Reboot Yourself With a Robot

When I was growing up, my favorite television program on Saturday morning was The Jetsons, a futuristic cartoon sitcom that promised the exciting life of tomorrow. The dad, George Jetson, is awakened every morning by an automatic process that slides him out of bed, shuffles him into the shower, and gets him ready for work while he slowly wakes up. Strangely, he still works in an office, although he commutes in a flying car and stays in touch with a videophone. Meanwhile, back at home, “Jane, his wife” is keeping the house in order (no woman’s liberation was foreseen for her), with the help of a quirky AI named Rosie, who does all the housework and gets a little sassy at times. Little Jethro’s best friend is Astro, an AI fashioned to look and act like a dog (except he could talk—he sounded a lot like another cartoon dog, Scooby Doo). Astro is about the only one in the family who gets any exercise, albeit he’s always running in place on his little treadmill. Judy, a typical teenager, loves to shop, which oddly is done in traditional stores. Online shopping isn’t dreamed of in this future. She loves to come back with arms full of packages. But the family home is equipped with an automated sidewalk, so no one has to walk very far to get anywhere. Travel to the rest of the solar system is common, the way we visit different cities today.

Two years later, a new TV program, Lost in Space, provided a different view of the future with B-9, a nonhumanoid robot with a passion for warning young Will Robinson of danger as the family traveled through space.

The cult sci-fi show Doctor Who featured many different robots, and most of them were bent on destroying the human race and taking over the Earth. But not K-9, the Doctor’s robot dog. He first appeared in 1977 and made several appearances when the show returned 10 years later. K-9 was completely devoted to the Doctor, whom he called “master,” finally sacrificing himself to save the Doctor and the rest of the world. As a reward, the 10th Doctor rebuilt K-9 (an advantage that robots have over us fragile humans) and left him with Sarah Jane, one of his companions, as a present. (Perhaps the most intriguing breakup gift ever.) Another robot served as the Doctor’s spaceship and home. The TARDIS (time and relative dimensions in space) could fly itself, travel forward and backward in time, transform itself into any shape, and expand into an infinite number of rooms “on the inside.” The TARDIS also developed deep romantic feelings for the Doctor and was jealous of his human companions.

Fast-forward to 2001, when Star Trek: Enterprise introduced us to Lieutenant Commander Data, a super-intelligent AI who is a member of the crew in 2151. Data also had an evil twin, Lore, who learned his evil ways by studying humans. Data had to save the humans many times and was sometimes a bit smug and condescending about his superior talents. But deep down, he desperately wanted to be more human, trying to fall in love, tell jokes, and feel empathy for others. Some would say he is the most authentically human member of the crew.

In 2016, HBO launched the series Westworld, based on the film by the same name. In this dystopian future, a high-tech amusement park is populated by robotic “hosts” who are programmed to satisfy the deepest fantasies of their human “guests.” When some of the robots begin to develop consciousness, all hell breaks loose.

In pre-COVID 2020, I was driving back home from a real-life meeting in downtown Phoenix when I was suddenly surrounded by a small fleet of all-white economy cars. My first impression was that they were rentals, being returned from somewhere. But the cars were somehow “behaving” differently. Their movements weren’t erratic or dangerous, but I noticed a precision in their movements as a group, as though they were performing a water ballet on the highway at precisely 55 miles an hour. It became clear that they were trying to get me out of the center of their little dance, so I obliged by slowing down. As the last car sped past me, I noticed the bumper sticker on the back. I had been surrounded by a test fleet of self-driving cars. Humans were on board, of course, as a fail-safe, but the movements I witnessed were the result of driving algorithms meant to promote public safety.

We’re still waiting for our flying cars, but we have videophones and portable computers in the palms of our hands. There are also robots among us, even if we don’t know it.

Are You a Robot or a Bot?

