Chapter 1: Why Digital Transformation Matters To Your Career PDF

CHAPTER 1: WHY IT MATTER SO MUCH TO YOUR CAREER =============================================== VIDEO "DIGITAL TRANSFORMATION: A MASS EXTINCT EVENT" ---------------------------------------------------- **The word revolution gets thrown around so much in the media that we\'ve become desensitized to...

CHAPTER 1: WHY IT MATTER SO MUCH TO YOUR CAREER =============================================== VIDEO "DIGITAL TRANSFORMATION: A MASS EXTINCT EVENT" ---------------------------------------------------- **The word revolution gets thrown around so much in the media that we\'ve become desensitized to what it really means. I did a brief online search on media headlines with the word revolution in them for just the month in which we\'re filming this video and the results were quite plentiful.** **Maybe that\'s the reason why, when we hear about the digital revolution, so many of us mentally downplay the magnitude of what\'s happening right now. When every new fashion runway show gets labeled as revolutionary, the original significance of the word fades away. So I\'m not going to start this course with a digital world revolution is taking place.** **I\'m going to word it a little bit differently. Something like, in 10 years, the job that you have today or that you are busily studying to have one day will not exist. Gone.** **Poof. Many people associate the kind of job transformation I\'m talking about with factory work. In their mind, factory workers will be replaced by robots.** **And while that\'s true, I want to be crystal clear about the jobs I\'m talking about just to make sure I\'m talking about the jobs of only the other people. I mean key account managers, surgeons, lawyers, supply chain managers, accountants, journalists, actors, composers, electricians, event planners, teachers, butchers, bakers, candlestick makers. Any workflow that follows a pattern that is repetitive, that has steps which are steered by customer preferences, can already be carried out by a machine in ways where the output is indistinguishable from that of the human beings.** **And in those areas where there still is a marked gap between human output and machine output, that gap is shrinking faster than greased lightning. Just as a quick sidebar, I\'ve purposely had AI write the text for roughly two minutes of this first video. See if you can even identify which two minutes were written by a machine rather than by a person.** **Does that mean that we human beings will become irrelevant to the future workforce? Are we outsourcing ourselves? I personally don\'t believe that at all. Whenever humans have discovered a new technology that revolutionizes work, whether it\'s the wheel, fire, agriculture, the printing press, steam engines, telephones, or computers, we\'ve always found new work that can\'t be done by the existing technology yet. I think it\'s part of our programming as a human species to want more than what we currently have.** **And so, that will inevitably lead to new forms of work. And to new ways of organizing that work. So I\'m not saying that all the jobs on our planet are suddenly going to disappear.** **We will still need surgeons, farmers, judges, teachers, authors, and most other jobs. What I am saying, though, is that 80% of the activities that the people involved with these jobs will be carrying out all day long in the future will have nothing in common with 80% of the activities their current counterparts are carrying out all day long. For every profession that has repetitive elements, any process that can be automated will eventually be automated.** **In the short run, this will be because it\'s cheaper. In the long run, it will be because machines will be better at these repetitive tasks than human beings are. Is this progress? Will the digital revolution propel humanity forward to unknown heights? Or are we reducing ourselves to the role of passive consumers? Will we become redundant observers that watch as machines slowly take over the lead roles in a drama that we ourselves have unleashed? None of us should be so arrogant as to predict with 100% certainty that it will be one or the other.** **I think a more appropriate answer is, we\'ll see. Because it depends. And to be clear, it doesn\'t depend primarily on the digital machines themselves.** **It depends on us, the leaders, the consumers, the voters. We alone have it in our hand to make sure that this real revolution that we are all a part of does not end up devouring its children. That responsibility, that digital responsibility, is one that you and I now carry every time we make a decision.** **Gunpowder existed in China as early as the 2nd century AD, but it was primarily used as a form of rocket propulsion for ground rats, for fireworks. It wasn\'t until 800 years later that its potential to shoot bullets was developed. That wasn\'t just a discovery.** **It was a decision. And whoever was involved in that decision bears a partial responsibility for every mammal that has been wounded or killed by a bullet or cannonball since then. For every war that was started because some group thought it had more guns than some other group.** **The responsibility you assume as a leader for your digital decisions is just as significant. And it begins with understanding digital technologies, in knowing what they can and cannot do today, in anticipating what they will and will not be able to do 15 years from now. Only then will you even be in a position to be more than an ignorant bystander in this revolution.