to maintain a digital presence effectively. One of the biggest shifts in people-to-people collaboration in the digital age is that relationships of all types (personal, work, romantic) might be predominantly digitally mediated.2 Ironically, the digital tools that allow people to work together across time and space create a new problem: psychological separation. This separation causes us to overcommunicate as a way to close that gap—posting more and more pictures on social media or deluging our colleagues with messages on Slack. But doing this has the opposite of the intended effect. Herbert Simon won the Nobel Prize in economics for describing how when confronted with more information than they can process, people attend selectively to a small subset of that information that appears relevant to them and they ignore the rest.3 In the digital age, the vicious cycle that ensues is that the more people communicate to be noticed, the more other people tune them out.

You’re now equipped with the tools to collaborate more effectively with machines and people in the digital age. In addition to treating AI like machines, not people, you also know how to cultivate your digital presence to break through the information clutter that makes it difficult for you to reach others.

If you’re like many readers of this book, you might not have had a systematic approach to computation before you started reading. But you did the hard work to embrace the challenge and now you understand how actions, text, photos, and other pieces of data are computed in ways that turn them into “things we know”—not to mention how the various analytic techniques run on those data turn them from “things we know” into “things we should do.” And you recognize that building a strong foundation in statistical reasoning is key to being an astute consumer of analytics in the digital age.

These skills in analytics and statistics pay big dividends. You can more effectively understand, keep track of, and make use of the massive troves of data that are being collected all the time. As you’re now aware, each time you send an email, text a friend or coworker, visit a web page, type in a search term, like someone’s post, comment on a picture, give someone a badge, endorse someone’s skills, make a meeting on your calendar, chat on a videoconferencing application, check in at a location, or—the list could go on and on … and on—you are leaving digital exhaust. Digital exhaust is the by-product of your activities on digital tools. That exhaust tells vendors, companies, your employer, law enforcement, or anyone else who has access to it whom you interact with and what you say and do. From those data, analysts are increasingly using advanced statistical models to make predictions about relatively benign things like what kinds of lotion you will want to buy and what color car you will want to drive to much more consequential things like whether you will quit your job or commit a crime.

Can you have confidence in these predictions? How do you incorporate them into decision-making? Should you? These are the kinds of questions you are now able to ask and answer with your new approach to computation. The specific skills that you’ve developed in statistical reasoning will help you to know if those data amassed from varied sources of digital exhaust were indeed representative and whether the conclusions derived from their analysis are valid. You’ve also learned through examples like that of UrbanSim how to think about presenting data in ways that are more persuasive to your audience. If you didn’t have a specific way of approaching computation before, you do now, and this new approach will help you to be a smart consumer and producer of data-based insights.

As you’ve been exposed to cases from companies across numerous industries, you’ve come to recognize that the digital technologies you use don’t ever act the same way twice—they perform new, learned computations on data sources that are themselves constantly changing. And because digital technologies are constantly changing, the uses to which they can be put change too. That means that organizations and the people in them are in a constant state of change.

We’ve covered how an approach to change that treats security as an evolving process is necessary for thriving in the digital age. We’ve also shown how the rapid set of changes characterizing the digital economy means that it’s hard to predict exactly what kinds of organizational forms work best or what product designs are going to be the most successful. With a digital mindset you can appreciate how experimentation helps you to prepare for and react to changes in the best way possible. And you’ve got the skills to approach change in a new way.

Most importantly, your digital mindset has helped you recognize that the formal and informal structures that define our working lives are in continuous transition. You can appreciate how the speed with which we respond to the influx of available data is a critical driver for a successful digital organization. For some organizations, the most suitable structure will be agile teams that can be fluidly formed and easily disbanded once a target is met.

To facilitate continuous change, your digital mindset will help you recognize how crucial it is to spend time working on the implementation of digital tools to make sure they’re used in ways that align with your major goals. You also now have a good understanding of how to determine the best way to train employees at scale. What is clear is that digital training must be a continuous process. Employees have to continuously develop their skills in the digital age and so do their bosses. This process of never-ending learning differs from simply acquiring a new skill for one’s job each year; the jobs themselves are constantly changing, and employees must be able to move along with these changes in order to stay productively employable. Your digital mindset allows you to approach change not as something to achieve and then forget, but as a constant process requiring planning, intervention, and a lot of care.

Your Superpower

You have really ramped up your skills even if you didn’t realize it as you were going along. And now, by doing the difficult work of learning the skills that have enabled you to shift your approaches to collaboration, computation, and change, you’re able to see, think, and act in more nuanced and agile ways in this era of rapid change.

Your digital mindset is something of a superpower. You can now unlock opportunities you may never have imagined. This power is so much more than knowing how to code and how to do data analytics. You will no longer be shy about diving into conversations about technical topics, and you have a technical language that creates entirely new possibilities.

Perhaps the most important thing about your digital mindset is that it means you don’t have to worry about finding your place in the digital future. You’ll be helping to blaze pathways into that future that create value for you and those around you. Maybe you won’t go to Kenya to plant potatoes, but we’ve seen time and again how a digital mindset not only sets up people for success where they are but also gives them new places to go.

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