Jobs of the Future

0:01A skill is not a static concept. IBM reported that technical skills have a shelf life of about two and a half years. Four out of five CEOs say that the number one inhibitor or one of the top few inhibitors to their growth is finding people with the skills they need. Jobs are going to become richer. About 80 % of jobs in the US and similar in other countries that pay well say they require a college degree. But in our country, actually only about a third of Americans earn a college degree. I think this technology will impact almost every single job out there in some way. Having a college degree is life -changing, but it cannot be the only way to change your life.

0:41Technology understanding is becoming relevant for everyone in the company. This trend is only going to continue. The number of searches for how to become a data analyst was the number one search of any how to become in the world last year. Consider this. A staggering 60 % of jobs that exist today were non -existent in 1940, and with the relentless progress of software eating the world, jobs have undergone a profound metamorphosis. Plus, with AI taking center stage in 2022, people are hard pressed to identify industries that will not be impacted. But this is also not very new. Jobs have been evolving since the dawn of time.

1:24If you look at farming, around 1800 you add 90 % of the population working and farming, around 1950 the time that you just cited, I think it was down to about 20 % and today we're seeing about 1 .5%. So as we enter 2024, what lies ahead in the future of work? What skills will fall to the wayside alongside their long line of ancestors, and what skills will prove indispensable for success? Today, we're joined by Kai Romalt and Lisa Gabelber to talk through these fundamental shifts and how they might impact everything from hiring to degree acquisition to global participation. Kai is a CEO of Udacity, which provides online programs that cover everything from deep learning to autonomous systems to cloud computing, but also topics that you may not have heard of, things like sensor fusion, self -healing architectures, or data governance.

2:16Lisa, on the other hand, hails from Google where she built their program, Grow with Google that deploys career certificates. Grow with Google has graduated over half a million people from their courses that include programs around cybersecurity, data analytics, UX design, and more. So, in a world where technology is moving at an unprecedented pace, what will the jobs of the future look like? And how might we prepare for them? Let's find out. As a reminder, the content here is for informational purposes only. Should not be taken as legal, business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund.

2:59Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details including a link to our investments, please see A16Z .com slash Disclosures.

3:15Why don't we start with a statistic? I'd love to just get your raw reaction to this. But a recent report from economist David O 'Tour shows that actually 60 % of workers in 2018 have jobs that actually did not exist in 1940. So over the last 80 years, most of the jobs that we have today and even more so the job growth in that period came from completely new jobs. What's your take on that? I think it's absolutely amazing. Personally, I think it's amazing and I'm really grateful to live in such exciting times. It's also not surprising because if you look at the history and the longer run, we've always seen those kind of changes and those kind of changes fueling, then the societal changes.

3:59If you look at farming around 1800, you had 90 % of the population working and farming. around 1950, the time that you just cited, I think it was down to about 20 % and today we're seeing about 1 .5%. So this change is really what allowed us to take the human capacity and then apply it to new problems. And a lot of the things that we see around us today, even kind of our jobs that we're doing here, recording podcasts, things like that, those wouldn't have been possible if everyone would still work in farming, right? I think AI, as such, will absolutely accelerate this once more, and we will see the same effect, we'll probably see it in even higher pace than what we see in historically.

4:43As I said, I'm excited about it. I do hope that that excess capacity, that capacity that's being created, will be used and applied to address some of the big challenges that we have in our society today, like climate change, like mental health epidemic, but I think that if we didn't have changes in the job market, we wouldn't be able to address new challenges and new problems. Yeah, I think you mentioned the term pace. Things are moving so quickly, and we have seen this phenomena where jobs, occupations, the world has changed over time, but maybe the dilemma or the juncture that we're at that people are calling out is the idea that maybe things are moving so quickly that certain jobs are being wiped out more quickly than new jobs are being created.

