Zero Knowledge Proof Of Competence

[GENERAL] Name and surname of main applicant

Ubio Obu

[GENERAL] Email address of main applicant

ubboyoyo@yahoo.com

Additional applicants

Ediyangha Ottoho, Daniel Effiom, Yash Ambekar, Blessing Izirein

[GENERAL] Please specify how many months you expect your project to last (from 2-12 months)

9

[GENERAL] Please indicate if your proposal has been auto-translated into English from another language.

No

[GENERAL] Does your project have any dependencies on other organizations, technical or otherwise?

No

[GENERAL] If YES, please describe what the dependency is and why you believe it is essential for your project’s delivery. If NO, please write “No dependencies.” .

No dependencies.

[GENERAL] Will your project’s output/s be fully open source?

Yes

[GENERAL] If NO, please describe which outputs are not going to be open source. If YES, please write “Project will be fully open source.”

Project will be fully open source.

[METADATA] Category of proposal

Identity Solutions

[METADATA] SDG rating

SDG goals:

Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all

Reduce inequality within and among countries

SDG subgoals:

Achieve higher levels of economic productivity through diversification, technological upgrading and innovation, including through a focus on high-value added and labour-intensive sectors

Promote development-oriented policies that support productive activities, decent job creation, entrepreneurship, creativity and innovation, and encourage the formalization and growth of micro-, small- and medium-sized enterprises, including through access to financial services

By 2030, achieve full and productive employment and decent work for all women and men, including for young people and persons with disabilities, and equal pay for work of equal value

Protect labour rights and promote safe and secure working environments for all workers, including migrant workers, in particular women migrants, and those in precarious employment

Key Performance Indicator (KPI):

Proportion of informal employment in total employment, by sector and sex

Average hourly earnings of employees, by sex, age, occupation and persons with disabilities

Unemployment rate, by sex, age and persons with disabilities

Universal Human Rights Index (UHRI):

#proposertoolsdg

[IMPACT] Please describe your proposed solution.

Do you know why employers and HR pass candidates and applicants through different stages of applications, CV screening, interviews, post-interviews, capstone projects, etc before giving a job or gig to a talent? In fact, this process is so strenuous that research established that nearly 60% of job seekers quit online job applications mid-way due to their length and complexity. Despite this, one would kind of wonder why HRs and employers still insist on such a strenuous process just to give jobs to an applicant. The simple answer to this is that Employers are looking for capacity and trust.

Competence is a combination of capacity and trust. Trust is such a critical factor in the gig and hiring industry that talent teams rank employee referrals as the most important source of hire. This means that employers trust the capacity of other talents that the employees refer to, this we can call referred trust and shows that most employers will prefer hiring people they can trust and are sure of the capacity of the person.

Where and when trust is lacking employers are left with no option but to use the following approaches

APPROACH 1: Resort to using different stages and long processes to build and test the capacity of the potential employees

APPROACH 2: Undertake the process of verifying and validating the individual

APPROACH 3: Collect relevant and irrelevant data of the candidate with the hope of using it to track the trustworthiness and capacity of the talent

APPROACH 4: Give capstone sample projects to potential hires.

PROBLEMS WITH THE ABOVE APPROACHES

All these approaches have been with mard with serious challenges, when looked at critically let's examine these approaches one after the other, to see all the issues with these approaches.

APPROACH 1: As already established in the introduction, research shows that 60% of talents drop out or give up on the process, in there are probably good hires that would have been helpful to the employer.

APPROACH 2: Verifying and validating individual applicants can be a very long and tasking process, in addition to this the employer may not have the capacity to even do this.

APPROACH 3: This speaks directly to the issue of privacy and data breach, talents are forced due to desperation to give out vital and private information in order to get jobs. The most annoying part is that employers get access to data that do not directly contribute to a talent's competence, data like the father's date of birth, mother's maiden name, etc, imagine this info in the hand of a malicious actor and what they can possibly do. Not only this approach also opens doors for bias, both implicit and explicit as employers gravitate towards certain demographics at the expense of others, especially when it comes to certain jobs. This bias can come as a preference towards certain gender or ethnicity when it comes to certain jobs, the issue of bias is so much in hiring that a recent Havard report states that Blacks and persons of color stand a 46% chance of getting job callbacks if their backgrounds are excluded from the CV, unfortunately, Approach 3 only reinforces this bias.

