Hello, everyone. I'm some of the engineering components, but I hope today we can come back into our human minds for a moment and think about how the individuals and the humans who are gonna operate in this new world are actually going to work, and how are they going to interact with these machines. So, let's first define the human cloud.

I know we've heard about many, many clouds. So, it is an emergent set of online digital marketplaces where talent and those looking to hire talent can find and engage with another in work. So, what this really is, it's more of a complementary ecosystem with a peer-to-peer equivalence of some of our corporate structures.

So, we have a few developing departments that are freelancers. You can call them gig economists, whatever you might wanna use, but the idea is these individuals are not tied in a full-time basis to any one firm. They operate in a liquid manner.

They go from place to place. They go from firm to firm and department to department. So, most of our human cloud is focused on IT, and that's pretty obvious.

It's easy to work remotely, and it's easy to have this access to the innovation, but we have a few other elements coming into the human cloud. For the most part, it's emphasizing human intelligence. So, the human intelligence tasks that we can still have with all the automation taking over a lot of our jobs, these are the roles that we wanna involve in the gig economy.

So, in 2016, we had about $50 billion in human cloud revenue. This is projected to exponentially increase over time just as all of our other infrastructures are going to change. So, let's talk about who these people are.

A lot of people assume that the gig economy belongs to the young people. The kids these days are playing around with their apps and their platforms, but for the most part, we actually have a good distribution of individuals working in this space. We have our baby boomers.

We have our experienced, lifetime's worth of knowledge individuals coming out of their workforce and advising in a consultant basis. We also have our young individuals who want the freedom and the flexibility, our millennials, our Generation Y, who hope to have some kind of travel slash lifestyle freedom in addition to their career paths. So, one thing we also notice about the people in the gig economy is that they tend to be more educated.

They tend to be more professional and technical. This makes sense. We have to compete against the machines, so we have to have a little bit more of our brain power involved in the actual usage.

So, like we were saying, gig workers, sharing economies and other terms we can use, telecommunic services, remote performance from anywhere around the world. We have a lot, especially in the IT element. On-demand access and coordinated talent.

So, there are a few companies right now that are coordinating this talent, and for anyone here that is entering the gig economy or has been in the gig economy, you may have used some of these platforms, and they include Upwork, Freelancer, Fiverr, and we'll go into the landscape a little bit more. But some of the characteristics of these platforms is that they facilitate peer-to-peer transactions. They coordinate end-to-end how the individuals are connecting, how they're communicating, and how they're actually achieving the interaction that's taking place.

How is the work actually being transacted? So, user-based feedback tends to drive most of what we do these days anyway. In the case of this, it's review systems. These are the things that we're all familiar with.

Flexibility tends to be the emphasis, and equipment tends to be provided by the providers. They may bring their own computers. They'll use their own landscaping materials.

They'll use their own tools to achieve the task. And the main role of these human cloud companies is to manage relationships, and that's really what we're finding is as the technology takes over a lot of our automated tasks, we as individuals, as self-organizing human beings, how are we interacting with each other now with all of these new tools? So, there are three types of human cloud companies. One of them is the online stacking platform.

So, a great example of this is Upwork. They're just in the economy alone. And basically, the platform connects individuals.

It offers them a project management tool, escrow. So, it offers a middleman that takes people out of the corporate space into a more free and contingent work basis. Online work services, on the other hand, tend to be more based on the service outcome.

So, this is where we have Uber. Uber, for example, the emphasis is getting to that place. You don't have to have a relationship with the individual.

Your driver may talk to you on the car, but you're not really that interested in what they have to say. So, the relationship isn't as important. Quite a few transportation, in particular, based industry consequences from this one.

And the last type of human cloud business is the crowdsourcing. So, there are two ways that you can crowdsource your work in human cloud. One is that larger projects get broken down by the platform into individual tasks and that get distributed across different freelancers.

And a lot of times, you sometimes have an individual moderator in the middle. Or the other type of crowdsourcing is a contest-based crowdsourcing, where you put out your project and everyone may submit some type of result or solution. And only one of them will win.

Only one of them will get rewarded. But everyone has put in some element of work. So, there are different ways to get talent out of the human cloud without having to commit to a full-time work relationship.

So, let's just look at some of the companies that are existing in the space now. The emphasis can fluctuate between the individual or the crowd itself. So, on our crowdsource side, we have companies like Mechanical Turk, which is Amazon, basically.

Amazon and a few of its alternatives. That is more on the crowd side. It kind of has more of a decentralized model.

You don't have too many individual building reputations. It's more about the skills themselves. On the other hand, you have the individual workers really emphasized on platforms like Upwork.