5:29What's your take there and specifically how quickly certain skill sets are going in Vogue and then out of Vogue or other skill sets that still exist today that can hold with time? Recently, IBM reported that technical skills have a shelf life of about two and a half years. But I think that the way we need to look at these things that a skill is not a static concept. If you acquire a technological skill today or whether you've acquired that skill five years ago is going to be fundamentally different because the tool that have changed, the capabilities in the market have changed, the whole environment has changed or think about digital marketing strategies that worked five years ago might not even be applicable anymore, not doable anymore today.

6:13I can confirm that. And I think that the way we have to look at it is we have to look at acquiring skills and about saying current in those skills. So I think it's becoming more flexible. We need to be more flexible because as I said, it's not static. How do you think about what kind of education is then required or how to design an educational platform given that pace of change, given the fact that maybe we are in a new environment that is very different to, let's say, 40 years ago where someone could acquire a skill set and remain in that occupation for decades on end. I think what it means for us is that we have to provide the content that we have in a more flexible way.

7:00And, you know, the traditional model of universities is learning all the education happens at the beginning of the career, and then it has to last over the span of a whole career. With the data degree that was invented at Udacity, you have a shorter form that focuses on a set of skills that make you employable. Where we are going from there now is that we're making short -term content that can be combined in different ways that allow people to train themselves up and prepare themselves for maybe something like a nanodegree, but also afterwards to say, okay, how do I say current in the skills? I mean, on that note, how do you think about what is worth creating that will stand the test of time?

7:41Or are you just on a completely new iteration cycle? For every six months, you're having to come up with new material, because if you think about the alternative, let's say university, those spend years developing a curriculum to the point where in certain fields, it may no longer be relevant or at least won't be at the cusp of innovation there. I think you're making exactly the right point. So it's really about having a high content velocity. So first of all, one of the things that we've done is rather than thinking about something like a non -degree as like one static concept that lives from beginning to end.

8:20We're building it in a different way now that we've disaggregated and we take it down to a lesson level and then these lessons combined make up the degree. The difference is that traditionally what you would do is you would have lesson one and then you would have lesson two that builds on lesson one and lesson three that builds on lesson two and lesson four that build on lesson three. The way we build the content now is that every lesson stands for itself, which means we can recombine these lessons in any way necessary. But what we can also do if we realize that there is a lesson that's not relevant anymore, we can just pull it and we can replace it with a different lesson.

8:58So it's really about flexibility in how you can reconfigure your content all the time and a high content velocity that you create the amount of content when it's needed and move it in and out as it's relevant. As new trends show up and speaking of trends, I mean, I think certain courses, if someone were to go to Udacity's homepage, they'd see a lot of things that they would expect, especially with the AI wave. You've got things like deep reinforcement learning, AWS machine learning. Those were no surprise to me, but you also had some courses that I was a little surprised to see. You've got sensor fusion, data governance, identity access management, self -healing architectures, and maybe I'm just out of the loop.

9:39But tell me a little bit more about how you identify whether a skill set is worth adding to the platform, what datasets are you looking at, and also are you seeing any discrepancy in supply and demand? Because there are these trendy titles that a lot of people are jumping towards, but it does feel like there are maybe some of these more underground trends that aren't on people's radars. Yeah, we have about 140, 14 ,000 companies that we work with. Plus, we have a large amount of individuals and we take a lot of cues from our customers, from our partners. We also see based on jaw boards and analysis that we do, we see kind of what are the skills that are trending that are needed and then we build courses to address those.

10:21In terms of mismatch, what we see a lot in the market, for example, let's take the topic of generative AI. We're seeing a lot of content being out there that's descriptive, but what companies are really looking for is the practical application of it. So I think that it's really about answering those questions on how can I and my company practice it, how can I have the practical element of it? What you're pointing at to a degree is it sounds like it's not just training new folks on being the machine learning engineers that develop the models, but also since this is such a broadly sweeping technology that basically anyone in an organization can benefit from understanding how to incorporate AI into their jobs.