** **To shape rather than to be shaped. Most leaders around the world do not have a profound understanding of the current digital revolution that is taking place. Their mindset is often limited to what kind of software should we install and what kind of data warehouse do we need.** **That\'s not what this is about. I want you as a future leader to go about this differently. From today onwards, I want you to look at every single organization you interact with.** **Be it the company you work for, the non-profit organization you help out at, the supermarket you shop at, the hairdresser that gets you ready for Friday night, or the movie theater you visit with your friends, whatever. I want you to look at each of these organizations and ask yourself. What do this organization and its people do all day? What are all the big and little processes that they carry out behind the scenes in order to deliver their output? And now ask yourself.** **Which of these big and little processes can and presumably will be carried out by computer intelligence within the next 10 years? Only if you assume this mindset do you have a chance of getting ahead of the curve and thus of making decisions that will allow the consumers, employees, society, and planet that you are responsible for not only to survive in current form, but to thrive. If you want the word manager in your job title, then that\'s your digital responsibility in this brave new world. Understand the consequences, the opportunities, the risks, and the instruments of the digital revolution.** **That knowledge is what will empower you to make wise, forward-thinking decisions that ensure the prosperity of the human beings and the society that are in your sphere of influence. Without that knowledge, you have no place running an organization or department in the 21st century. In my opinion, you don\'t even have any place running a child\'s lemonade stand.** **You\'re basically like a horse carriage driver in the early 1900s that refuses to acknowledge the cars around him. Make no mistake about it. The digital revolution is a real revolution, not some glitzy catchphrase.** **Almost nothing about the way we will work in 15 years is going to be the same as it is today. In his excellent book Digital Transformation, Thomas Siebel even refers to this revolution as a mass extinction event in reference to most current-day business models, which is exactly what it will be. This course is designed to give you the basic know-how you need to help you steer your people through that.** **\ ** INNOVATION: FAST AND FURIOUS ---------------------------- **We feel that the following takeaways are valuable to any leader:** 1. 2. 3. 4. ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ***[Fact:] If you ask people that were adults in the 1970's and 80's whether they were familiar with tools like "GPS", "internet", "email", "video conferencing", "mobile phones" or "3D printers", the overwhelming majority will answer "no". Yet all of these technologies had already been invented. Similarly, inventors have most likely already discovered the big disrupters of 2050: most of us just don't bother to scan the environment for what's out there.*** ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- **You will not identify potential future disruptive innovations just by skimming through popular media. Journalists specialize in "what IS" far more than in "what might be".** **Bottom line: Due to the accelerating speed of innovation, a good 21^st^ century leader has to establish steps and habits to proactively identify disrupters and game changers on the horizon.** **\ ** TRANSCRIPT VIDEO MEGA-TREND \#1: THE INTERNET OF THINGS (IoT) ------------------------------------------------------------- **I want you to take a deep breath and think of all the important objects in your life that are connected to the internet. Your list will probably include your smartphone, your computer, the smart TV, and maybe a watch and a smart speaker.** **But whether we realize it or not, we are already surrounded by a vast number of other devices which happily chat away with each other without us paying nearly as much attention to them as we do to our 'productivity' devices like our phones or laptops.** **So imagine this scenario: you wake up and groan -- that hasn't changed. But in this scenario you might be wearing a bracelet that tracks your body's sleep data and vital signs. That bracelet -- which is of course connected to the internet -- will sense your raised heartrate and increased movement, and will inform the stove and the coffee machine in your kitchen -- which will ALSO be connected to the internet -- that you just woke up. That's great, because as you enter the kitchen, a bowl of porridge and a steaming cup of coffee is already waiting for you.** **You might open the refrigerator to get some milk for your coffee. Since your refrigerator contains sensors and is also connected to the internet, it will alert you that soon you'll be running out of milk, eggs, and that moldy green stuff in the corner, and it'll offer to automatically order some for you from a food delivery service.** **While you have breakfast, you might get startled by your automatic vacuum cleaner -- it has started cleaning much earlier than its usual evening time - it has access to your calendar and knows you're planning to have guests over right after work. Sparky, your cat, has heard the commotion and escaped to the garden though the cat door, which, also being smart, has already alerted you via SMS about it.