For example, for development projects, for technology-related items, we tend to have Upwork and there are a few more that aren't quite mentioned here. TopTel, Council. So, these are the liquid workforces that we are more familiar with because this is more of a telecommunications conference, but there are others as well.

And then we have online workforces. These tend to be more transportation-based. As of now, the top 10 human cloud companies are all transportation-based, but they are developing door dashes and things where you have other services complementary to the actual delivery.

So, depending on what the client is looking for is which platform they're gonna use, people tend to jump between platforms. So, we've talked a lot about the Ford's Industrial Revolution, Industry 4.0. There are different terms for it. And we have three key forces that are really influencing the new age.

And we have our disruptive technologies. We're gonna go into this in more detail, and I'm sure all of us are familiar with many of them. We have some new business models.

So, our traditional business models have been very centralized and very hierarchical. And then we have this emerging set of these startups, and we're all very familiar with them here, who are really disrupting the stability of the old models because they're operating without as much overhead. They're operating without as much baggage from previous infrastructure.

So, they're creating this alternative that's really kind of shocking some of the older companies. And then we have our empowered customers. Our customers are far, everything is more visible in the information age.

They have more access to details and each other's feedback and history of every object that they choose to purchase. So, their decision-making has become much more refined over the recent decade. So, some indicators that there's a change happening.

This is an evolution of our economy, and we have many companies that have gone under. We have about 50% companies in our country that have ceased to exist since 2000. 50% of today's S&P 500 is expected to also disappear.

We also have a high centralization of what's left in the market because these few companies that have developed ecosystem models new business models, Amazon and Google have really captured so much of the market that they're knocking out most competition. So, what is the problem? Why is this slow to develop in parallel to all the technology that we're developing? Why are our human being the same level of workforce management that we are allocating to our server networks, right? So, we need to have the same type of resource optimization between our human capital, our human labor. So, some of the issues that we see with adoption of the contingent workforce would be just management not being, just being a little confused, not quite understanding how to trust these contingent workers.

How do you trust someone to come in and work on your IP without any accountability? So, that's where the platform is trying to modify that comfort and try to add some understanding. Worker classification is a big topic. This has been around since Uber has been getting into their first lawsuits.

We have the idea of, do we consider them full-time employees? Are they temps? Do we give them insurance? Do they have to pay taxes? How do we actually classify these workers? And beyond this, how is the marketplace going to perceive what's actually being offered by the liquid workforce? Not everyone understands what this stuff is. Here we do, we hear these words, but the concept of big economy, of 5G, of IMT, these words are new in the market. And in Silicon Valley, they're not so new, but around the rest of the country, they're relatively buzzword terms.

So, sometimes self-evident, but let's talk about the benefits of a liquid workforce. And by liquid workforce, I'm saying people who are coming and going from the company without a full-time commitment to the engagement. So, we have low cost.

We don't have to commit to 52 weeks out of the year if you need someone for a very specific task. The overhead, you're not actually, not only for the individuals in their labor, but also for the equipment. They're able to buy their equipment, so why would they have to actually, well, you don't have to necessarily sponsor their workspaces.

On-demand skill sets, global talent pool, easy collaboration, and temporary operation scaling. If you wanna make a technical analogy, you have your elastic share, auto-optimize, elastic caching and such on your AWS networks. We should have a similar system in place for our human networks as well.

So, as we have 5G integrating manpower, machinery, and equipment, we have the development of 26 billion IoT devices coming up in 2020. So, as we, our seven-ish billion individuals are operating within this space, we have to have companies that are at their best in a virtualized, interlinked, and monitored world. So, in a nutshell, 5G has allowed us to create, or will allow us to create smaller computing units that are more efficient, and also to shorten the time-to-market.

Shorten the time-to-market, the latency of our supply chains is really the bottleneck of most of our operations. So, if we're able to shorten the time-to-market, we should also be able to create a more agile workforce to match this quicker and more fast-paced environment. And so, we have to think about the future.

So, a lot of times, we look ahead at what technology will do for us, the internet of everything, and this is the room, or this is the conference of people who are building the standards and building this future world, and we have to think about what we're designing. Are we creating a competition against the machines that we're designing, or are we trying to create a synergy? Are we trying to create some kind of collaborative, symbiotic relationship with our machines? So, the two outcomes that are, I guess, popularized would be the Terminator outcome, where we create our own replacements, and then we all disappear. And then we have the Iron Man outcome, where we create a human-machine interaction that allows us to augment one another, and allows the machine to augment our capabilities and our ability to think and to operate and to live our lives.

