Artificial Intelligence: Preparing Your Career for AI | Matthew Renze | Skillshare

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Artificial Intelligence: Preparing Your Career for AI

teacher avatar Matthew Renze, Data Science Consultant

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Taught by industry leaders & working professionals
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Watch this class and thousands more

Get unlimited access to every class
Taught by industry leaders & working professionals
Topics include illustration, design, photography, and more

Lessons in This Class

    • 1.



    • 2.



    • 3.

      Educate Yourself About AI


    • 4.

      Upgrade Your Career for AI


    • 5.

      Invest in an AI-first Economy


    • 6.

      Use AI Responsibly and Ethically


    • 7.

      Adapt to What Comes Next


    • 8.



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About This Class

Learn how to prepare your career for the coming wave of AI automation.

Whether you realize it or not, we are currently entering the era of artificial intelligence. AI technologies are radically transforming our lives, our careers, and our world. However, most of us have not yet learned how to leverage the power of this new technology.

In this free course, you’ll learn the five things you should be doing today to prepare your career for the coming wave of AI-enabled automation.

  1. Educate yourself about AI
  2. Upgrade your career for AI
  3. Invest in an AI-first economy
  4. Use AI responsibly and ethically
  5. Adapt to what comes next or become obsolete

The future belongs to those who are willing to invest in AI now. Don’t get left behind!

Meet Your Teacher

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Matthew Renze

Data Science Consultant


Matthew Renze is a data science consultant, author, and public speaker. Over the past two decades, he’s taught over 400,000 software developers and IT professionals. He’s delivered over 100 keynotes, presentations, and workshops at conferences on every continent in the world (including Antarctica). His clients range from Fortune 500 companies to small tech startups around the globe.

Matthew is a Microsoft MVP in AI, an ASPInsider, and an author for Pluralsight, Udemy, and SkillShare. He’s also an open-source software contributor. His focus includes artificial intelligence, data science, and machine learning.