** **You finish your breakfast and head out the door. Your home automation system locks the door's smart lock behind you, rolls down the blinds, and, much to Sparky's dismay, turns on the garden sprinkler system.** **And before you even got in your car it has activated all alarms and cameras, turning your house into an impenetrable fortress.** **What kind of magic technology are we describing here? Welcome to the Internet of Things, here to make your life easier, more efficient, safer, and more enjoyable! At first glance, this Internet of Things seems to be made of many different devices, communicating with each other to make your day better.** **That's a good start, but if we want to be more precise, we should define the IOT as a network of physical objects (which are the 'things' in the IOT). But being simply connected with each other doesn't yet make an object smart, or part of the IoT. In order for these various physical objects, or devices, to be defined as a 'smart' device and part of the Internet of Things, it must contain embedded sensors, software, communication protocols and other technologies in order to gather data and exchange this data with other devices and systems in the cloud for various purposes.** **But that kind of sounds just like what a normal computer might be doing, right? That's right, and technically, your PC or smartphone IS an IoT device. In practice though, IoT devices are either tailored to fulfill one, or few very specific purposes, or they perform functions which historically would not be associated with network computing, but have been upgraded with cloud functionality.** **Think of the bracelet that tracks your biometric data and then sends it to various other network nodes to start yet other actions -- it will do this very well, but don't rely on it to help you with your tax spreadsheet. Sparky's collar tag will show you on your smartphone exactly where he's hiding from the sprinklers, but won't do much more. And the fridge and coffee machine? Both are appliances which we have been successfully using for decades in their 'dumb' form, but which now have been upgraded with sensors and communication features.** **But home automation or personal smart gadgets are only a small part of the IoT -- it has a vast number of other application cases:** - - - - - **This is a big deal. A 2020 McKinsey report estimates that in 2025, the IOT will have around \$2.8 trillion to \$6.3 trillion in potential economic value. The forecast for the number of connected devices in that same year is estimated to be 75.44 billion IOT devices.** **But the Internet of Things also poses significant challenges and risks, more so than established, 'classical' computing systems do. The include:** - - - - **And finally, a risk which concerns both large companies and private users:** - **But not all is doom and gloom - to end this topic on a lighter note, here are a few IoT devices which have been let loose upon our world (*see video for examples*).** **\ ** TRANSCRIPT VIDEO MEGA-TREND \#2: BIG DATA ----------------------------------------- **We've just heard about the "Internet of Things" and how it's going to grow. That goes hand-in-hand with our second mega-trend: Big Data.** **Unless you live under a very, very analogue rock, you're already familiar with the term "Big Data". But I want you to think about this for a second.** **The International Telecommunication Union -- so, the branch of the United Nations that is specialized in information and communication technologies -- has forecasted that by 2030, global monthly data traffic will be 84 times higher than it was in 2020. So here's where we were in 2020, and here's where the United Nations expects us to be in 2030.** **Let's make that a little more tangible. Here is the lovely European country of Austria. And here is the lovely Latin American country of Brazil. That's the relative size growth the International Telecommuniation Union is talking about. If 2020 global monthly data traffic is the size of Austria, 2030 global monthly data traffic will be the size of Brazil. Mainly -- but not only -- because of the growth in the Internet of Things, Big Data is about to get a lot bigger.** **"So what?" you may be asking yourself. "My job has nothing to do with building data networks. Why should I care?"** **You should care because this data explosion is going to catapult the quality of Artificial Intelligence and Machine Learning lightyears beyond what it is today.** **For any type of Artificial Intelligence to be useful, it needs to draw upon accurate and relevant data. The more such data it has, the better it will be able to identify patterns, make predictions, and provide recommendations.** **In the past, the amount of data that Artificial Intelligence worked with was limited by two factors: the speed at which computers were able to process data, and the availability of the data itself.** **Modern day processors have freed AI of the first of these limitations: computers can now process billions of units of data per second.** **But until recently, the second limitation -- access to enough accurate and relevant data -- has required Artificial Intelligence to limit its computations to statistically significant SAMPLES of data.