So, here are some of the technologies that have come up in the recent decade. I'm sure we're familiar with many of them, but they're all, so, Internet of Things, of course, we've seen how it helps with data sharing, and also, the rollout of Internet of Things. You've seen a lot of it coming into retail, we're coming into marketing, how you can connect people's location to what they're actually trying to purchase or interact with.

Beyond the fridge talking to the toilet and all of this, there are other ways that IoT can benefit us, of course. We have our automated vehicles, we have our distribution logistics, and this is another element of how we're getting things not just across Amazon's warehouse to our home, but also from one side of the company to another, from one branch, from one collaborator to another. Our artificial intelligence and machine learning, this is gonna be essential in how we design our intelligence in the future, because we ourselves are unique in certain ways biologically, so when we add this machine component, we have to make sure that it's complementary to what we are, because in the end, we are the users, we are the one, the machines serve us, we are not supposed to serve the machines, supposed to.

So, we have robotics, of course, repatriation of manufacturing is a big topic, politically, economically, the idea that when you have these automated production methods, the arbitrage of human labor is really one of the biggest issues in macroeconomics and how we're operating, we have our supply chains, which are so extended because labor is so cheap across the world, and if robots are at the same price universally, then we can bring things back into the native country. Digital traceability, this is really coming out with blockchain a lot of the times, which we'll talk about again, but the idea of trust and transparency as we create a more remote world, as we have people diversifying their work styles, we have to be able to track what's going on and trust who is doing the work. 3D printing, prototyping, again, this is just making it more efficient for us to get things to market.

AR, VR, human-machine collaboration, again, synergies between our senses and the abilities of machines to augment those senses. And blockchain, which is going to be the secure transfer of information, data passports, things that allow us to interact between different platforms, different environments, different individual cells and different private networks. So how are we gonna operate our businesses in the future? We have future operating models, which allow us to sort of start from scratch a little bit.

There are two main components to how we need to design our businesses in the future. One of them is mindset. The individuals have to acknowledge and understand the digital involvements in their daily lives.

So the focus on humans, living humans, enhancing that activity as a living being is where we have to start focusing on culture. Because a lot of times, up until very recently, the focus has been on automation. How do we automate processes as quickly as possible? How do we get that assembly line working more quickly? But the assembly line is no longer our natural habitat.

That is for the machines. So for our human intelligence tasks, we need to modify the ways that we approach our organizational structures. And on the other hand, you have the organizational structure.

The most successful businesses that we're seeing these days are ecosystems. They are complimentary infrastructures where you have modular interchangeable parts. And this is similar to a decentralized network.

You have AWS, and you have Amazon.com, and you have Amazon Prime, and you have all of these different systems interlocking and operating together, but managed separately. And that way, you need to innovate one piece of the whole. You don't have to break across your whole structure, break across your whole operation, and find a way to modify everyone's behavior.

And the main goal that we should be thinking about is not just how to go as quickly as possible to market, but to do it in an intelligent way. So economic viability is a big problem these days because it used to be that a company's lifespan could be upwards of 60 years. A successful company should be lasting multiple decades.

The average now is 15. You're having companies coming about and disappearing. And if we're shortening the lifespan of our operational models, then we're not really creating a sustainable new future.

So how can we create these operational models? How can we create these new companies and make them as optimized as possible? We have to focus, first off, on governance. Agility, these new companies especially have shown the larger, older structures just how necessary it is to be agile, to be able to adapt and to modify as quickly as possible. Now, this is from the inherent biological evolution of us as humans.

The ability to adapt is all that can protect a company in a changing world, an ever-changing world, which we have right now. Decentralization needs to be key. Hypercentralization creates inefficiency and it creates high risk.

Decentralizing the models in an ecosystem way will help companies operate more efficiently. And decision-making needs to be done more quickly. And that's where the machines come in.

The idea is the 5G technologies that we're implementing that are speeding up our access to data and our access to information should be allowing us to make better decisions as individuals. So process-wise, we're not going to be able to rely on the products themselves. The products are obsolete quickly and the products that we create are very rarely long-term.

So we have to think about the processes that we use to innovate, the processes that we use to bring items to market, and then we have to integrate all of those processes in an efficient way. Cross-functional teams, I'm sure many of these restructurings we're seeing within our own companies. We're seeing how individuals are, the collaboration of individuals is being emphasized.

We want to focus on the outcome, but we also want to focus on the teamwork and the process to get to that outcome without knowing what that outcome is. And then we have our workforce itself. So as I mentioned, the liquid workforce is this new phenomenon.