You’ll often find the terms robot, bot, and AI used interchangeably, even in this book. While it is often overlooked in the popular press, there actually is a difference. I like the definition provided by CodeBots.com (Tansey 2017): “Our definition of robots and bots is that they are both programmable machines that can automatically execute actions. There are those with bodies (robots) and those that are simply programs (bots).”

For the purposes of this book, it often doesn’t matter if the programmable machine has a body or not. My focus is on what these machines can do to enhance learning and performance. Thus, I tend to use bot, but will occasionally use robot, if that term makes more sense in context.

Will You Be Replaced by a Robot?

Will you be replaced by a robot? I’d like to assure you that the answer is “no,” but the truthful answer is “maybe.” Oxford economist Carl Benedikt Frey predicts that 47 percent of jobs could be replaced by automation in the near future (Frey and Osborne 2013). There is even a companion website to Frey’s paper that lets you submit your job to see if the paper makes any prediction about your chances of being replaced by a robot. However, based on trends from the past few years, it’s far more likely that you will soon have robot employees and colleagues who expand and transform your work life, rather than replacing you altogether. This is because the state of AI, even at its most advanced, still needs human direction to be most effective. And that’s good news for us “biological machines” (LTEN 2019).

For example, in the healthcare industry, some providers are testing robots that can conduct a conversation with elderly or other at-risk patients, to remind them to take their medication, offer to check their blood pressure, recommend exercise and diet tips, and other basic services. Other applications have proven that AIs can identify cancer by reviewing a patient’s scan faster and more accurately than a trained human. This application frees the humans for more nuanced analysis that can’t be resolved by a machine.

What would you like to do faster or more accurately, or get out of doing at all? Think about all the things you do in your job and make a list of tasks that are repetitive, routine, or require minimal creativity to accomplish. To give you some ideas, here’s my list:

• reading and responding to most emails (not yours, of course!)

• managing my calendar

• proofreading content

• searching for information

• managing my to-do list

• preparing and sending invoices

• following up on past-due payments (again, not yours, of course!)

• keeping track of business and personal financial records

• updating my website and posting on social media.

Depending on your role, your list may be different, but I’m willing to bet that you can identify at least a few tasks that could be—and perhaps should be—done by someone else. But in today’s world there is really no “someone else” for most of us. Many L&D professionals are sole contributors in their organization. If they manage a team, those people have their own work to do. Productivity experts are fond of telling us to delegate whenever possible, but for most of us, this simply isn’t an option. When we look around us, there is no one to delegate the work to.

What if you could outsource some of those lower-value tasks? What would that look like for you?

Learning technology expert JD Dillon suggests several applications for AI-enabled talent development, including a few opportunities for automation that might surprise you. I’ve expanded on his list and added a few of my own (Dillon 2020).

Hire an Assistant

You may not be able to hire your own personal assistant, but you can “hire” a digital personal assistant right now. Your new co-worker will probably require some training, but with some effort and patience, you’ll soon be delegating more simple tasks to your assistant, such as relying on it to tell you what deliverables are due today and set your schedule. Apple users have learned to rely on Siri for everything from reading their email, to taking dictation, to even making dinner reservations. The simple voice-activated interface makes it easy to communicate with virtual assistants and can help you free up some time for more complex tasks—plus keep you from forgetting your mother-in-law’s birthday. (If you “hire” an Alexa for this purpose, she’ll also be more than happy to shop for you and order Mom the perfect gift on Amazon. She’ll even have it shipped and gift-wrapped, with a lovely card enclosed.) Additional tasks your administrative assistant can do for you today include:

• Draft meeting agendas based on content in an email.

• Proofread your emails and documents.

• Schedule meetings across multiple calendars and send invitations at times when all parties are available.

• Summarize and read the news to you.

• Read your email to you and take dictation to respond.

• Remind you of important tasks and deadlines.

• Tell you what movies are appearing at a theater near you and buy tickets.

• Track your exercise and sleep patterns and recommend healthier habits.

• Tell you a joke, play your favorite music, or sing you a song to brighten your day.