11:08Am I understanding that correctly? It's interesting because you're absolutely right. Historically in technology, you see people looking for very deep skills. Today what we see is that we have very high demand from a broader base in the company. So where it's really about, I would say, technology skills and technology understanding is becoming relevant for everyone in the company. We now have two different types of content. We have the deep learning content, and we also have content that allows managers and people in the company to become fluent with the technology. without having to go super deep into the technical skills, because maybe they have technical teams.

11:48All what we also see is that we have today a lot of tools where technical requirements are just not needed anymore for the users because you have low -code environments, no -code environments. So yeah, we're seeing that the barrier for more advanced technical skills that are coming down, just as an example, today you don't need necessarily explicit design experience anymore to work with tools like DALEE or mid -journey, because these tools can do a lot of that hard work for you. But what's really important is that you are able to use them and have enough knowledge to know how you can apply these tools in your context.

12:25Yeah, there's something counterintuitive there, which is, I think as these technologies advance, the natural reaction is for people to say, oh, all the foundational stuff we no longer need because it's being abstracted. But to extend what you're getting at is actually, it's really useful to understand basic code. It's really useful to understand basic design principles and it's really useful on mass. It's useful for all of us as we will get more exposure to technology via AI to have that foundational layer. And when we talked originally, it sounded like you're actually seeing that in your data, right?

12:58We're actually surprisingly enough. The foundational stuff is what is trending or a lot of people are reaching for. You're absolutely right. We've seen in the last year about a 33 % increase in AI related courses. And we had exactly the same increase in foundational courses related to AI. So something like Python programming. So we can see that from the learners that we work with, they want to do the AI application courses, but they also want to make sure they understand the basics and the foundations. Are there any other jobs that you're seeing sprout up with time that you just think are really fascinating and could be the equivalent of like the social media manager, the UX designer, the product manager, that were kind of like the last generation.

13:42They're still extremely relevant. But if you think about it in the early 2000s, those jobs didn't exist, right? As we talked about at the outset. And also, they're the kind of jobs that we probably just truly could not have predicted, right? They've manifested in ways that seem so obvious today. But back then, someone would be like, wait, there's someone who like studies, help people engage on a screen? Yes, I think there's a lot of the obvious jobs that are going to... I'm sure we'll see chief AI officers. We'll see lots of AI product managers that will manage tools. But I do think that this is what makes this technology different from a lot of other technologies that we've seen before.

14:21Is that I think this technology will impact almost every single job out there in some way. And I think very often the effect that we're going to see is that for certain roles we will need less people to do the same job that's from engineers where you have GitHub Copilot where to design as a copywriter that are going to use some of the tools but it means that the jobs themselves are going to change. So I think people will much more focus on quality checking and doing more meaningful tasks so the jobs will be augmented by AI and then people will function as data the stewards, they'll look at the efficacy of AI, and they will make sure that the quality of level of the results is where it needs to be.

15:09So it's a little bit if you want to compare it to an individual building a car to a manufacturing line where now one person just oversees a much bigger process rather than doing every step of the way themselves. It's going to become a very key tool. Yeah, absolutely. Our founders, Mark and Ben, and record an episode about Hollywood and they have this section where they are talking about within the entertainment industry, you have producers, you have actors, you have screenwriters, you have all of these people who participate in the production of something and they were talking about how actually, yeah, you could have any one of those jobs then work with their team of AI's to basically have their own production agency, right?

15:53Where basically they're able to do all of those roles through the help or augmentation of AI. So it's exciting to imagine that to your point, every job is going to be impacted by this or most jobs. But that actually in many ways makes each job more dynamic, right? Instead of it being in a silo, a designer, a developer, and a product manager can all, in some way, fuse into one IndieHacker, right? And that IndieHacker can do so much more on their own. And if you think about it, we just talked about like a car manufacturing process. It is a lot more interesting as a job if I can oversee a machine that makes a whole car rather than just having to be somewhere where I just have to do one screw the same screw every day.