We have this peer-to-peer interactions of our contingent workers, our gig workers, our freelancers. And the idea is because they have this sort of independence as an entity, they're becoming more specialized. They're becoming more skilled.

And also as a recipient of that higher skilled labor, you're also paying less for it because you're only using it on demand. So this liquid intrapreneurial type of worker really adds a lot of value at a very low cost. Converging teams, this is again with the collaborations, the idea of having people working together.

And then learning and re-skilling. You can't optimize the product anymore. You can try, but you can't maintain a stability on one structure.

So you have to focus on having the individual learn to be adaptable for any potential outcome. And beyond that, re-skilling and learning allows them to build not just the actual skills themselves, but the ability to learn and the ability to adapt. Because if we don't enhance our humans, then we're just creating a more paralyzed race.

So we also have our technology, of course. Continuous innovation, this is not so new. But a lot of the times, we kind of focus in the style of our individuals into learning about just the things that are right for me as far as how technology affects not just how they work, but how those around them are working.

Then we're able to create a more adaptable environment. We're able to create a more efficient organism. So last, we have culture, especially with the newer generations.

A company is not just a place to make your money and feed your kids. It's also a lifestyle. It's also a family.

They're assigning a lot of branding, not just externally, but internally. So you have to create a kind of culture that will attract the kind of talent that has the choice and has the freedom to say no. So now you have to attract these individuals who are highly specialized and have many, many options because the human cloud is providing them with these options.

So bias has to be towards action, aligning with society's values and becoming an attractive place for people to spend their time. Because in reality, what we're really talking about is how are you gonna convince people to spend their time and their intelligence on your tasks, on your projects. And last, we have our metrics and incentives, just like we have continuous development and agile development and feedback mechanisms.

We should be able to also continuously innovate these operating models. And that's where the modular components and ecosystem components come in. Because if you need to innovate one area of your company, having this constant driven driving force towards innovation, not just technologically, but also culturally and behaviorally, allows us to continuously keep up with the rapid change of technology, which we are not gonna see slow down anytime soon.

So learning and personal growth, the ability of a machine to learn should be complimentary to the ability of us to learn. We have to now compete with these items that we've created, so we need to be able to step up our game. So the real thing that we wanna, that I guess I'm trying to convey here, is the concept of work.

And what does it mean to work? Because I think we're all really excited about what's possible. We're all really excited about 5G and what it's going to offer. But we also need to focus on what we are going to do once all of this is rolled out.

What does it mean for us to have jobs? What does it mean for robots to have jobs? Who is supposed to do the work? What work is available? And how is that work gonna get done? So on the essential end, are we gonna create this Terminator workforce? Or are we gonna create this human cloud Iron Man workforce? And that's really decisions that we all make as individuals and that collectively creates our new future. So in conclusion, firms and innovators must adapt organizational efficiency and operating models to succeed. Everything's changing.

We can't just keep the same structures and then wonder why they're disappearing and then get mad that they're going away. So we have to really focus on renovating the business model. We have to really think about technology-driven change, understanding how it affects us and affect our behaviors, and then decide how we wanna act differently.

And then beyond that, digital inclusivity. Human-machine integration is inevitable. If we're going to do it, we should do it correctly.

So let's all try to design the world that we want to live in and we want our kids to live in and operate in. So that's it. Thank you.

And keep being human. 

Q&A

I understand how you can build an organization for a certain economy. But are there any public success stories for incumbent organizations who are transitioning into this mode of work? 

So we have sort of different terminologies for this type of thing, and that's why I don't understand the phenomenon in full. A lot of times you see just like the blossoming, and there's just so many consultants these days. Like, what are these consultants coming from, right? So the idea of these individuals, self-employed consultants, really is the start of the human workforce, but you see it a lot of times in IT.

So we have, like, it's starting to enter through the IT, and that's where innovation tends to enter. So we have a lot of times you have a project manager who outsources work through Upwork because they've been assigned it. So we're starting to see it when you're outsourcing technology projects.

That tends to be where we get the human cloud models. But beyond that, you also have different operational models just being developed. There's something called the Holacracy.

H-O-L-A-C-R-A-C-Y, if anyone wants to Google it. And it's the idea that we're dividing, instead of having people with individual responsibilities, we're creating new maps of how individuals are operating and just creating tasks and allocating them across that board. So you have individuals floating between the tasks that are at hand as opposed to their individual job descriptions.

So when you focus on the outcomes, you end up shifting the focus, and then you can outsource and insource as needed. So it's the outsourcing that you start to see that entering. 