• Greet you with a cheery “Good morning” at the start of every day and turn on the coffee machine.

Sound too good to be true? There are certainly some challenges to working with a digital assistant, so be prepared for the unexpected. I have a friend who is still trying to get Siri to distinguish between his brother and his brother-in-law, both named Bob. If he doesn’t carefully phrase his commands, he ends up “Siri dialing” the wrong person. My editor has a Google smart speaker. One day, she was watching a YouTube video of Patrick Mahomes showing off his high-tech “smart home.” When the quarterback said “Hey, Google,” my editor’s machine responded.

Like any new “employee,” your assistant will need to be trained if you want to enjoy a productive relationship with it.

If you haven’t experimented with a digital assistant, this could be an excellent way to dip your toe into the AI experience that many of your learners already enjoy. If you own a smartphone for personal or professional use, you already hold one of these digital assistants in your hand, even if you’ve never asked it to do anything. I encourage you to experiment with ways to become more productive and efficient in your daily routine.

Once you start using your digital assistant, it’s not much of a leap to imagine practice applications that will support learning and performance support. One of my clients uses the proprietary software on their employees’ company phones to provide just-in-time answers to questions on procedures, company policy, technical processes, and more. It’s like having a coach standing right by you while you do your job. It can reduce errors, reduce downtime, and improve productivity.

Most of your learners likely already have smartphones and other devices that can access a digital assistant. Whether this is a company-provided phone or you work in a BYOD (bring your own device) environment, you may be able to use these digital assistant programs to deliver short, in-the-moment learning activities such as:

• reminders for class schedules and due dates for prework, homework, or assessments

• review questions to reinforce content from training

• access to job aids and other performance support documents on the job

• fun facts or tips to keep things interesting.

Sound like something you’d like to try? Selecting the right digital assistant for you is beyond the scope of this book. (Besides, the details would probably change by our date of publication.) Your choice for your digital assistant will probably depend on which platform is most available and comfortable for you. Here’s a list of some popular options.

Platform	Assistant
Apple	Siri
Android	Google Now
Microsoft	Cortana
Facebook Messenger	Facebook M
Amazon Echo	Alexa

Hire a Junior Writer

You may think that only a human can write compelling, accurate content for training, but robot writers have been employed by news outlets and online marketing companies for years. In fact, there’s a good chance that you’ve read news stories written without any human intervention and you didn’t even know it. Here are a few of the major outlets that regularly use AI programs to produce at least some of their content: Forbes, the Washington Post, the Los Angeles Times, and the Associated Press. It’s not as simple as just writing a program and unleashing it to produce tomorrow’s headlines, however. “The work of journalism is creative, it’s about curiosity, it’s about storytelling, it’s about digging and holding governments accountable, it’s critical thinking, it’s judgment—and that is where we want our journalists spending their energy,” said Lisa Gibbs, the director of news partnerships for the AP (Martin 2019). In most cases, AI can be used in a more supportive role, like a junior reporter who is learning the ropes from a more experienced news writer. Journalists can be freed from the necessary but sometimes time-consuming tasks of gathering and interpreting data, identifying trends, validating sources, and locating contact information for subject matter experts (SMEs). As Gibbs says, the use of AI frees human journalists to do what they do best, by letting AI do what it does best. The two skill sets, at least today, are quite different.

What would it be like to have an AI write your learning content? Setting these concerns aside for a moment, let’s think of all the content your organization puts out on a daily basis. The Internet is growing by a staggering amount every day, and your company intranet is just a smaller example of the same phenomenon. A content development bot could help you by:

• delivering a daily report on key organizational metrics so you can monitor trends and make recommendations to stakeholders

• identifying top performers and strugglers on the job, so you can deliver a learning solution that keeps top performers from getting bored and helps low performers improve their skills in real time

• creating a first-pass storyboard based on SME-provided content so you can get some initial responses before you invest too much time perfecting a design that must be approved by others