16:35So jobs are going to become richer. They're going to become faster paste. So I think intensity as it's always been is going to increase. Paces going to increase. But the jobs are going to be more meaningful and richer than what we have today. And the exciting part, if we use the car analogy and extend it, is when someone can not only oversee a whole process of creating a car, but all of a sudden we have a self -driving car or a flying car. And I know that sounds facetious to an extent, but it's like, how can we use AI not just to build what we currently can in a different way, but also to build fundamentally new things, which I think will come, right?

17:11The same way that the reason that UX designers or app developers exist is because now we have apps. Those did not exist in the past. Let's talk about other trends like regional access. I think that's something also that is intersecting this AI wave where you have not just people in North America participating in these new technologies. You have people truly all over the globe and I think this is something that you've seen also with Udacity. So maybe you could speak to that level of access and the integration of people from all over the world participating. First of all, I mean technology is pretty amazing, right?

17:46We're historically you had to be in a specific location to do a job and now there's a lot of jobs that you're able to do from anywhere in the world. And one of the programs that we particularly proud of is we're working with the Egyptian government. Egypt has a foreign currency crisis, so they came to us and we're looking for us for ways of how they can solve this. And we designed We find a program where we are training people in Egypt in technical skills with the goal for them to become freelancers in the end or some of them, a portion of that. So they generally want to create a more tax -heavy population just to give you an order of magnitudes with this program.

18:29It's been running for two years. We've trained up about 150 ,000 people in Egypt now. And then a portion of those people went into freelancing. So we also trained them into how to access the freelancing market. from their portion is working for global companies. That's now bringing annualized about $200 million of foreign currency back into Egypt. Just through that program. Just through that program. So number one, it's interesting because again, jobs become globalized in a whole different way, where it's not about you don't have to take a whole factory and move it from one country to another one, but like job markets now open up in a way where people from the whole world have access to it.

19:07If you think about it, now you have a single mother in rural Egypt that has access to tech gigs that she can work in. So if you think about what that means, not only for her, but what that means for her children, what that means for the community around her because obviously there's money coming in that she can now take and spend in the local community where she lives, the fabric of society that we've got, where you have people that historically have been strong and could dominate, that's because they have access to jobs. Now that's different. So the level of confidence that you give people and the liberties that come with that, that's amazing.

19:51And as I said, we're very proud to do that. Egypt is one example. We do similar things in a number of other countries. We're very proud to have trained the first female self -driving car engineer in Saudi Arabia. Amazing. And it levels the playing field in an incredible way and that from a geographical perspective, from a gender perspective, but also people that physically might not be able to drive to a job, but now can do it really well. From truly anywhere. From truly anywhere. How should companies be thinking about this? Because something that comes to mind as you're describing all of these people becoming educated and skilled in ways that they hadn't been before, the systems to which people are higher seem a little outdated.

20:35If I'm just thinking through a like how we look at resumes, what signals we look for, whether it's a specific kind of degree or if they went to a specific kind of school, but also I'm thinking through an interview process if someone's been trained in that way, right, to be able to command that confidence that you just described. So tell me a little bit more about what you're hearing from companies. Our company is rethinking how they're hiring people or what signals they're looking for as they now have an increasingly global talent pool. I think this is something where we're only standing at the beginning of it.

21:11If you look at the numbers of freelancing, gigs, etc. that's vastly increasing. Companies are really now in the process of learning of how to deal with it and how to use it and how to leverage it. But at the end of the day, it all comes down to practical application. And what's important is that a company is able to understand what is the set of skills and capabilities that they've got and what is the set of skills and capabilities that they need in order to get their strategic priorities done. The best companies have understood that learning is not a benefit for employees and learning is not a kind of nice to have, but it's really about up -skilling programs that have a tangible impact on the business.

