As artificial intelligence becomes part of everyday life, most people experience AI as users or consumers. HAR is being developed around a different idea: people should also be able to participate directly in how AI systems are improved, understand what they contribute, give clear consent, and receive value.
At its core, HAR is intended to establish that a real human participated in a contribution or provided consent, while supporting selective disclosure so people do not necessarily need to expose more personal information than required for a specific purpose.
The aim is to create a trusted layer between people and AI projects: one where human participation can be verified, consent recorded clearly, and contributors can benefit from that verification.
“AI is being built from human knowledge, behaviour, language, images, voices and real-world experience, but ordinary people rarely have a direct way to participate in that process,” said Jythesh T Achary, Technical Director at MotionGravity. “HAR is being developed to create that pathway — where a real person can knowingly consent, contribute something of value, and be paid for eligible participation. At the same time, projects gain greater confidence that the data they receive comes from authentic human participants.”
Rather than treating contributors as anonymous one-time sources of data, HAR is intended to create continuity. Once verified, a person may become eligible for projects based on language, location, skills, knowledge, devices, documents, or other requirements.
Verification is therefore intended to become more than a security check. A verified participant may be able to access future opportunities where authentic human participation matters, while avoiding the need to repeatedly establish that they are a real consenting person.
From Verification to Real Participation
MotionGravity is developing specialised contributor projects on top of this HAR verification layer.
Project Atlas focuses on authentic documents and document imagery. Contributors can check whether documents they already possess may be eligible for a current requirement by identifying the document name or type. No upload is required simply to check eligibility.
Where a project requires genuine real-world documents from consenting individuals, HAR verification can provide additional confidence around the human source and participation behind that data. For contributors, Atlas creates a way to discover whether documents they legitimately possess may qualify for a paid contribution.
Project Lumen applies the same principle to human knowledge and video. Verified contributors may participate by explaining, teaching or demonstrating subjects and skills they genuinely know.
That may include a practical activity, software workflow, professional subject, trade, hobby, lesson, equipment demonstration, interview or presentation. The objective is not to recruit influencers or professional presenters, but to enable ordinary people to contribute authentic human knowledge in a form that can help improve AI systems.
Together, Atlas and Lumen demonstrate how HAR can move from verification into practical participation: one trusted human layer supporting different forms of authentic data contribution.
Helping People Participate in the AI Economy
MotionGravity’s broader objective is to make AI participation accessible beyond traditional technology and data-work roles.
A person may qualify for one project because of a language they speak, another because of a skill they can demonstrate, another because of a document they possess, and another because of their voice, image or real-world experience.
In this model, people are not simply treated as raw sources of data. They become recognised participants in the process. MotionGravity describes the goal as creating a legitimate pathway through which individuals can consent, contribute and earn, while helping AI systems gain access to authentic human-origin data.
HAR is also being developed with longer-term applications around digital authenticity. As synthetic images, voices and videos become more sophisticated, MotionGravity intends to explore how the verification layer can eventually support broader anti-deepfake, authenticity and consent-verification technologies.
The company plans to expand HAR with additional opportunities across image, speech, audio, language, video, documents and other multimodal data categories.
About MotionGravity
MotionGravity is an India-based technology and data services organisation specialising in precision data collection and AI dataset production. Its capabilities include audio and speech data, transcription, annotation, OCR, image and video collection, dubbing, captioning, language services and multimodal data programs.
Through HAR and contributor projects such as Atlas and Lumen, MotionGravity is developing infrastructure intended to connect verified human participation with legitimate AI-data requirements.
Email: connect@motiongravity.in
Learn more / Join the HAR Contributor Network: https://join.harregistry.org/contributor-signup
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