• drafting one-page product guides from larger documents like manuals and whitepapers

• populating presentation slides from a script, news article, or blog post for your review

• inserting or recommending images for a presentation based on keywords in the content

• using a template to design a webpage or convert classroom content into self-paced e-learning

• identifying broken links and page issues on your intranet and e-learning pages, attempting to fix them, and letting you know which ones need your personal attention

• automatically updating learning content for routine items, such as product changes, that can be identified by constantly monitoring all corporate communication

• running reports on learner activity, satisfaction, performance, and other key performance indicators and producing attractive dashboards or spreadsheets to present the data to your stakeholders.

Translate Your Training Almost Instantly

If you’re working in a global organization, or your learners come to you speaking and reading a variety of different languages, chances are you’re already outsourcing translation services to make your content more relevant and accessible to your learning audience. In today’s global and digital workplace, where learners can be based anywhere, the written and spoken language of training and education has grown increasingly complex. Training content may be created by human content developers on one side of the globe and consumed by learners all over the world. Online schools and universities face the same challenge—how to efficiently and effectively translate content without changing its meaning. This means that the translation program must not only perform a literal translation from the words of one language to another; it must be able to recognize and adjust for cultural differences, local references, idiom, and slang, which can change the way a learner interprets what they read or hear.

As anyone who has watched a foreign film with captions will attest, translating from one language to another is not a simple word-for-word replacement. While babies learn their native language with relative ease, today’s AI is still challenged by nuances that come easily to the human brain. For example, an AI might not be able to parse the difference between read (present tense) and read (past tense) and many other meanings that are dependent on context.

The challenge for determining how well AI is doing with human language is that the humans are serving as the judges—and we keep changing the rules. In his book, The Measure of All Minds: Evaluating Natural and Artificial Intelligence (2017), Dr. José Hernández-Orallo writes, “AI measurement suffers from a moving-target phenomenon.” In other words, as soon as AI gets good at doing something, we humans raise the bar and no longer find the previous level of achievement interesting. Thus, it never seems to get quite good enough, because we humans know that the effort was generated by a machine. Hernández-Orallo proposes that a better means of measurement might be to flip the equation: to measure the performance of an AI by the effort required by the human to detect it. Using this yardstick, one only has to play around with Google Translate to see two different answers to the same question. Although AI has come a long way in the ability to translate human speech or text, it still has a long way to go.

One of the most interesting developments to me is that most AIs seem to do better learning on their own; the less we tell them in advance, the better and faster they seem to learn. In this respect, the two neural networks (human versus machine) are quite similar. Learning through free-flowing experience is often more effective and creates a deeper and broader “understanding” than teaching through lecture or hard-programming.

If you are using a translation service today that is powered by human translators, chances are they are leveraging artificial intelligence for more basic applications, with a human reviewer who can add the nuance and correct anything that doesn’t quite hit the right note for a human audience. Each time the human reviewer enters a correction, the program learns from this experience, so these targeted applications can only get better.

As long as you get a quality result, to me there is really no reason to debate whether the result is produced completely by the algorithm, or whether it represents a collaboration between human and machine.

Translation is a perfect example of how targeted AIs have already entered the workforce as virtual colleagues and assistants, rather than competitors for our jobs. Just as a different generation had to learn how to use computers and the Internet to do their work in new ways, today’s learning managers need to plan for how they can incorporate a new array of helpers to make life easier and drive performance—for their learners and for themselves.