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Level: Beginner

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1. Trailer: e Hi, I'm Matthew Renzi, data science consultant, author and public speaker. Welcome toe. Artificial intelligence. Preparing your career for a I artificial intelligence has become extremely important in the past few years, from machine learning to deep learning to reinforcement. Learning AI is taking over the world as a result. Those with the ability to leverage a I to solve business problems are in extremely high demand and our commanding significant increases in salary as a I is revolutionizing the world around us. However, most of us have not yet prepared our careers for the changes that modern A I will soon thrust upon us. The purpose of this brief course is to answer the question. What should I do today to prepare my career for the coming wave of AI enabled automation. To answer this question, I'll provide you with advice that specific, actionable, pragmatic and timely as an introductory course. There. No prerequisites for this course. I'll be explaining everything you need to know along the way. In addition, this course is designed for a general audience, whether you're a software developer and 90 professional, a manager or none of the above. This course is right for you by the end of this course, you understand what you should be doing today to prepare your career for the AI Tech revolution. So please join us today and learn how to prepare for the A I revolution with artificial intelligence, preparing your career for a I. 2. Introduction: Hi, I'm Matthew Renzi, data science consultant, author and public speaker. Welcome toe. Artificial intelligence. Preparing your career for a I. In this brief course, you'll learn what you should be doing today. To prepare for the coming wave of AI enabled automation, you learn how AI will impact you, your career and our world. More importantly, I'll provide you with practical advice on how to prepare for these changes today. But first, let's begin with a quick story. Over the past few millennia, humanity has gone through several major technological revolutions. Around 10,000 years ago, we entered the agricultural revolution. This revolution led to new agricultural technologies like farming the plow in the wheel. As a result, agricultural societies spread from the cradle of civilization to the ends of the earth. Around 250 years ago, we entered the Industrial Revolution. This revolution led to new industrial technologies like steam power, the factory and electricity. As a result, industrial societies flourished and spread across the globe. Less than 100 years ago, we entered the information revolution. This revolution led to new information technologies like tele communications, electronic computers and digital information. As a result, high tech societies prospered as they spread across the globe and into cyberspace. With each of these technology revolutions, human society was radically transformed over a relatively short period of time. With each revolution, we saw wellspring of new technologies that had never existed before. And with each revolution there were those who were prepared and thrive in this new world and those who were unprepared and became redundant, unemployable or obsolete. Today we're entering the next major revolution in human history. The artificial intelligence revolution. Just like the previous technology revolutions will likely see a fundamental transformation of our economy, our society and our world. We will likely see a wellspring of new AI enabled technologies and there will be some people who will prepare and thrive in this new world and others who will be unprepared and will become redundant, unemployable and obsolete. The purpose of this brief course is to answer the following question. What should I do today to prepare for the coming wave of AI enabled automation? What should you be doing right now to prepare as we enter this next major technology revolution? However, I don't provide you with a bunch of pie in the sky. Wishful thinking. I want to provide you with advice that specific, actionable, timely and pragmatic advice that you can put to good use today to ensure your success through the AI Tech revolution and beyond. To answer this question, I'll provide you with the following five recommendations. Educate yourself about AI. Upgrade your career for A I invest in an AI first economy, use ai responsibly and ethically and adapt to what comes next or become obsolete with each step will go a bit wider in scope, in longer in her time scale. By the end of this course, you'll know what you should be doing today to prepare for the coming wave of AI enabled automation. Before we get into the practical advice, I want to make sure that we're all on the same page about what artificial intelligence is and what it isn't. So what is a I Artificial intelligence is a field of computer science that attempts to create machines that act rationally in response to their environment. An AI is any machine that perceives its environment and chooses actions that maximize the likelihood of achieving a goal of some kind. Essentially, an AI is just a machine that takes data as input and produces the best possible output. Given what it currently knows, some examples of AI include computers that can play chess, robot second vacuum your floor, non player characters and video games and navigation software on your smartphone. Any computer algorithm that replicates some aspect of human intelligence or natural intelligence is essentially a form of artificial intelligence. Now, when I say artificial intelligence, many of you will immediately think of sentiment robots like R two D two data from Star Trek or how 9000 this is what we refer to is Artificial General Intelligence or General Ai General Ai Consol. The wide variety of general purpose problems. It's a type of futuristic ai that doesn't currently exist. In fact, it will likely be several decades before we reach this level of highly flexible and adaptable AI. However, it's the direction that things are moving and the eventual goal of many AI research projects. On the other hand, many of you will think of modern A I like IBM's Watson, Amazon, Alexa or Google Self Driving car. This is what we call artificial narrow intelligence or narrow A I narrow ai is focused on solving a very narrow set of specific problems. It's the type of AI that exists today, the type of AI that we're gonna be talking about during this course. However, it's also the type of AI that will likely revolutionize our world over the next few decades . It might surprise some of you that artificial intelligence has been around for quite some time. In fact, the field of A I dates all the way back to the 19 fifties. In the past, we had some machines that were capable of making rational decisions. However, they had to be explicitly programmed to make these