APPROACH 4: The problem with this approach is how exploitative it has become, many bad actors see this as an avenue to get free and unpaid labor in the name of sample projects, the desperate talents work on the samples unknown to them these employers are not willing to employ but are looking for free skills to execute their projects under the guise of sample projects. Unfortunately, there are no regulations against this such of exploration and one can as well argue about its necessity to protect the employer against bad actors on the talent side as well, who lack competence but want the job. Another problem with this approach can be likened to the problem of double spending in blockchain, where talent has to keep doing these sample projects for every employer he is applying to, this double spend problem finds itself even with other approaches, the talent has to keep trying to prove his/her competence every time by going through all of these approaches very single time and even the employer has to go through these long processes every single time.

WHY ZERO KNOWLEDGE PROOF OF COMPETENCE?

This analysis of the approaches establishes the fact that trust at the center is what the employer and the hire need and both are skeptical of each other's intention. It's a game where you either catch or become the catch. But apart from these approaches is there no way to prove competence? This is what this proposal Zero knowledge proof of competence is all about.

At Remostart we help startups/organizations hire inclusively, and we have seen firsthand the exploitation and bias that exists in the hiring industry, we feel the pulse and fears of both the employer and the talents and this is why we have decided to be of help to them.

As the founder of Remostart, while completing my Pioneer program, I noticed how critical the topic of Trust was as well as the topic of self-sovereign identity and decentralized identifiers. I realized that what the employers are trying to do by validating and verifying their employees are actually SSI-related concepts and I figured out there's a way Remostart can become issuers and verifiers on behalf of the organizations, reducing the responsibility of the employer to only the role of one who checks the candidates' competence over the blockchain, as such allowing the employers to validate the talents competence without bureaucracies, continuous repetition, and redundancy.

THE CONCEPT

Zero-knowledge proof of Competence seeks to identify and prove an applicant's level of competence on any skillset while preserving the applicant's sensitive data and allowing employers to check the candidate's competence and fit for the job/gig. The project leverages the principles of self-sovereign identity (SSI) to empower talents with control over their digital identities.

The project will consist of the following identity concepts

(I) Remostart as an Issuer

(ii) Employers as Verifiers

(iii) Talents as Holders

TECHNICAL IMPLEMENTATION OF PROPOSAL

Credential Issuance

Remostart, acting as the issuer, will verify the talent's qualifications, skills, and competence through a trusted and secure process. This process involves testing the talent against a very robust and integrative adaptive test process which helps determine the exact competence of the talent. Once verified, Remostart generates a verifiable credential containing the necessary qualifications, signed using digital signatures. The credential includes specific attributes related to the talent's competence, such as skill, competence, other related parameters like problem-solving skills, technicalities, etc.

The credential will also have metadata that can be validated, these meta-data contain info like the version of the credential, time is taken, independent scores, type of tests done etc This way, the problem of double spend is removed because talents only do these test once and use it to verify ain't other employers.

Zero Knowledge Proofs

To protect privacy, the talent employs zero-knowledge proofs to verify their credentials without disclosing the underlying sensitive information. Zero-knowledge proofs allow the talent to demonstrate possession of specific attributes without revealing the actual data itself. This ensures that only relevant information is disclosed while protecting personal privacy.

Verification Process

When applying for a job, the talent presents their verifiable credential to the employer or validator. The employer initiates the verification process by validating the authenticity and integrity of the credential. Through cryptographic techniques, the employer can verify the issuer's signature, ensuring the credential's legitimacy.

Zero-Knowledge Proof Validation

To assess the talent's competence, the employer requests the talent to provide zero-knowledge proof related to specific attributes or qualifications required for the job. The talent generates and presents the proof without disclosing the sensitive information itself, thereby preserving privacy while satisfying the employer's verification requirements. Imagine this use case for a gig, the confidence and trust on both parties will increase and this is what we seek to address.