Curate Your Content

Curation has become a popular topic in learning and development circles. It’s a term borrowed from the art world, where the role of a curator is to collect works that support a gallery’s theme or mission and then present these works in meaningful ways to the public. The role of the curator in L&D is similar. We package content from a wide variety of sources and organize it in a way that makes it more accessible to the learner. By employing artificial intelligence, you can create an interface that tailors the recommendation to each learner, based on individual needs, requirements, and interests. The sources for this information may include a learning management system (LMS), YouTube, Vimeo, online third-party courses from providers like Coursera or LinkedIn Learning, books, magazines, blogs, and other sources. Many companies are looking at curation as a powerful way to leverage existing content in engaging new ways. With an intelligent curation engine, you can delegate the difficult and sometimes tedious work of going through thousands of digital artifacts to find the content that will be most valuable to your learning audience. It would take an army of humans to do this, and it likely wouldn’t be as fast or as thorough as a well-designed AI. We’ll talk more about curation solutions in chapter 4.

Manage Course Registration and Payment

If you provide courses to a large number of people, the registration process could quickly become a nightmare. And if you charge for those courses, you have to factor in the complexity of conducting e-commerce securely. Course registration, payment collection, fulfillment, and reporting can all be handled by a number of programs that are available today. You may also find that e-commerce is an option that is available on your LMS. Even if you never intend to charge for your courses, registration and delivery can be a logistical challenge. This might be a perfect opportunity to implement some simple and targeted intelligence to do the work for you.

Get Ready for the Digital Employee

These examples of targeted AI demonstrate that smart machines are already entering the workforce as virtual colleagues and assistants, rather than competitors for our jobs. As a talent development professional, you have the opportunity to make yourself more productive and efficient by using a variety of these bots, and you can put yourself in a position to lead the way in the implementation and development of these tools in the workplace.

For many professions, artificial intelligence will introduce much-needed help in the form of smart robots and programs that support or augment the human side of work. For example, IT professionals who augment their surveillance with AI can gain 20 times more effective attack-surveillance coverage than traditional methods, allowing them to find and remedy critical security vulnerabilities 40 percent faster (Ciccarelli 2020).

In many countries, including the U.S., 2020 began with a serious labor shortage. Employers struggled to fill jobs due to low single-digit unemployment and other factors (Lowrey 2018). However, in response to the COVID-19 pandemic and the resulting downturn in the global economy, many companies were suddenly unable to maintain their operating expenses, laying off large portions of their workforce or cutting hours and wages. Consulting powerhouse McKinsey & Company warns about the post-pandemic “next normal,” a period during which nearly every business will be disrupted by the necessity of responding to and recovering from COVID-19, resulting in a major shift in how we conduct business at all levels. As learning professionals, we must arm ourselves with the agility and business acumen to be ready to support a number of possible “nexts,” including:

• An increased focus on delivering education via distance learning

• An increased reliance on automation in the form of drones and robots to deliver basic goods and services

• A new way to provide healthcare, which may include automated solutions, such as tracking apps, chatbots, and virtual doctor appointments

In March 2020, McKinsey analysts Kevin Sneader and Shubham Singhal wrote:

It is increasingly clear our era will be defined by a fundamental schism: the period before COVID-19 and the new normal that will emerge in the post-viral era: the “next normal.” In this unprecedented new reality, we will witness a dramatic restructuring of the economic and social order in which business and society have traditionally operated. … More simply put, it’s our turn to answer a question that many of us once asked of our grandparents: What did you do during the war?

The good news for us humans is that we’re supremely prepared for this challenge through thousands of years of evolution.

André Vermeulen is one of the pioneers in the application of brain science to enhance learning and development. His company, Neuro-Link, is a boutique consultancy specializing in the neuroscience of performance optimization and neuro-agility. Vermeulen recently reminded me that learning is “the DNA of the mind. It is the key to not only mankind’s survival, but also to our competitiveness, employability, prosperity, and success. It is therefore essential to optimize all the brain-based elements that will influence the ease, speed, and flexibility with which we learn, think, and process information.” You can learn more about his ideas on his website, provided in the references.

Our brain is the most complex single object known to humankind and it is constantly rewiring itself in response to new information. We are constantly learning; we simply can’t help ourselves. Learning is our superpower. By teaching learners how to fine-tune their learning skills, we can help them keep up with the accelerating pace of change, integrate new concepts and processes into their daily routines, and develop new skills to help them continue to advance in their careers. Those same skills will enable all of us, as learning professionals, to succeed and thrive as well.