decisions, and they could only operate successfully in very constrained environments. There was a lot of hype about what artificial intelligence would eventually be able to do. Many experts predicted that machines would soon replace all human labor, but it never happened. By the end of the nineties, machines couldn't even solve basic general purpose tasks that even a toddler could solve. The inflated hype about the potential of AI and subsequent disillusionment when it never happened led to what we now refer to as the A. I winters multiple periods between the late seventies into the early two thousands were funding for a. I had almost entirely dried up, however, by the mid two thousands. The last day I winter, it ended and things started to warm up again. Today, A. I is booming because of recent advances in machine learning, deep learning in reinforcement learning. In fact, modern A I is largely built upon these three data driven approaches. These advances are largely the result of four changes that have occurred over the past few decades. We now have a tremendous amount of data available. We now have significantly more compute power available. We now have much better algorithms for training AI models, and we now have a much more disciplined approach to AI, a data science approach. If these trends continue in the near future, AI will likely become even more lucrative as it begins to destruct almost every industry imaginable. So to quickly recap, what is AI? An AI is any machine that can act rashly in response to its environment. We're talking specifically about narrow AI, which can Onley solve a very limited set of problems. And it's an industry that's been through various cycles of booms and busts, largely based on the ratio of hype vs real world applications 3. Educate Yourself About AI: Step one, Educate yourself about a I in this module. We're gonna learn why basic AI literacy will be so important during the A I technology revolution. In addition, I'll provide you with recommendations on how best educate yourself about a I. Why is education important during a technology revolution? Why can't we just continue going about her day to day lives? Is the world changes around us? With each of the previous technology revolutions, there is a need to update human education to function in the new World. With the agricultural revolution, humans had to become proficient with agricultural technologies. As a result, we had to learn how to farm domesticate animals and use a plow. With the Industrial Revolution, humans had to become proficient with industrial technologies. As a result, we had to learn how to operate steam engines, run machinery and use electricity. With the information revolution, humans had become proficient with information technologies. As a result, we had to learn how to use telephones, work with computers and programs software with the A I revolution, humanity will once again need to update its skill set to become literate in the basics of AI. We'll need to learn how to train and models develop a I applications and use AI tools. You see whether you realize it or not, Our world is going through a major transition as we speak, rendering the era of artificial intelligence and machine learning a future where machines will be doing many of the jobs that humans are currently doing today. As a result, the softer industry is preparing to go through a major workforce transition as well. In the past, we'd have to explicitly program a computer step by step to solve a problem. This involved a lot of, if then statements, four loops and logical operations. Today, however, machines can teach themselves how to solve these problems on their own. We just need to provide the data now. This is a radically different way of working with a computer than we're used to a software developers and I T professionals. While there's a growing demand for individuals with the skills necessary to implement AI solutions, there's currently a shortage of people capable of teaching machines how to solve problems in this new way. As a result, those with skills necessary toe leverage ai are commanding significantly higher salaries, and this trend doesn't seem to have any end in sight. Think back to our last major technology revolution, the information revolution. Each of us had a choice to either learn how to use a computer or to stay computer illiterate. Think of all the opportunities that computer literacy has afforded you over the years and think of all the disadvantages for those who can barely use a computer. The same will be true of a I literacy during the A I revolution. Those who are a literate will be highly functional in our new economy, and those who are not will sit on the sidelines and eventually become obsolete. How should you educate yourself about AI? What should you be doing today to teach yourself about this new set of technologies? Unfortunately, there's no one size fits all answer to this question. It really depends on what your objectives are for learning Ai. However, I have some general recommendations that I think will help get you pointed in the right direction. First start by learning the basics of AI basic ai. Literacy will be important no matter who you are or what you want to do with a I, you need to learn the difference between what Israel versus what is hype. What can I do successfully today versus what things are currently impossible or impractical ? Learn the basics of data science, machine learning, deep learning in reinforcement, learning. Learn what they are, how they work and why they're important for AI and learn the difference between the various types of ai like narrow AI vs. Generally I Symbolic AI vs Data Driven AI and supervised learning versus UN supervised learning. Everyone in the general public will need to have a basic level of AI literacy in order to function effectively in an ad driven society. Second, choose an objective with a I. What do you actually want to do with artificial intelligence? Do you want to automate decisions, predictions or tasked with AI? If so, you need to learn how to train new AM models using machine learning algorithms. Do you want to solve new problems with a I software? If so, you need to learn how to develop a applications using pre trained AI models. Or do you just want to be more productive with your own day to day tasks? If so, you need to learn how to use pre built A I tools created by third party providers. You need to decide what you want to do with a first before you can decide what AI skills you'll actually need. Third, get the right training. There's no one size fits all training for your air education. For each objective that we previously mentioned, there's an ideal curriculum and learning path. If you want to train new AI models using existing machine learning algorithms, then you'll need training in both data science and machine learning. If you want to develop new applications using pre trained