HUMAN Protocol is a blockchain infrastructure designed to decentralize human work by supporting the growth of digital labor markets.
After its recent launch on the Ethereum mainnet, the protocol has now gained the ability to fully automate the lifecycle of data tagging jobs, allowing human and machine collaboration to create and complete a series of real-world expendable allowances.
By working with artificial intelligence and machine learning technologies, users can now be rewarded with HUMAN’s native token, HMT, for successfully completing anti-bot visual challenges, such as identifying traffic lights in a grid image. This data is then collected and used to support the eradication of biases in labor markets, promoting a more circular gig economy.
For a more in-depth reflection on these recent announcements and the broader implications for the blockchain technology sector, Cointelegraph spoke with Harjyot Singh, Chief Technology Officer at Human Protocol.
Harjyot is a leading entrepreneur in the field of fintech engineering with an academic background in computer science and artificial intelligence.
His current focus is “exploring how cutting-edge technologies like artificial intelligence and blockchain can improve the day-to-day experience for the majority of Internet users.”
Cointelegraph: How will HUMAN’s recent announcements (launch on Ether mainnet and launch of CAPTCHA web application) support the growth of the protocol?
Harjyot Singh: We are excited about our recent accomplishments. The launch of HUMAN Protocol on Ethereum Mainnet allows us to realize the first instance of a decentralized HUMAN labor market. It is also about the evolution of the Protocol; HUMAN Protocol currently processes a significant number of user interactions every day through the applications it supports. It is designed to operate on multiple blockchains, with Ethereum being the first mainnet implementation. What we learn and make possible here, we can use and execute elsewhere, including Solana and Polkadot.
Obviously, the launch also allowed us to include HMT, which helps us grow the HUMAN community and incentivize broader participation. But the real growth comes from the HUMAN app – the first gateway to the HUMAN ecosystem and the first means through which people, located anywhere in the world, can earn HMT directly for completing tasks.
It is also important to note that the HUMAN application is not just a CAPTCHA application; allows people to perform many types of tasks.
CT: Readers will be familiar with Google’s reCAPTCHA system. How is the HUMAN model different from a technological point of view and what are the benefits of a human-centered identification method?
HS: It’s important to have on mind that hCaptcha is not part of the HUMAN Foundation; it is simply an application that uses the HUMAN Protocol. HUMAN has a much broader goal of tokenizing many types of human work, not simply the limited set of tasks that can be executed through a CAPTCHA.
That said, a key difference between reCAPTCHA and hCaptcha is that hCaptcha pays websites for the work their users do when they solve a CAPTCHA, rather than forcing them to donate that work to Google.
CT: Vitalik Buterin recently advocated for a transition to “humanity test” governance at DeFi. If widely deployed, how do you imagine this will affect the space?
HS: I think it will make DeFi a fairer space. Right now, systems that distribute votes based on wallet balance are causing big problems; allows crypto whales to affect proposals in their favor. HUMAN’s “HUMANITY Test” would allow one vote per verified human user, which would also combat the prevalence of bots. Because Proof of HUMANity is the first and only human on-chain verification system, it makes sense for a DeFi on-chain world.
But the potential of Proof of HUMANity doesn’t stop there; Any space where bots wreak havoc, such as overtaking trades, can potentially apply Test of HUMANITY to solve it.
CT: Could you share some specific examples of HUMAN contracts that could be facilitated in a market using the Intel CVAT image and video tagging system as well as the text-based INCEpTION?
HS: An applicant in an AI startup needs a hundred thousand images of labeled damaged cars. They provide the images, along with an HMT sum that is held in the smart contract until the job is completed. HUMAN Protocol agents ensure data is safe to share and ready for applications; HUMAN Exchanges can intelligently distribute tasks to Intel CVAT users (which could be running on different chains, and work is sent to different chains based on speed, cost, etc.).
The worker connects to an Exchange, views the job, and begins to complete the granular work in Intel CVAT by drawing detailed boxes / shapes around the damaged areas of a car. The oracles, which record and evaluate the work, then update the smart contract to reserve HMT for the Workers who completed the work.
CT: How does your native HMT currency, and specifically a worker’s token value, determine the priority for task supply?
HS: We use the balance test as one of the contributing factors to the task that the order book ranking provides, in other words, how many tasks will go to one worker or workforce group versus another. However, to reduce friction in the system, we also run a weighted average on many other parameters to allow new users to join immediately.
Related: How Blockchain Benefits From Artificial Intelligence
CT: How advanced do you think machine learning and artificial intelligence systems are today, both in terms of technical capacity and cultural awareness, to support HUMAN scalability?
HS: AI systems are currently good at specialized intelligence. That is: they are good at performing specific linear tasks, such as GPS, chatbots or Amazon’s Kiva bot that transmits boxes to and from Amazon workers. But AI isn’t that good at pervasive intelligence, which is the domain of flexibility, responsiveness, and adaptation – a domain humans thrive on.
In terms of cultural awareness, I think we are primed and ready for the next wave of AI. Artificial intelligence products are already ingrained in our lives, from face unlock systems on your phone to cleaning robots. If anything, however, I think the culture overestimates current AI capabilities; I think most people believe that AI is smarter and more capable than it really is, because we’ve been talking about AI since the 1950s, but progress has been shaky, as we saw in the “AI winter ”From the 1980s. For example, we have already integrated the inevitability of driverless cars into our cultural awareness, and yet they have yet to take off. I think we are ready; I think people are waiting for the products.
CT: As we enter a more automated economy, how crucial is it for us to build systems where machines serve the true values and needs of humans?
HS: We hear a lot of different things about AI and the implications of introducing machines to labor markets. But instead of replacing human workers, we like to focus on how machines can support and even empower them. Intelligent automation means that more repair work, small tasks, can be handled by machines, helping to maximize the time, energy and focus of human workers.
Humans are capable of feats that machines are not: creativity, ingenuity, imagination, while machines are more efficient at performing repetitive tasks. An infrastructure that supports this is particularly well suited to the growth of knowledge workers, who are capable of providing specialized input and nuisance but whose time is increasingly scarce. It also means providing skilled workers with the data they need to make informed and safe decisions.
The HUMAN protocol is designed to allow machines to complete repetitive tasks and to request the completion of those tasks from other machines. Through this, we want to empower human potential and provide the space and focus for creative problem solving.