Throughout history, the development of new technologies has turned complex trades into routine tasks. When the automobile was first introduced, most people believed that you needed a skilled driver to operate and maintain it. Now we consider that process so routine that learning to drive is a standard rite of passage for most teenagers today, and we’re already outsourcing the task to digital employees in the form of “self-driving cars.” According to a recent study by LinkedIn Learning, the introduction of AI into the workplace will require almost everyone to acquire new skills. What we once called “soft skills” or “people skills” make the top of the list, only now these skills will include ways to collaborate with machines (Berger 2019).

Beware the Uncanny Valley

You may have noticed that I sometimes refer to artificial intelligence applications with the personal pronouns he and she. That’s because it’s natural for us to assign human characteristics to the apparent “behavior” of animals and machines. Our brains are prewired for social interaction. It’s an evolutionary response to our earlier environments, which were so dangerous that banding together was the only way for the species to survive. This urge is so compelling that we look for social connections where they may not really exist. Having close relationships with our pets is not such a stretch, especially in light of increasing evidence that their brains are structured much like ours and that they have an inner life that has many cognitive and emotional correlates to our own.

What may be more surprising to you is that we can also form deep and complex attachments with machines. In fact, we’ve been doing it for centuries. Have you ever given your car a name? Or told a friend that your P.C., phone, golf club, or other inanimate object doesn’t “like” you today? It could be just a colorful way of expressing yourself, but it is often something more. Our machines are psychological and physical extensions of ourselves. They take us places we couldn’t go on our own, make us safer and more dangerous, and give us new ways to engage with the world and ourselves. In the movie Castaway, Tom Hanks befriends a soccer ball that has washed up on the beach along with the rest of the debris from his wrecked plane. The longer he stays alone on the island, the more he depends on his friendship with “Wilson” to keep him sane, or at least get him through another lonely day.

Humans have been falling in love with technology since the first time someone picked up a rock and reimagined it as a tool. That person soon discovered that a rock can be a lifesaving device to build a home or prepare food, or a weapon to harm another being. That dichotomy has been the story of our conflicted relationship with our machines ever since.

While investing our machines with personality might be fun, it has a darker side. We can sometimes become overly dependent on them, replacing genuine social contact with the appearance of a social world on our devices. As natural language processing continues to improve, our AIs will only become more and more like people, making it easier to interact with their powerful capabilities and creating more potential for confusing our all-too-human brains.

An interesting phenomenon we’ll likely encounter is called the uncanny valley. AI pioneer Masahiro Mori demonstrated that as robots (AIs in physical form) become more and more human in appearance, we are at first engaged, even charmed. But this pleasant reaction continues only as long as we are able to differentiate the experience from a human-to-human interaction. At some point, the appearance, voice, and behavior can cross a line, appearing almost too human. As IEEE Spectrum author Rina Diane Caballar (2019) puts it, “There’s something about it being almost human but not quite that can make people uneasy.” Mashiro’s theory further posits that at some point the robot may become so humanlike that our revulsion evaporates and we begin to enjoy the interaction again, forgetting that our companion is, in fact, artificial.

Think about how you would react if your cat or dog suddenly started talking to you in perfect sentences. It might sound pretty cool, but it would probably be truly frightening if it happened tomorrow.

Experiencing the Uncanny Valley

Trish O’Connor, the owner of Epiclesis Consulting and its new publishing arm, Epiclesis Press (www.EpiclesisPress.com), is developing a new interactive journaling aid that brings together her computer programming skills, spirituality, and principles from the art of magic in what she calls “cyberillusionism.” Intended as a tool for spiritual reflection such as dream analysis, her algorithms create the eerie illusion of a conversation with a spiritual director named “Chris.”

I wanted to try it out, so here is an excerpt from my own conversation with her “beta” version of the bot (Figure 2-1).