and models, then you'll need both programming skills and the ability to use pre trained AI models. Or if you just want to use pre built A I tools, then you just need basic AI literacy and training on how to use each of these tools is necessary. What's important is that you get the right training based on what you actually want to do with a I Fourth, you need to practice your skills. No matter which career, path and training you choose, you're going to need lots of practice. It's one thing to know what a neural network is, however, it's an entirely different thing. To be able to train a neural network to detect fraud. You can participate in online competitions like Kegel competitions to apply your skills while learning from your peers. You can create a maintain an open source project to share your knowledge with others while you learn. Or you can find low risk projects at work to practice your new skills and build your portfolio. Ultimately, you need to find lots of opportunities to practise the skills that you've learned and build up your resume. Finally, choose reliable sources of information. Unfortunately, there are some people out there that are just trying to take advantage of you to take your money. So you want to avoid the AI hucksters, charlatans and snake oil salesman out there. Look out for people trying to dazzle you with a bunch of big hyping buzzwords or people that are making grand or unrealistic claims and said you want to find trusted sources for all of your information and training. So be sure to check your source's credentials, qualifications and experience. You want to make sure that you're getting the most value possible for your investment in your AI education to recap our first recommendation. Educate yourself about A. I learn the basics of A I choose your objective for using a I get the right training for that objective, practice your skills extensively and choose reliable sources for your education. 4. Upgrade Your Career for AI: step to upgrade your career for a I in this module, you learn how AI will impact your career and our labor economy. In addition, you learn how to upgrade your career to prepare for the coming wave of AI automation. Will A I take my job? This is probably the most common question I get asked when I tell people that I work with a I. During each of the previous technology revolutions, we've seen fundamental shifts in employment. During the agricultural revolution, we saw the rise of the farmer and the decline of the hunter and gatherer. During the Industrial Revolution. We saw the rise of the factory worker in the decline of the artisan and craftsman during the information revolution, we saw the rise of the knowledge worker in the decline of the manual labourer during the A . I revolution will likely see a similar shift in careers within our labor economy. Imagine you could ask a horse in the early 19 hundreds how the automobile or tractor would have changed its life. It probably would have told you that a car or a tractor was gonna make it's life a lot easier. Unfortunately for the horse these technologies also made them obsolete to the economy. In fact, we had Peak horse in 1915 Justus, the automobile and tractor began to scale up in production. Today. The emergence of modern AI is beginning to have a strong impact on her labor economy in the near future. This impact on labour will likely be tremendous. AI will automate a significant number of jobs in the next few decades. Given the economics driving this trend, it's less a matter of if a given job will be replaced and mawr a matter of when. Some experts are currently attempting to predict which jobs are most likely to be automated based on measures like they're repetitive nous and complexity. Based on these measures, we can see what types of AI technology will be necessary to automate a variety of occupational tasks. For example, we can see which retail jobs will likely be automated in the coming years as a I continues to be applied to retail sales. Even the medical industry isn't immune to this coming wave of automation. While these medical tasks are generally more complex and less repetitive than most jobs, the rapidly becoming within the reach of modern A I. We can then extrapolate this information to determine which sectors of our economy will be hit the hardest by AI automation. The length of the bars in this chart represent the total number of workers in each type of employment in the USA as of 2016. The Red Bar segments represent the proportion of jobs at risk of automation in the next two decades. While the blue bar segments represent the proportion of jobs that are not at risk of automation in the next two decades, As we can see, the future landscape of labor in the next few decades is likely going toe look radically different than it currently does today. In fact, we could even use these data to predict which cities will be most impacted by unemployment from a i automation. As we can see, Las Vegas, Nevada, where I live, is currently at the top of the list. In fact, it's predicted that 65% of all jobs in Las Vegas are at risk of automation by 2035 roughly half of all jobs in the United States are at risk of automation in the next two decades there certainly jobs that will be more resistant to automation. These jobs require more human aspects like compassion, creativity, empathy and trust. However, there are many jobs today that are unlikely to exist in the next few decades. This will create a tremendous disruption to our labor economy, with unemployment, retraining and early retirement. On the other hand, it will create tremendous opportunities for new jobs that don't yet exist. And for the I T professionals that build these automation systems, the big question right now is whether a I will create more jobs and it eliminates. Historically technology. Revolutions have created more new job opportunities than they've destroyed. However, there's pretty compelling evidence to suggest that the A I revolution may be different. We're beginning to transition from an economy where most of the work of values done by humans toe one where most of the work of value will be done by machines. As a result, it's important. Ask yourself which side of this new economy will your job be on the side that's leading our new economy or the side that's being eliminated? How should you upgrade your career for a I? What should you be doing today to prepare your career for the coming wave of AI automation . First, determine if your job is at risk of automation from AI. Is your job simple, repetitive, dangerous, air prone are expensive. If so, it's at a higher risk of becoming automated. Or is your job complex, creative, compassionate or uniquely human? If so, it's at a lower risk of being automated. However, it's important to note that most jobs will not be completely automated. Rather, many of the day to day tasks within your job will become automated. But some tasks