21:58So how do I connect a. My strategic agenda to the skills that I need? And b. How do I make it relevant for employees? How do I measure the skills and capabilities that people have? And how do I turn that into a currency inside the company? The big question around upskilling is it's all about the why. Because if you have an online learning platform, the learners are ultimately sitting there and they're saying like, I'm going to log into this platform now, or am I going to log into Netflix? Or am I going to play soccer with my kids? We're going to do YouTube. The question that you really have to answer is, why should learners be on the platform spend their time and learn the skills?

22:40and that's where companies can come in by really turning skills and capabilities into a currency, where you'll see in job descriptions where the exactly highlights what skills capability is qualifying you for a job, how you can show that you have gained them and can do them, and then you get that connective tissue. All right, we'll return back to Kai, but here's Lisa adding her perspective on what she's seeing in the marketplace for jobs, including how AI is impacting that landscape. But first, her take on the difference in people with traditional degrees in the jobs that require them. About 80 % of jobs in the US and similar in other countries that pay well say they require a college degree.

23:23But in our country, actually only about a third of Americans earn a college degree. So that leaves two -thirds of our country basically locked out of every good paying job. And so we said, well, this is a big, important problem that needs to be solved. And for sure, having a college degree is life -changing, but it cannot be the only way to change your life. And so we set out to solve this problem of how could you help more people get access to great jobs by training and certifying their abilities to do those jobs? To your point, it does feel like there are a couple things that, But if you put them on a resume, they just greatly enhanced your ability to get to the first interview.

24:06And so are you seeing that reception where things are changing both on the talent side in terms of taking this chance and in pursuing this instead of a full time degree or also on the company side being receptive to hiring these folks? Our goal is economic mobility and economic stability for people. And the only way you can achieve that isn't by training people. It's by helping them get a better job and a better career. And the only way to do that is to get employer buy -in. So even from the very beginning, we were very deliberate about involving employers. So we looked at what are really in demand career fields that are projected to keep growing, where Google has unique expertise, and where we knew we could teach people in a relatively short period of time, how to become proficient for entry -level jobs, and where we could do that completely online.

24:59Because we really want to meet people where they are, which is working Americans don't control their schedules. About a quarter of Americans don't even know their schedule for the following week. And so they need it to be online on demand. So we vet the curriculum with top employers. And actually what we found, which was really fun and exciting for us, is that they were willing to contribute content. OK. So a great example is we have a data analytics certificate and Deloitte, who hires tons of data analysts, gave us the assessments that they used to test for mastery of SQL and R, and they let us build it right into the certificate.

25:35And then we became a preferred hiring credential at Deloitte, because they knew what we were teaching was exactly what they were hiring for, and that we were testing for mastery in the same way that they would. Exactly, and I mean, I feel like these companies, it makes total sense, because they would end up doing that training anyway. And so the incentive is there for them to say, hey, yeah, actually help us train these folks and we trust that if you're using our material, then we're gonna get the folks that we need. Let's talk about some of those trends. I like that you really narrowed down. It has to be online.

26:04It has to be done in a specific period of time. And actually just real quick, how quick are we talking? It's all self -paced. Usually have from 100 to 150 hours of content. Some of those people finish in somewhere between three and six months. Great. And so what jobs have you incorporated the program that kind of fit that bucket that you said is important today, but also is going to be just as if not more important looking ahead. Yeah. Well, research shows that demand for data analytics skills is growing 15 times faster than the average demand for other skills. And we see it on the other side from people looking for new careers.

26:44The number of searches for how to become a data analyst was the number one search of any how to become in the world. Really? Last year. Yeah. So, all things. Apparently, a lot of people want to become data analysts and we can see the demand from the employer side as well. So data analytics is one example. Another good example. Just a few months ago, we launched our cybersecurity certificate. Many things. And we all know, unfortunately, the cyber attacks keep happening. As a matter of fact, they grew 38 % last year. So there's this giant gap between the number of cybersecurity jobs and the number of people who are already trained to do them in the US I think the number is 650 ,000 open jobs in cybersecurity.