** **So let's take an example where we want to use AI to make a prediction about how EU households will respond to a new environmental law. In the past, instead of looking at the data of all the households in the EU, Artificial Intelligence would consider the data of a subset of these households that has been selected in a way that makes this subset statistically representative of the whole.** **This data would then be analyzed by the AI and -- using statistical methods - it would make predictions about how EU households would react to the new law. That's already pretty astounding. But statistical methods are always subject to sampling errors and "confidence limits". What this means -- for the purpose of our discussion -- is that there's ALWAYS a certain probability that conclusions drawn on the basis of statical methods will be... wrong.** **And here's where Big Data comes in. As more and more data becomes available -- so, Brazil instead of Austria -- Artificial Intelligence won't need to draw upon statistic samples -- so subsets -- of a dataset anymore. It will have access to the entire dataset. And computer processors will be fast enough to sift through that entire dataset in the blink of an eye.** **We'll talk more about what that means for the future of AI in a later video. here, we can preemptively say that AI will be able to recognize patterns, spot outliers, and identify trends with an accuracy and at a speed that human beings simply can't match.** **Obviously, the forthcoming data explosion will bring its own set of challenges, such as making sure that the data is accurate and trustworthy, and that protective data privacy is protected. One central challenge related to Big Data is the question of where organizations will store or access all this data. And that's where our third mega-trend, Cloud Computing, comes in.** **\ ** TRANSCRIPT VIDEO MEGA-TREND \#3: CLOUD COMPUTING ------------------------------------------------ **When most of us hear the word "cloud", we either think of a big puffy floating glob of cotton in the sky, OR we think of that special online place to which we upload our pictures, videos, and Word documents, so that our many electronic gadgets now have storage space for NEW pictures, videos, and Word files. Most of us think of clouds as just another place to store things. So why is "Cloud Computing" one of THE biggest current trends in digitalization today?** **One of the most fundamental ways in which Cloud Computing has changed the world is in the way teams now collaborate. In the past, team members that were working on the same document or project had to either be sitting at the same table OR one of them would work on a document, then send it to the others, who would each add their own two cents, then send it to the others, in an endless loop that left the team with multiple very different versions of the same underlying task. You basically either had the choice between 'moving ahead very slowly' or 'creating mass confusion'.** **With cloud computing, all team members now have access to the same documents and data in real-time, regardless of whether they're sitting at the same table or located in very different geographic locations. Aside from the obvious benefits of saving time and reducing confusion, this type of real-time collaboration fosters creativity, resulting in higher-quality outcomes.** **Cloud technology also gives us access to a bundle of online services and apps that simply wouldn't be available at a click otherwise. Think of all the apps that you use that aren't stored on a digital device. The only reason they work is because they're stored in a cloud somewhere. And because they're in a cloud, they can be accessed by multiple team members -- or by you and your customers, or you and your suppliers -- always at the same time, once again allowing you to collaborate much more effectively. Which allows organizations to develop new goods and services at a much faster pace.** **Aside from collaboration, the fact that an organization can store its data on a cloud allows employees, suppliers, customers, and other stakeholders to access this data in real time, regardless of where in the world they're located.** **In the past, an organization would store all of its data on a local server. So let's say you're a company employee located in a branch on another continent. Because of the geographical distance, you don't have automatic, immediate access to the local server. But you need some of the data on that server to do your job. So you contact someone at headquarters, request the data you need, and wait. And wait. And then wait some more.** **With cloud solutions, you don't have that time lag anymore. If you're authorized to access the data you need -- whether you're a company employee, a company supplier or even a company customer -- you simply retrieve it from the cloud. No phone calls, emails or waiting time involved. Just think about how much time that saves around the world every single day.** **And now think of all those machines and robots in a modern-day factory that also need countless data in real-time so that they can carry out their work. Once again, the ability to simply access the data they need from a cloud -- completely independent of where in the world they're located -- allows companies to produce goods and services in a far more efficient, automated manner -- and far more safely than was previously the case.