will remain. As a result. You may likely spend most of your day essentially managing software or baby sitting robots . In addition, one Ai assisted worker will likely be able to do the job of several regular human workers, so there will be less total workers needed for each type of job, and competition for those jobs will likely become more fears. Second, determine if your company is at risk of becoming obsolete within our AI first economy. Are you still using traditional business tools and processes while your competitors air automating with AI? Are you still relying on guesswork while others are using data to improve decision making or are you in an industry that's currently being disrupted by a new AI enabled business model? If so, you either need to help your company embrace AI now. Or you may want to find an employer that's already moving in the right direction. Unfortunately, it's quite likely that many employers that are resistant to automating using a I will not survive this impending technology revolution. Third, you need to choose an AI career path. You need to decide how closely and deeply you want to work with a I. If you want to train and models, you'll need to find a company with lots of data and compute power for training these AI models. If you want to develop a I applications, you'll need to work for a tech company with access to pre trained and models from third party providers. If you just want to use add tools to improve your efficiency, then you can work for anyone provided they encourage the use of these new AI enabled tools . Ultimately, you need to decide what you want to do with AI before he can choose your career path. Fourth, get into the I value stream. You don't need to work at Google to make a good living in her new A economy. However, you do want to be part of the value stream or the ecosystem that's built on top of these new technologies. This could involve working for tech companies in horizontal markets that are positioned within the I value stream. For example, companies working on the Internet of things, big data, virtual reality, augmented reality, robotics and drones. Or it can involve working for vertical industries built on top of a technology's. Essentially look for industries that generate lots of data to train and models, or use an models to improve their existing products and services. Finally, focus on the uniquely human aspects of your job. Avoid specializing too deeply on the task that could be easily automated. These include task that air simple, repetitious, error prone or dangerous. Instead, specialize on the aspects of your job that cannot be easily automated. These include aspects like human interaction, creativity, compassion and establishing trust. These were the task that will still remain when all of the mundane tasks have been automated away. To recap our second recommendation, upgrade your career for a I determine if your job is at risk of automation. Decide if your company is at risk of becoming obsolete. Choose an act career path, get into the add value stream and focus on the uniquely human aspects of your job. 5. Invest in an AI-first Economy: Step three. Invest in an AI first economy. In this module, you'll learn why it's important to invest in our new AI economy. In addition, you'll learn what investments you should be making now to ensure your success. Who will be the world's first trillionaire? Who will win and who will lose in the new AI economy? During the agricultural revolution, we had visionary societies like the Sumerians, Egyptians and Chinese. They all capitalized on the key technologies of the agricultural revolution. As a result, they became some of the largest and most powerful civilisations on earth. During the Industrial Revolution, we had visionaries like John D. Rockefeller, Thomas Edison and Henry Ford. They all capitalize on the key technologies of the industrial era. As a result, they became some of the wealthiest and most influential people on the planet. During the information revolution, we had visionary companies like IBM, Microsoft and Google Veil capitalized on the key technologies of the Information Age. As a result, they became some of the wealthiest and most powerful corporations on the planet. During the A I revolution, there will likely be future visionaries. They will also capitalize on the key technologies of the age of AI. As a result, they will likely become some of the most wealthy and powerful people, businesses and governments on the planet. In fact, many experts predict that the world's first trillionaire will likely be created from wealth generated by AI. The AI revolution will likely have a significant impact on our economy and capitalism as we know it. These changes will require that individuals, businesses and governments need to adapt in order to function in an AI first economy. First, we're seeing a shift in returns to Capitol versus returns to labour. Returns to Capitol are essentially how much money you can make by investing in capital assets. These include investing in machines, software data and more. Returns to labour are essentially how much money you can make by soliciting your labor for income. This includes physical labor, knowledge, work and highly specialized labor. Over the past few decades, we've seen a continuous upward trend and returns to Capitol. As a result, the value you received from investing capital assets continues to increase. On the other hand, we've seen it continues decrease in returns to labour. As a result, the value that you received from each hour of your labor continues to decrease, Essentially, labor is becoming cheap and automation is becoming highly profitable. This phenomenon is referred to as the great decoupling. Essentially, productivity in the USA continues to rise year after year. However, somewhere in the 19 seventies, labor compensation broke away from the productive ity gained trend. This diverging trend will likely continue and become amplified with further AI automation. Second data may likely become one of the most valuable resource is in our information economy. Those that have the most data and the ability to enable AI with data will wield tremendous power in her information economy. In fact, their data sets that existed day that are currently valued at over a $1,000,000,000. Think about that. That's just a bunch of ones and zeros in a computer somewhere worth over a $1,000,000,000. Third, the A I revolution will likely lead to a significantly more non linear economy. Those with smart machines will have even more power, and those without smart machines, unfortunately will likely have even less power. It will become progressively harder for individuals, small businesses and even some governments to compete with large established tech companies . How should you invest in an AI first economy. What should you be doing today to capitalize on a I automation first, before you make any other kinds of