HUMAN Protocol is a blockchain infrastructure designed to decentralize manpower by supporting the growth of the digital job market.
After being recently released on the Ethereum mainnet, the protocol has now been able to fully automate the life cycle of data tagging, enabling human-machine collaboration to create and complete a large number of real-world alternative tasks.
With the help of artificial intelligence and machine learning technology, users can now earn rewards in HUMAN’s native token HMT to successfully complete anti-robot vision challenges, such as identifying traffic lights in grid images. This data is then collated and used to support the elimination of prejudice in the labor market and promote a more circular gig economy.
In order to think more deeply about these recent announcements and their broader impact on the blockchain technology field, Cointelegraph talked with Harjyot Singh, Technical Director of Human Protocol.
Harjyot is an outstanding entrepreneur in the field of financial technology engineering, with an academic background in computer science and artificial intelligence.
His current focus is “exploring how cutting-edge technologies such as artificial intelligence and blockchain can improve the daily experience of most Internet users.”
Cointelegraph: How will HUMAN’s recent announcements (released on the Ether mainnet and the release of the CAPTCHA web application) support the development of the protocol?
Harchot Singh: We are excited about our recent achievements. The release of HUMAN Protocol on the Ethereum mainnet enables us to realize the first instance of a human decentralized job market. This is also about the evolution of the protocol; HUMAN Protocol currently handles a large number of user interactions through the applications it supports every day. It is designed to run across multiple blockchains, and Ethereum is the first mainnet deployment. What we learn and implement here can be used and implemented in other places, including Solana and Polkadot.
Obviously, this release also allows us to list HMT, which helps us develop the HUMAN community and inspire wider participation. But the real growth comes from the HUMAN App: the first gateway to the HUMAN ecosystem, and the first way that individuals located anywhere in the world can earn HMT directly by completing tasks.
It is also important to note that the HUMAN app is not just a CAPTCHA app; it allows people to perform multiple tasks.
CT: Readers will be familiar with Google’s reCAPTCHA system. How is the HUMAN model different from a technical point of view, and what are the benefits of a human-centered identification method?
high: It is important to pay attention hCaptcha is not part of the Human Foundation; it is just an application that uses the HUMAN protocol. HUMAN has a broader goal, which is to mark a variety of human jobs, not just a narrow set of tasks that can be run through CAPTCHA.
In other words, one of the main differences between reCAPTCHA and hCaptcha is that hCaptcha will pay website fees for the work done by users in resolving CAPTCHA instead of forcing them to donate these labor to Google.
CT: Vitalik Buterin recently advocated the transition to “Proof of Human Nature” governance across DeFi. If it is widely implemented, how do you think this will have an impact on the space?
high: I think this will make DeFi a fairer space. Currently, the system of distributing votes based on wallet balances can cause huge problems; it allows crypto whales to influence proposals that benefit them. HUMAN’s “Proof of Human Nature” will allow each verified human user to vote, which will also combat the popularity of robots. Because human proof is the first and only human verification system on the chain, it is meaningful to the on-chain DeFi world.
But the potential of proof of humanity doesn’t stop there; any space where robots can cause serious damage—such as seizing an opportunity in an exchange—may apply proof of humanity to solve it.
CT: Can you share some specific examples of HUMAN contracts that can be promoted in the market using Intel’s video and image labeling system CVAT and text-based INCEpTION?
high: The requester of an artificial intelligence startup needs to mark 100,000 images of damaged cars. They provide images and the total amount of HMT stored in the smart contract until the work is completed. The HUMAN protocol agent ensures the safe sharing of data and prepares the application; HUMAN Exchanges can then intelligently assign tasks to Intel CVAT users (they may run on different chains-and send work to them based on speed, cost, etc.) Different chains).
Worker connects to Exchange, looks at the work, and starts to complete the fine work on Intel CVAT by drawing detailed boxes/shapes around the damaged area of the car. The oracle records and evaluates the work, and then updates the smart contract to reserve HMT for the worker who completes the work.
CT: How does your national currency HMT—especially the value of workers’ tokens—determine the priority given to tasks?
high: We use proof of balance as one of the factors that contribute to task ordering, in other words, how many tasks will be allocated to one worker or labor pool versus another. However, in order to reduce friction in the system, we also weighted average many other parameters so that new users can join immediately.
CT: How advanced do you think AI and machine learning systems are in terms of technical capabilities and cultural awareness to support HUMAN’s scalability?
high: Artificial intelligence systems are currently good at professional intelligence. In other words: they are good at performing specific linear tasks, such as GPS, chatbots, or Amazon’s Kiva robot, which relays the box to Amazon employees. But artificial intelligence is not good at generalized intelligence. This is the field of flexibility, response, and adaptation, and is the field where humanity is flourishing.
In terms of cultural awareness, I think we are ready for the next wave of artificial intelligence. AI products are deeply ingrained in our lives-from facial unlocking systems on mobile phones to robotic cleaners. However, I think that culture overestimates the current artificial intelligence capabilities. I think most people think that artificial intelligence is smarter and more capable than reality, because we have been talking about artificial intelligence since the 1950s, but progress has been unstable, as we saw in the “artificial intelligence winter” of the 1980s . For example, we have incorporated the inevitability of driverless cars into our cultural knowledge, but they have not yet fully taken off. I think we are ready; I think people are just waiting for the product.
CT: As we enter a more automated economy, how important is it for us to build systems where machines serve the true value and needs of humans?
high: We heard a lot of different things about artificial intelligence and the impact of introducing machines into the job market. But instead of replacing human workers, we prefer to focus on how machines support and even empower them. Intelligent automation means that more remedial work-small tasks-can be handled by machines, which helps maximize the use of human workers’ time, energy, and attention.
Humans have abilities that machines do not possess—creativity, ingenuity, imagination—and machines are more efficient at performing repetitive tasks. The infrastructure to support this is particularly suitable for the growth of knowledge workers, who can provide troublesome and professional input, but their time is increasingly scarce. This also means providing professional staff with the data they need to make informed and confident decisions.
The HUMAN protocol is designed to allow machines to complete repetitive tasks and request other machines to complete these tasks. In this way, we hope to stimulate human potential and provide space and focus for creative problem solving.