** **If an organization stores its digital content on a local, centralized server, then the amount of data it can store is limited by whatever hardware it has purchased. This essentially leaves it with two options: either buy hardware with the storage capacity to match the organization's current data needs or buy hardware with the storage capacity to match the organization's anticipated future data needs. The first option will obviously be cheaper than the second.** **both options are sub-optimal in case an organization grows and incurs higher data storage requirements. In the first case, the upgrade in storage capacity is going to cost the organization much more than if it had simply bought the "higher storage capacity" option server right away. And in the second case, the organization will have to spend a much higher amount earlier up-front for something that it doesn't need yet.** **Cloud computing bypasses this tradeoff because it's scalable. Basically, an organization can increase or decrease its storage capacity as needed -- and without disrupting an organization's ongoing workflow.** **Now consider that in light of our first two 'megatrend videos'. The Internet of Things is growing at lightning speed. This means that the amount of data that affects EVERY organization will not just double, triple or quadruple in the near future. Instead, we're talking about a worldwide increase in the next ten years by at least TEN times as much data as is currently being handled.** **Where are organizations going to store all their extra data? Local physical servers simply won't be a cost-efficient option for most organizations for such massive scaling -- but clouds will.** **Imagine an organization that stores all of its data and its applications on a server at a SINGLE geographic location. And now, let's imagine that something happens at that geographic location -- maybe a tornado races through the city, or maybe the building next to the server catches fire. The organization's data and applications would be gone forever. And because of that, the organization probably would be, too.** **The ability to backup data and applications on clouds spread across the planet eliminates that risk entirely.** **And we don't even need to think that drastically. You've probably experienced hours in your lives where your phone service is down, or when your wi fi provider is down. That's an understandable annoyance for you, as a consumer. But imagine how the same downtime affects a company whose employees, suppliers, machines, robots, and customers ALL rely on company data in real time. If there is only one location at which that data is stored -- and that location is 'down' for whatever reason -- then the workflow in that company will essentially come to a standstill.** **On the other hand, if the company has distributed its data and applications over multiple clouds in different geographic locations, it has the perfect 'safety net'. Whenever a primary site is down, data or App requests by employees, suppliers, machines, robots, and customers are simply re-routed to a secondary cloud location that isn't down.** **This distribution of data over several locations often goes hand-in-hand with something called "Blockchain technology". The idea behind blockchain technology is that you don't store the complete version of something at ONE location or in ONE cloud. The reason behind this is that if that one location is ever hacked, the hackers have access to ALL the data they need in order to do some real damage.** **Instead, with blockchain technology, data is split up into individual "blocks" that are connected to each other, but are each stored at very different locations. So even if a hacker manages to infiltrate and get hold of the data at one of these locations, they still won't have access to the data that's stored at all the other locations.** **Think of a picture. Now split that picture up into the little pieces of a jigsaw puzzle. Each piece is separate, but it also has a connection to some of the other pieces. Now imagine each piece of the jigsaw puzzle is kept at a separate location. A thief breaks into one of these locations and finds exactly one piece of the jigsaw puzzle. They'd still have no idea what the entire picture looks like.** **Because of this far greater level of security, companies are increasingly using blockchain technology in combination with clouds to to store information securely.** **In order for any type of AI to be useful, it needs to access a significant amount of data. The more relevant data it has, the better its ability to analyze the data, identify patterns, automate and optimize workflows, and make recommendations.** **Obviously, the data explosion that is the consequence of the 'Internet of Things' will be a bonanza for the quality of future Artificial Intelligence. But again, this data needs to be stored somewhere cost-effectively. Also: a great deal of the data that future AI will draw upon will be need to be accessed by multiple organizations, not just by one. The best solution for both these requirements are clouds.** **Last, let's re-visit the daily quantity of data traffic that will be sent through cyberspace by the Internet of Things in just a few years. We're talking about at least ten times as much traffic as per 2023.** **Faster communication networks like 5G will undoubtedly improve transfer speeds per kilobyte. But even so: the internet traffic of the future is going to look a lot like the Hollywood Freeway on a Monday morning. So any workflow where a company transfers all its data to one centralized location -- like a local server - and then retrieves all its data from that same centralized location, simply won't be fast enough anymore. And that's why many organizations are already experimenting with newer solutions like "edge computing", "hybrid clouds" and "multi clouds".