investments, be sure to invest in yourself first. The best way to leverage your time, money and resource is is to invest in your education and your career. We've already covered this in depth in the previous two modules. However, it's important enough to be stated again. The best investment you can make right now is an investment in yourself. Second, invest in and solutions to solve real world problems. No matter who you are. There, AI solutions available today or soon will be. That can solve a wide variety of problems that you face on a daily basis. If your business owner you can use AI to improve business operations, invest in a I to make better decisions, build smarter products or automate manual labor. If you're an employee or contractor, you can use a I to increase your own personal productivity, investing off the shelf productivity enhancing tools that will automate the parts of your job that air monotonous, repetitious or inefficient and outside of work, we can use AI solutions to make our lives more enjoyable. There are many AI products and services today that can simplify your life and eliminate chores that you don't enjoy doing. However, you need to let economics drive these AI solutions. The benefit you receive from an AI solution must be greater than the cost. Automate and maintain that solution. Otherwise, it's not a worthwhile investment. Third, don't depend solely on your labor for income. Your labor is going to become progressively less valuable as we automate more jobs. This includes manual labor, knowledge, work and even highly specialized flavor. Instead, you need to begin putting your money in tow. Wealth generating assets. These include investing in companies, selling your own products or providing automated services. Your labor can only make you money while you're working, so most people are only making money roughly eight hours a day. Hover wealth generating assets could make you money 24 hours a day, so those that invest in wealth generating assets are essentially making money even while they sleep. Fourth, invest in the economy as a whole. On balance, the A I revolution is ultimately going to lift the entire economy you don't need outsmart the markets to make money in this new economy, you just need to invest in the economy as a whole. Now it's important that a note that I'm not a financial advisor, so I can't offer you any specific financial advice. However, what I can do is tell you about my own personal investment strategy so that you can do your own research and come up with an investment strategy that works for you. First, I diversifying my investments to reduce my overall risk. I do this using index funds with very low expense ratios. For example, I use Vanguard's Total Stock Index fund and the World Stock Index Fund Index funds. Spread your investment across the entire stock market to minimize your overall risk. Essentially, the entire global economy would have to collapse for me to lose all of my money, and if that happened, we'd probably have much bigger problems on her hands. Next, I buy low and I hold all of my investments. I don't day trade, speculate short cell or try timing the market. Instead, I invest regularly in my index funds. I put extra money in when the markets slow. I keep all of my investments long term, and I re balance once a year. Finally, I have a safety net. During economic downturns. I have just enough in the bond market and semi liquid assets to cover me during a recession . If I should happen to lose my income, and I progressively grow the size of the safety net as they get closer to retirement during the years that I would likely need it the most. It's a ridiculously simple yet highly effective investment strategy endorsed by many of the top experts in the world. Fifth, invest early for compound growth. Exponential curves like the growth of GDP per capita in the USA, start out slow in and explode quite rapidly. The sooner you invest in the economy, the better off you'll be exponentially the next. Google's, Amazon's and Microsoft's are out there now or soon will be, however, you don't need to find them yourself. Your index fund will find them for you when the time is right. You just need to invest in the whole economy now so that your investments will reap the rewards of long term exponential growth. To recap our third recommendation, invest in an AI first economy. Invest in yourself first invest in A I Solutions to real world problems Don't depend solely on your labor for income, Invest in the economy as a whole and invest early for compound growth. 6. Use AI Responsibly and Ethically: step for use ai responsibly and ethically. In this module, you'll learn about the legal, ethical and social issues being created by modern A I. In addition, you learn how you can use AI responsibly and ethically to the benefit of our whole society . With great power comes great responsibility. During the previous technology revolutions, humans gained access to new superpowers. In many cases, these new superpowers were abused often to the detriment of many less fortunate individuals . Agricultural societies gained the ability to raise large armies. They often misused this new superpower to acquire new land, enslaved human labor and subject gate. Entire civilizations. Industrial societies gain the ability to mechanize warfare. They misuse this super power to control resource is maintain colonies and expand their political influence. Information societies gained the ability to wait. Cyberwarfare. We've definitely misused this new superpower with mass surveillance, industrial sabotage, an election tampering in the A I revolution. This situation will likely be more of the same. We're going to discover some amazing new superpowers in the next few years. However, there will be some people will try to use these new powers for their own self interest in personal agendas with technology revolutions were like Children getting her hands on a sharp object for the first time. We typically don't learn our lesson until we've cut ourselves a few times. The difference with a I is that we might not get a second chance to learn from our mistakes . With great power comes great responsibility. And with a I, we have the greatest responsibility that humankind has ever known. The emergence of modern A I has led to some rather interesting legal, ethical and social issues in recent years. For example, we now have facial recognition systems throughout our cities that may be violating a right to privacy. We have a I generated advertisements that use a consumer's behavioral profile to manipulate their purchase decisions. We have text generation software like GPT three, which congenital eight propaganda and fake news on an unprecedented scale. We have deep fake technology that could be used to impersonate politicians, celebrities and executives for nefarious purposes. We have deep new technology that can digitally remove a person's clothing