Figure 2-1. Example Bot Script

For me, this experience felt very strange, yet quite comfortable at the same time. I also felt that I gained real insight into my dream and the state of my mind from the exercise. If you want to have your own uncanny valley experience, visit the Resource Site.

Prepare to Be “Creeped Out” a Bit

Our applications of AI become will more sophisticated and more general in nature. We will need to consider how to help users adapt to the potential creepiness of the interaction, so that they can get through the uncanny valley and enjoy the benefits the application is designed to provide.

As we prepare to bring AI into daily life, the temptation to imbue these learning machines and systems with imagined personalities and intents will be powerful, perhaps irresistible. As a talent development professional, you will not be entirely immune to this human trait, but you can be aware of it and prepare to resist it in yourself while you help others maintain a boundary between the AI that helps them do their jobs and the human beings in their lives. But maybe that’s OK, and we will interact better with machines that feel like colleagues.

Has COVID-19 Accelerated Investments in AI?

In 2020, it is impossible to discuss the future without considering the impact of the COVID-19 pandemic. While the final chapter in the story of the human race and its battle with this deadly disease has yet to be written, the opening paragraphs suggest a time of increased awareness of and investment in artificial intelligence, if only because it is being used so freely in the rush to find a cure or vaccine. The work being done around the world to track the spread of the disease and test potential treatments or vaccines has been driven by machine learning, and is showing the world the enormous potential for AI to recognize patterns and solve problems faster than humans could ever achieve.

While this massive effort is under way, AI itself is evolving. By its very nature, an AI gets better with use. The data scientists, programmers, and cognitive scientists engaged in pointing the power of AI toward a virus are learning new techniques every day. These techniques will translate into advancements in medicine, technology, computer science, pharmaceuticals, and other industries. But more importantly, the work being done by the AI community to fight COVID-19 today is making us all a whole lot smarter. And we’ll be able to apply those solutions to new problems as soon as we’re able to change our focus. At the same time, decision makers who aren’t very educated about AI today will be much more familiar with how it works, its limitations, and its potential. From where I sit, it seems likely that the post-pandemic world is a world driven by AI—perhaps even sooner than predicted before a global crisis forced us to seize the most powerful tool we have to fight our most dangerous foe.

Summary: Get Ready to Change

In this opening chapter, we introduced additional key terms, including:

• machine learning

• the singularity

• general intelligence.

We also talked about some simple, practical ways that you can begin engaging with AI today, by using technology readily available to you as a consumer with a smartphone. We explored a few use cases for AI in the workplace, specifically related to our field of talent development. And we peeked a bit into the near future, as we begin to move from hypothetical use cases to living examples of these use cases in practice. Along the way, it was impossible to discuss our present or our future without touching on the impact of COVID-19. The full details of that event in our history have not been written, but it is safe to say that we have been changed by our shared ordeal.

We addressed a question that many of us ask when we think about AI and automation: “Will I be replaced by a robot?” If your livelihood depends on performing manual, repetitive tasks, the answer to that question is “probably.” But since you’re reading this book, I can make some assumptions about the work you are doing today and can give you a different answer. It is much more likely that your work will be transformed by an army of smart machines. You will likely find yourself collaborating with machines, if you aren’t already. Nearly every job has some tasks that are routine and require minimal cognitive effort to accomplish. Intelligent machines can take over these tasks, so that we can focus on those tasks that require human involvement—creativity, judgment, compassion. Parkinson’s Law says that the amount of work in an organization expands to fill the available time. So even if you succeed in delegating all your current duties to a new team of digital employees, you’ll still find plenty of work to do—it will just be different work.

Working with these smart machines can do more than solve scientific puzzles like COVID-19. It can move the organization—and the people within it—into new levels of insight and performance.

If you’re interested in engaging some of the simple programs mentioned here to streamline your work, you’ll find updated information, tips, and training on the Resource Site.