** **Bottom line: Digital strategies that don't make clever use of cloud computing have no future.\ ** TRANSCRIPT VIDEO MEGA-TREND \#4: ARTIFICIAL INTELLIGENCE -------------------------------------------------------- **This is the scary one, right? With apocalyptic film franchises like 'The Matrix' or 'The Terminator', it's no surprise that many of us see 'Artificial Intelligence' as a kind of Pandora's Box that can only end in the destruction of the human race. In this video, let's take the red pill and see what AI actually IS.** **First and foremost, the term 'artificial intelligence' is an unfortunate one - in our minds, it evokes images of some sort of living, intelligent artificial being, with its own thoughts, character, and consciousness. Perhaps one day we'll manage to create such artificial beings, but for now, no matter how 'lifelike' AI seems to be, there is absolutely no trace of any consciousness, thought, or 'life' in any AI -- just to get *this* out of the way first.** **So what *IS* AI made out of? Simply put -- out of *software code*, the same kind that your office suite or adventure games are based on. Code that a human programmer has written. In lots of ways, AI is like *every* other software code of any other application.** **The big difference is this: regular software code is simply a series of steps, or commands, which are executed one after another, in a very clear and predictable manner. The code might be complex, but it's always understandable and predictable -- you'll *always* be able to know WHY the software arrived at the result it did. We call such code "deterministic", which means that it will always follow the exact same set of steps and produce the exact same output for a given input. Think of a calculator - if your input was "four plus five", you, and every single accountant on this planet, would be very frustrated if the calculator's output was not a predictable "9*", every single time*.** **In contrast, the type of software code which powers artificial intelligence is not deterministic, but probabilistic. This means that unlike traditional software, artificial intelligence provides only estimates -- it predicts only the probability of various outcomes rather than offering absolute certainties.** **How does AI do this? It also uses software code, but this code is different -- we call this type of code 'Machine Learning'. While traditional computers must rely on human programmers to give them very specific instructions on how they should complete a task, Machine Learning enables computers to learn AUTONOMOUSLY, and then make decisions on how to complete a task based only on what they themselves have learned.** **Let's take a simple example of this. We'll use machine learning to have an Artificial Intelligence mimic the way the English language works. To do this, we give the AI access to millions upon millions of different English texts, gathered from print media, celebrity magazines, and the internet. It analyzes these texts, and learns all recurring patterns it stumbles upon. For example, it learns that almost every time the words "salt and..." appear, they are immediately followed by the word "pepper".** **Another pattern it learns is that the word sequence "rock and" is often followed by the word "roll". That the words "trial and" are nearly always followed by "error", the sequence "law and" is followed by "order", and so on. Oddly, it also learns that the words "Brad and" are followed by "Angelina" only half the time... the other half of the time, they're followed by "Jennifer". A most curious pattern.** **Our AI then feeds all these patterns into its machine learning algorithm. This algorithm creates something called a 'model' -- this is a mathematical representation of all the patterns it has learned. And NOW, our AI can use its new model to correctly and creatively interact with yet new and unknown data and patterns. For example, when it is asked to continue a text and the lead in is "Salt and", it will add "pepper" based on what its model has learned. But if it's asked to continue a text that begins with "Brad and", then it MIGHT add "Angelina". Or, it MIGHT add "Jennifer" instead -- we can't really predict what it will choose.** **How is this different from a regular computer code that a programmer has created? Well, in the regular computer code, the programmer would have to specifically create instructions where each time someone types "Salt and", the code adds the word "pepper". In contrast, AI adds "pepper" by itself -- without any explicit instruction by the programmer -- simply because it has learned that the probability of such a correlation is high.** **Using these Language Models has tremendous advantages in many situations, especially when the amount of possible choices or answers would completely overwhelm regular computer code. If a problem offers only a few possible choices, a human programmer is able to write code which will pick the best solution for the given task at hand. But when there are hundreds or thousands of possible choices to be made in a situation (like in a human conversation, or in navigating on a busy street) only a Language Model offers the power and flexibility to choose the best answer, based on mathematical probability and what it has learned.