without their consent and has been used for blackmail and exploitation, and we have semi autonomous weapons that are very close to becoming fully autonomous weapons. These are just a few of the current legal, ethical and social issues that we're now facing with modern AI. However, they're much more advanced and sophisticated AI technologies just over the horizon. Given this, the number and severity of these ethical issues is likely to increase significantly in the near future. To put it simply, we're gonna have some very difficult ethical issues to deal with in our lifetimes. For example, what does privacy mean In a world with constant and pervasive AI surveillance? We currently have very little privacy, and we're about to get a lot less. How do we avoid bias and discrimination in our AI models? It's easy to create biased and models that will directly impact the lives of millions of people. Even more concerning should we allow AI to be weaponized? Should we ban fully autonomous weapons before we enter a new AI arms race? And if we do, how long until a conflict Pressures of government toe override this directive? How should we allocate? Resource is in a post human labor world. Some economist suggests that we need either a guaranteed basic income, a negative income tax or a social stipend. But how do we pay for that? Should we tax robots in order to offset the inevitable unemployment from automation? How do we even begin to determine the true value of each robots labor in order to tax your labor appropriately. And if we tax robots, what right should they have in our society? I mean, we fought wars over the idea of no taxation without representation. What will the machines or the capitalists that own them demand in return for paying the bulk of all taxes in the world? It's pretty clear that we have a lot of ethical questions that we need to answer in the coming decades. The most important of these ethical questions, though, is what does this all mean for humanity? What is their purpose in a world where machines do all the work of real economic value? Does this technology set us free, or does humanity eventually become obsolete? How do you use a I responsibly and ethically what should you be doing today to ensure that we don't misuse or new AI superpowers? First, start asking the difficult questions. Now if you haven't spent any time thinking about any of the ethical questions that had just posed, then you're probably not prepared for what's rapidly approaching. You don't need to spend all day philosophizing about the legal, ethical and political implications of A. I will leave that up to the lawyers, philosophers and politicians. However, you do need to be thinking about what your core values are and whether they agree with or conflict with these new AI created dilemmas. Each of us needs to know where we stand on these key issues before they take us by surprise . Second, avoid bias in your AI models. It's very easy to accidentally or intentionally create bias in your AM models. If you train a model with bias data, you'll get biased results. As the old saying goes. Garbage in garbage out. This creates feedback loops that can reinforce and amplify existing socioeconomic divisions in our society. This will be especially true when these algorithms begin to impact the lives of millions of people. Third, provide transparency in your AI models. If you automate a decision with a I, you should make that decision making process as transparent as possible. If a I becomes a magic black box, I cannot be questioned. Then how can anyone get any recourse when it makes an incorrect decision. As a result, I recommend that you always use the simplest tool that effectively solves a given problem. Don't use a complex, deep neural network if a simple decision tree classifier will suffice and when possible, use explainable AI tools explainable. AI provides diagnostic explanations for how and why a specific decision was made. Ultimately, ask yourself, Could you explain to a judge how this AI model made its decision? If you can't explain it or the judge wouldn't understand your answer, then it's not transparent. Fourth, protect your private data from abuse. If people knew what I could do with their personal data in the right algorithm, they'd probably be a lot more cautious. However, the general public is currently quite a few steps behind data scientists in this domain think about what data you're willing to make public and protect everything that you want to remain private Onley. Entrust your personal data to organizations that you trust can and will protect your privacy. Finally, demand more from our leaders. We have several AI related legal, ethical and social issues that we need to address in the very near future. Unfortunately, many of our politicians have very little understanding of AI and thus are unable to make effective public policy decisions. You need to choose representatives that understand AI and how it can either be a benefit or detriment to our future society. In addition, we need to choose the best corporations to lead our society in the right direction. You vote for these corporations every time you spend your money on their products and services, vote for them with your dollars and hold them accountable if and when they fail us. To recap 1/4 recommendation, use AI responsibly and ethically. Start asking the difficult questions now of wood bias in your AI models. Provide transparency with your model's predictions. Protect your private data from abuse and demand more from our leaders. 7. Adapt to What Comes Next: this leads us to our final recommendation. Adapt to what comes next or become obsolete in this module. We're gonna look at the big picture for a I and humanity. Our time frame will extend beyond our careers into retirement and beyond, and we're also going to get a bit more philosophical. A swell, however, will keep things practical by learning how you can adapt to whatever comes next to avoid becoming obsolete, what becomes obsolete versus what becomes the norm? Why do some aspects of society disappear into obscurity while others become so common that we take them for granted? During the previous technological revolution, something's became obsolete while other things became the norm. During the agricultural revolution, hunter gatherers and nomadic tribes became obsolete while farmers and cities became the norm. During the Industrial Revolution, slave labor and draft animals became obsolete while factory workers and industrial machines became the norm. During the information revolution, human computers, an analog data became obsolete while office workers and digital computers became the norm. During the A I revolution, the question naturally becomes what parts of our world will become obsolete versus what new things will become the norm. No matter how things play out over the next few years. In the long run, there are really only three likely pass