Mario Kempken, Founder, Global Human Index (GHI)

I’m Mario Kempken, founder of the Global Human Index.

The index’s context is helpful. The Global Human Index is a way to measure human accountability in businesses and in systems. The reason for its existence is that, as we scale automation globally, human participation in systems is becoming optional rather than a requirement.

The reason we exist is that legislation and governments are struggling to regulate and manage progress. I don’t think it needs to be managed — we just need to provide a transparent view of the degree to which humans are materially involved. That will allow policymakers to actually understand how to govern, regulate, and manage that properly.

In that sense, the Human Index is just a transparent view of how humans are involved, or to what degree, in any system or organization.

The index has three primary areas of focus. The first is really at the top end of certifying a business or process so that we can, as a whole, understand the GHI score of that entity. That’s where our focus is at the moment — doing business audits and certifications.

The next level of standard that we have is self-disclosure. That’s more for product teams and departments to disclose. It’s a guideline and a framework for them to understand and measure how humans are involved in a system from a decision-weight point of view, from a labor-share point of view, and from an accountability perspective — so that when we have automated systems, they can really understand whether accountability lies in human hands or whether it’s a fully automated system. That is from a risk mitigation perspective, and that’s the self-disclosure.

The third focus element is the GHI labels, which are for consumer-facing products. That is to help us distinguish whether humans are involved in the supply chain and in the creation of the products or services rendered. I think that’s an incredibly valuable one because, as automation scales, we want to make sure that we’re consuming products and services that are actually rendered by humans. But at the top end, the primary focus is on business certifications.

The reason this matters is that we’re going to have a problem in society: as we measure an economy by economic output, automation will grow, and the economy will have higher output. However, humans will receive a smaller share of the economic value generated. So, in an economic sense, we’re going to become wealthier, but in reality, we’re going to have a lot less, and automation is going to reap the benefits.

Especially in labor economies, as we have — where people need to be involved, and taken care of — there’s going to have to be a governing structure for governments to understand businesses’ and industries’ GHI scores and the industry-standard GHI score. That will force people to still be involved in processes. Otherwise, we’ll have completely automated sectors of industry where people won’t be involved and won’t be able to earn income. That’s the real problem that we’re trying to fix by building the index.

We’ve developed a standard and a framework for analyzing and collecting data through a process. We go through an analysis phase where we collect the data as an organization — all of that is submitted to us. We have a data processing engine that obviously processes, manages, and produces a score.

The frameworks and procedures that sit in place are really what we’ve defined, and we have built hierarchies on top of the four pillars: labor share, the decision weight of individuals in the system, the labor share percentage, and then the accountability metrics. Those pillars are really the foundations from which we collect data in those silos. We would systematically go through all processes and procedures — specifically within businesses with factories and a process-driven approach — which makes a lot of sense.

Our data collection happens either manually, where we go and collect data within these organizations, or through our tools, where we process data. It’s an AI-driven process with humans involved to ensure the certification. It’s really a consulting function, where we understand what’s going on beneath the surface. It’s a fairly technical process involving engineering teams that understand the data layers of AI and robotics — technology-minded individuals and consultants who really understand where this is going within an organization and what the impact will be, so they can understand what these scores are made up of and who is involved.

It is a manual effort at the moment. We have a tool that goes in and collects the data, but aside from those two methods, the process of understanding and issuing the certification is still very human-led. Ultimately, it produces a single score — a GHI score — that sits at a business, individual system, or department level.

I sit on the other side, where I have companies that run on the other end, building automation. I don’t think we need to stop it — we can’t. Our goal is not to stop it, but to provide a transparent view into what it does.

The best reference I can draw is the climate industry. I often compare the GHI to the climate industry, where we understand a company’s carbon emissions and, based on those emissions, tax and regulate the company. It’s the same for AI and automation.

I think the biggest problem we have right now is that regulation cannot keep up with technological advancement, and I don’t think it ever will. As a result, in economies where automation thrives, the degree of human involvement is eroding.

At one level, we have AI, which has transformed enterprise tooling and the SaaS service layer — AI is ultimately the brain and has taken care of the product layer. Right now, every product company faces the question of whether they should simply generate with AI or actually build a product. At another level, robotics is coming to replace the physical labor force. So AI is essentially the mind, and robotics is coming to take away the actual physical labor force. If we don’t have a way to understand and measure its impact, there’s no way we’ll be able to regulate and control it.

The impact will be like what we’re seeing now with uncontrollable AI. For example, if we look at what’s happening in the market — where it shouldn’t be possible that, with the release of a new model, a company like IBM loses 12% of its market share — the competition commission should not allow it to happen, because it directly impacts entire industries. What we’ve seen happen at a software level is now going to happen at an actual labor, manufacturing, and process level, and unions are going to have a massive problem.

The impact of the work that we’re doing is to provide that transparency. Industry needs to measure impact so that lawmakers, policymakers, and governments can catch up and use it as a tool to understand it. Legislators don’t need to understand the technicalities of automation, but they need to see a clear, trusted view of the degree to which it affects society. I think if we do that, we’ll be able to control the next evolutionary step of automation in society, and I see us playing a key role in providing that transparent view.