** **Let's look at some of the things that AI can currently help us with using these models:** **The most obvious (and impressive) use case has to do with language itself. AI finally created a bridge between human language and stored digital information, and now acts as a powerful and efficient interface between the two. Digital assistants, chatbots, and customer interaction systems can communicate with humans and offer help, information, or guidance. Ai can search documents, summarize texts, or even create original content. In medicine, disease diagnostics can be vastly improved due to AI's pattern recognition capabilities. In agriculture, farmers are utilizing AI technology to optimize their crop management practices, transportation and logistics use AI to optimize routes and storage. Cybersecurity in the enterprise sector can adapt quickly to new and unknown threats. Retail, business processes, health care, city planning\... Any industry which creates lots of data -- and these days it's almost *every* industry -- can benefit from AI's powerful pattern analysis.** **But what about this "AI can only predict the PROBABILITY of various outcomes rather than offering absolute certainties' thing we talked about before? But I *want* my calculator to be perfectly correct, and my medical diagnosis to be absolutely certain!** **Well, for all the amazing things AI can do, it also has a darker side, or at least one we should be aware of. You might have heard that AI sometimes 'hallucinates'... What's up with that?** **An AI hallucination happens when the AI generates false, misleading or illogical information, but presents it as if it were a fact. Hallucinations are caused by limitations and/or biases in training data and the machine learning algorithms, which can potentially result in producing content that is not just wrong but harmful.** **Remember how we said that Artificial Intelligence is not conscious, or even actually intelligent? We have to remember that it only APPEARS to be so. AI uses so-called Large Language Models to interact with us and make it seem like it understands us, but although these models are designed to produce fluent and coherent text, they have no actual understanding of the underlying reality that they are describing. All they do is predict what the next word will be, based on cold mathematical probability, and not factual accuracy. They're a bit like\... well trained parrots.** **From a real-world example: If an AI is trained on data with a consistently skewed reference to, let's say, the gender of certain professions (using sentences like "The doctor promised *he* would visit me tomorrow" or "The patient saw the nurse and thanked *her*."), then, because the AI always only saw the word 'Doctor' in the same sentence with 'he', it might conclude, with full confidence, that becoming a doctor is not a viable career choice for young women.** **So - feed the AI with complete, unbiased datasets and you'll get objective recommendations. Feed the AI with incomplete, racially-skewed data and you'll get racist decisions. Or decisions that don't take the emotional well-being of humans sufficiently into account. What about job security? Generative AI -- meaning the type of AI which can generate original content in any medium, whether it's text, art, or music -- is already having a negative impact on the creative industry, with artists, authors, and musicians reporting significant financial losses.** **This all IS an undeniable risk of AI. It's what every dystopian sci-fi movie with 'evil machine overlords' is based on. But the response can't be to simply "ban AI". In all of human history, there has never been a revolutionary-but-risky technology that people have just 'put back in the box'. There are always enough people that value the potential benefit of an invention over its potential risk: and for better or worse, they will continue to develop it -- no matter what other groups may say or decide. And despite all the risks, AI has already proven itself to be way too useful to put it back in that box.** **So, we'll have to find a middle way -- we can reap the benefits, but at the same time we have to try to regulate -- legally, if necessary -- which areas we want AI to shape and influence. People who see the risks of AI -- more than anyone else -- need to be actively involved in developing the laws, the ethical guidelines, the transparency requirements, the individual accountability and - above all -- the tools and methods that ensure that the data which future artificial intelligence learns from is diverse, representative, and, not least, anthropologically benevolent.** **\ ** HOW CAN AN ORGANIZATION BE DIGITALLY TRANSFORMED? ------------------------------------------------- - **First, we covered why a thorough understanding of digitalization is a "must have" for any responsible modern-day leader.** - **Next, we looked at the current megatrends of the digital landscape.** **If we've done our job well as instructors, then we've sensitized you to WHY leaders must follow digital developments closely -- regardless of what department they're in or what functional background they have.** **The next question is "HOW"?** **The entire remainder of this course has been designed to help you answer that exact question. And that answer begins with an understanding of your Enterprise Information System (EIS) (or "Business Information System" (BIS)).** **By definition, every organization since the beginning of time has had an Enterprise Information System. But what is an EIS?**