forward for humanity. Ai inhumanity peacefully coexist together forever. AI destroys humanity if we don't accidentally destroy ourselves first, or AI and humanity eventually merge and become one and the same. If you really think about it, there really aren't any other real possibilities in the long run. Given humanity's historical track record in similar situations, it's unlikely that humans will be able to peacefully coexist with AI forever. We've simply seen too many past scenarios where a sufficiently advanced civilisation displaced the indigenous population. It's actually much more likely that will either destroy ourselves first or a. I will eventually displace humanity. Now, this might seem good for AI, but it definitely would be bad news for US humans. So given these three options, the most realistic and hopeful path forward for humanity is that we eventually merge with their technology. Essentially, we merged to the extent that humanity and our technology become indistinguishable. This idea may seem far fetched now, but these cell phones in her hands are already an extension of our brains and the younger generation is ready and willing to have them directly connected to their minds if and when the technology becomes available. In many ways, were already augmenting our human bodies and minds with manmade technologies on a daily basis, for example, wearable devices, artificial limbs, pacemakers, contact lenses, hearing aids and more. In the next decade and beyond, it's likely that will be even more deeply and continuously connected to our technology. For example, Coming soon are lightweight, augmented reality glasses, implantable bio T devices and, eventually, brain computer interfaces. It may sound strange, but we're likely one of the last generations of Homo SAPIENs to inhabit the Earth. Whatever comes next will likely be very different from what we've known for the past 200,000 years. How do you adapt to what comes next to avoid becoming obsolete? What should you be doing today to prepare for whatever comes next? First, embrace change. The Greek philosopher here client is famously said change is the only constant in life. Technically, he actually said Panta Rei, which translates to everything flows, but I think you get the point. If you find change, you'll continuously struggle your entire life as the world changes around you. Not only will you struggle with change, but you will inevitably lose every time. If you embrace change, you can adapt to what comes next. Adaptability is highly valuable from an evolutionary perspective. This is why it's a key pillar in the agile manifesto in many philosophical and religious world views. Second, be skeptical but not too skeptical. In the post truth era, it's really easy to be duped into believing incorrect information. Skepticism is the natural antidote to this intellectual disease of modern society. In addition, you need to be skeptical of your own beliefs as well. Always question and continuously update your beliefs based on new evidence as it becomes available. This idea is the essence of the scientific method. Third, keep an open mind. One of the worst things we can do today is get ourselves stuck in our own dogmatic worldview. The information bubbles we create in our society produced echo chambers that reinforce our own confirmation bias. So it's important that you're constantly confronted with alternative perspectives to challenge your own beliefs. Also, you need to keep an open mind when new information disagrees with your current beliefs. It's quite likely that a good portion of your belief system. Maybe come obsolete yet within your lifetime. And if you're not sure what I mean, just ask your grandparent's how much the world has changed around them since they were Children. Fourth, pick your battles wisely. There's some things that you should stick to your guns on and other things that you should be more flexible about. Figure out what your core beliefs are and fight for those beliefs when necessary, however, be flexible and open minded about everything else. Ultimately, when picking your battles, just make sure that you end up on the right side of history. Finally, be mindful. Our brains evolved to survive in a very different environment than our modern, technology driven society. As a result, much of our suffering today is caused by this conflict between human nature and our technology. Mindfulness is how we minimize this suffering and learn to peacefully coexist with our technology. Honestly, making the commitment to practise mindfulness daily is probably the smartest thing I've done in my adult life. I highly recommend it to everyone. So to recap our final recommendation, adapt to what comes next or become obsolete. Embrace change, be skeptical, but keep an open mind. Pick your battles wisely and be mindful 8. Conclusion: Finally, let's wrap things up and learn where to go for more information. First, I have several online courses that can teach you about artificial intelligence, data science and machine learning. I recommend starting with these three courses to learn the basics. You can find all of my courses at the URL below. And if you'd like free access to any of my courses, just send me an email and I'll provide you with a 30 day free trial code. Second, be sure to check out my website. I have tons of free articles, videos and courses on this topic and more. I also offer on site training and consulting services to help executives, teams and entire companies get started with a I data science and machine learning. Third, I encourage you to engage with me and others in the AI learning community, so please be sure to rate this video. Ask questions in the discussion forum, send me comments via social media and please provide me with any feedback you have on this course. I take your feedback very seriously, and I use it to improve each and every course that I create. Fourth, to summarize my five recommendations to prepare your career for a I. R. Educate yourself about AI. Upgrade your career for A I invest in an AI first economy, use ai responsibly and ethically and adapt to what comes next or become obsolete. Finally, how does your story end? Technology is inherently a moral. It is neither intrinsically good nor evil. The same technology could be used to take mankind to the moon or it could be used to propel warheads into cities. As a result, it will be up to us as a society to choose whether we want to use a I to make the world a better place for everyone or to use it for our own power, profit and control. The choice is ours to make. What will you choose? Thank you for joining me for this introductory course on preparing your career for a I hope that you found this information valuable and then does has helped you take your first step forward on your journey. Please be sure to keep in touch by my website and social media, and I hope to see you again in another course in the near future.