I think it’s going to happen extremely soon. I don’t think we realize how soon it’s going to happen. If we look back 24 months, we probably didn’t realize we could build complete products with singular agents working together. Now that’s happening at scale.

I think the next thing will be significant, especially in global sectors. If you look at economic indices, the Western world has adopted a hybrid approach to automation, with parts automated. If we look at a continent like Africa, they’re not going to adopt a hybrid approach—they’re going to go from no infrastructure to fully automated. They’re going to jump the gate. The result is that we will end up with a mass-unemployment problem if we don’t account for it, engage with it, and build it into public policy properly.

I do think that within the next five years, we’ll definitely see that happen. I think we’ll start to see it in the next two to three years, but by the next five years, we’ll really see robotics fleshed out. At the moment, robotics is being tested in a way similar to the early days of AI — shown in a few things, but not yet as robust or as smart as everybody thinks. It’s still going to take a little bit to get there. But to manage society properly, we’re setting up the index.

If we look at industry sectors, it’s definitely the labor markets. We are looking at manufacturing, heavy industry, and specifically professional services, which is also massive. The sectors that are currently most important are software engineering, where accountability matters, and finance and auditing, for example, which are professional services that are highly important and highly regulated. At that level, human accountability has to sit at the pinnacle of the decisions that get made. If we erode accountability and hand it over to automated systems, we have a problem. So on the software solution side, it’s really accountability. On the labor market side, it’s really about ensuring transparency into the labor share.

The most important piece of our work at the moment is completing the certifications and starting to certify at scale. That’s our mandate — to start the process of providing labels that can be recognized in industry and become an important factor in our work. Once we have the certifications and the label, we will launch a transparent index—a public ledger—where every company can be found, indexed, and their score can be seen transparently. Those are the steps we’re taking to bring transparency into this ecosystem.

More than that, we’re not looking to guide and tell companies what to do. We’re really looking to tell them the current state of affairs so they can make the necessary decisions.

In terms of regions, the EU is a massive focus for us. The larger regions where automation is scaling fastest are in Asia, so that’s a focus from a labor-share perspective. From an accountability perspective, it’s really the European Union and the American corporate landscape. That’s where technology, product, and service are coming from at the moment, and product and service need to be regulated. The European Union is a key focus area for us because of how legal and union legislation works — in terms of the degree to which automation is allowed in those industry sectors — particularly in legislation. Having a hold on legislation is an important factor and probably our most important focus.

Africa as a whole has some time to develop. We were naturally born out of there, so we started there, and that’s where the index made sense — we saw the jump when there was no hybrid workspace and factories were being built that would be fully autonomous.

Consumer products are also one of the most important sectors in this work. We don’t specifically have a single region of focus at this point. We’re really doing it by industry sector more than by geography, because robotics and automation are not problems that scale at a regional level — they’re happening globally across all pillars, across every continent and every country, at varying degrees. The index needs to be there to manage that across industry sectors rather than necessarily by region.

There are two ways we specifically partner. We either work with organizations to provide certifications, especially with multinational organizations, where we partner with them to understand their supply chains and audit them efficiently. In terms of the labels, those are purchases that can be made directly from a product and service perspective.

In terms of the partnerships we have and are seeking, we are currently in talks at the government level to provide the GHI as a guideline to inform policy and serve as an independent service metric. It’s really an invitation not only for companies but also for governments to use the index as a guideline for economic measurement.

Those are the three tiers of participation: government, business, and consumer. At the government level, the engagement is really around enforcing the label from a regulatory perspective. At the business level, it’s really about auditing to understand the current state of affairs. And at the product level, it’s about putting a badge on the label to indicate that humans were involved in producing or supplying the goods or services.

I think the main message would be that we don’t need to panic about the innovation — we just need a way that everybody understands it. A lot of people don’t really understand what’s going on, and everybody who runs a business is pretty scared about their future and whether they’ll still exist. The message we have for everybody is that as long as you understand what’s going on, you can make rational decisions and sound judgments.

By simplifying AI, robotics, and everything that’s happening into a single measure — how are humans involved in this process and to what degree — we hope to simplify the understanding of the whole industry and the whole specific tech space for everybody, so that everybody can use it and continue with their normal lives. All of a sudden, if a policymaker sees that a system has no human accountability, it becomes very clear what the risk is and what to do about it. Our singular message is that we want to make this transparent and understandable so that we can help everybody progress faster.

Another message that is pretty important is that if we don’t prioritize human involvement in systems, we risk systems where human involvement isn’t mandatory. The result of that is pretty catastrophic for us as humans — we will have complete sectors working completely autonomously. The investment community is investing in fully automated businesses, and if we don’t make sure that we take care of our involvement in that, it’s not going to happen by default. It is quite serious to ensure that humans remain involved; otherwise, we won’t be.

It is kind of urgent because we won’t be needed anymore if we don’t actually act and prioritize being involved.

I come from a technology background, and we’ve seen what’s been going on. I think it’s a case where we just need to relax — there is a way to govern this and a way to manage this. As long as business leaders can resonate with that, I’m hoping to achieve it. We need to communicate that there is a process, because I think everybody is really scared that automation is just going to scale, and nobody knows what the unknown is. I think we can control and manage it when we have a way to go through it.