So one of the observations, Nora, is that, as you mentioned, digital changes are happening exponentially. It's so rapid that no matter how smart we are, I mean that's true of all of us, it's very hard to cope up now. Because thanks to not just 5G, but a plethora of technologies. So what's the social impact of these changes? In fact, I was talking to some folks in the government, very senior folks. They're saying they're really worried about the social impact of digital changes. I mean, the examples where WhatsApp has created riots, it's created crime in a place. How do you solve the problem? I don't know.

Well, I think some of the issue comes about because you have these two concurrent models, and there's a lot of friction between them. And that's not just companies, but also socially. I think, though, we tend to focus on the difficulty of the transition, but also you have individuals making these decisions.

So as humans, we're self-organizing. We're networking ourselves, right? So our decisions to enter the human cloud are being made in response to the innovations that are in front of us. We're losing our jobs, and we need to make money, so we go to the platforms available to us.

So in a way, I would say the future, the way to solve these problems is to just, as some would say, lean in, dive deeper into the human cloud. Because you have, especially Generation Y, Generation Z, people who have maybe three or four revenue streams. They're not actually committed to any one type of goal.

And you have these individuals who seem to be quite stable. They're paying their bills. They're living their lives. And the problem is that because they're unrecognized and because the regulation has sort of ignored this phenomenon for a while, the friction is there because they have no place in society. They have no sort of formalized structure. Even just getting statistics on the economy is a little bit shaky. I mean, I have $15 billion to $3.5 trillion. That variety is huge. And that's maybe, I would probably guess the trillions comes from Silicon Valley and the billion comes from the East Coast. But that's just my guess. But the idea is that you have this sort of uncertainty.

It's just no one knows about it because people are really hyper-focused on the technology itself. They're forgetting that the humans are making those decisions, and they have to analyze things with different metrics. The metrics are just outdated. 

Nora, what are your thoughts on robotics? You mentioned that today we are basically going offshore for manufacturing and all of that. It's sort of imbalancing the workforce and all of that. So what's the impact? Should we exploit more robots in every country equally such that we could balance the trade? 

Well, we have the phenomenon of insourcing. We have our president talking a lot about countries, not just America, that are building more.

So you're creating these interactions within an existing network. So robotics especially is sort of the obvious where you can create the automated production. You can create the automated manufacturing.

But the idea of, you're saying how other countries may want to act in this way, they are going to have to create their own systems that mimic or maybe modify their own production. So I think the fact that we're decentralizing a lot of our telecommunications allows us to operate independently, allows other countries to develop more rapidly without as much dependence on the globalized supply chain. Because if each individual is one piece of this large, huge chain that's so extended and has so much latency at every link, you're creating this environment where everyone is sort of trapped in this older environment, this centralized environment where everything kind of funnels to the end consumers here in the United States.

So when you take away that strict line that ends in the U.S., then you end up creating this opportunity for individual countries to innovate and to develop and to create their own micro-networks and create their own micro-economies. So you're saying 5G can help with microeconomics going from centralized to... Well, the biggest thing is the collaboration and the development we as humans interact is going to create the potential for us to collaborate and to create better futures and better outcomes. Thank you.

Not really much about what you talked about. My curiosity is what prompted you to move into this, looking into how the effect of technology is on the human? 

Well, I think, so I have a biology background....

[...]

If we connect the gig economy to our human existence as individuals, one of the reasons we are able to have such an innovative society here is that we’ve brought so many innovative people here. And if you connect the human flow / human migrations as individuals and where we’re going, that’s where the brains are going and that’s where the innovations are going to go. 

So if we want to create an attractive environment here and we want to create something that isn’t necessarily the same consumer supply chain globalized outcome that we’ve had in the past, we have to create an attractive business model and an attractive operating model that will keep the brains where want them to be, which is here. If you have a remote workforce where everyone can work from wherever, you have to create the environment that is their preferred location of work. 

If we don’t innovate the way we operate our models and invite this flexible workforce to feel comfortable in our companies then they’re not going to stay here. And there are other places that are more than happy to take these skilled workers and these skilled minds. 

...

We shouldn’t hyper focus on just IT. When we think of remote workforce individuals, we tend to think of computer science. The liquid workforce has more to do with interactions, and most people that you interact with are right in front of you. Sometimes you need someone right in front of you. We have this concentration of the human cloud in IT, but if we build those other elements, these other components, then we insulate and we diversify the human cloud a little bit more. 

The questions in this talk, about platform infrastructure, human agency, and what it means to build economic systems around people rather than institutions, are the same questions I've been working on since. Trops is the operating model I've built in response.