Tentative Prototype design

▶ Remoforce - Web - High Fidelity Desing (figma.com)

[IMPACT] How does your proposed solution address the challenge and what benefits will this bring to the Cardano ecosystem?

Directly from the challenge setting page, this is what success looks like for this challenge

What does success look like?

Establish key relationships and learnings early in the development cycle, leading to faster and more successful business outcomes.

This is achieved through our proposal as we have the opportunity to put this approach directly to the test in our business, the learnings from both the development and utilization of our proposal will be key in helping this solution.

Also from the challenge setting this is one of the key metric

Key Metrics to measure

• Develop a Proof of Concept, Pilot, or commercial launch

This is exactly in line with our proposal which seeks to develop a prototype and commercially launch this solution for use at Remostart and open-source it to any and every business or person who wants to use it in their own product.

To the Cardano community we will benefit from this project by the number of DID addresses which will be created considering that we are using Atala prism framework for development this goes directly as a benefit to the Cardano community. Also currently we do have about 6000 talents and 100 businesses in our platform this new feature will get between 20-30% of our customers using it, these 20-30% are directly using a Cardano-based product, increasing the utility of our ecosystem.

As the CEO of Remostart, I have completed the Atala PRISM Pioneer Program. And Remostart will hold regular meetings with stakeholders, holders, and verifiers, to work towards adopting Ecosystem Governance and publishing a Governance Framework.

[IMPACT] How do you intend to measure the success of your project?

To us the success of this project will be measured by

(I) Deployment of the successful code into github

(ii) Broader adoption of SSI: Every user both the holder and the validator are directly adopting SSI, we will be measuring how many users adopt SSI base on this project

(iii) Cardano community Adoption: We will measure how many developers, talents and businesses specifically in Cardano who will be using this our solution, for talent verification and validation.

(iv) Enhanced privacy and streamlined hiring processes: We will love take stakeholder surveys to measure how much privacy has been enhanced through using our solution and how better streamlined the hiring process has become.

[IMPACT] Please describe your plans to share the outputs and results of your project?

Phase 1: Deployment of Issuer and all its dependencies

Time period: 4 months

Phase 2: Deployment of Holder and all its dependencies

Time Period: 2 Months

Phase 3: Deployment of Validator and all its dependencies

Time Period: 2 Months

Phase 4: Test and Deployment

Time Period: 1 month

[CAPABILITY/ FEASIBILITY] What is your capability to deliver your project with high levels of trust and accountability?

As the CEO of Remostart, I have had the privilege of working with all the stakeholders involved in this problem, I have worked with thousands of talents and hundreds of businesses, especially as Remostart is focused on helping talents from disadvantaged backgrounds to have access to jobs, I have seen firsthand the deficit of trust in this system, this is why I feel confident that I can execute this project. This plus my skills and experience as a developer with my organizational skill as a CEO and having completed the ATALA PRISM pioneer program makes me well-suited to handle this project.

Also, I had a fund9 funded proposal which was executed and brought to completion on time, this demonstrates that I can be trusted when it comes to managing funds properly.

[CAPABILITY/ FEASIBILITY] What are the main goals for the project and how will you validate if your approach is feasible?

The goals and objectives of this project are:

(I) To set up a ZK proof of competence protocol on our platform

(ii) To streamline hiring processes and stages to a maximum of 1, as such reducing the process by over 60-70% of the current time for the stakeholders using our solution

(iii) To reduce the time for validating talents from weeks to less than an hour

(iv) To add between 200-1000 users of Cardano based DID in 1 year

(v) To protect the privacy of talents even when searching for jobs and gigs

I will be validating my objectives against my actual deliverables throughout the project

[CAPABILITY/ FEASIBILITY] Please provide a detailed breakdown of your project’s milestones and each of the main tasks or activities to reach the milestone plus the expected timeline for the delivery.

Milestone 1: Deployment of Issuer and all its dependencies

Timeline: 4 months

Key Activities:

1. Develop a design framework for the development plan that will be utilized
2. Compute and integrate the relevant modules and methodology that will be used for testing and validating talents
3. Set up the development environment and infrastructure
4. Design and implement the issuer component, including the necessary APIs and interface
5. Integrate the issuer with the self-sovereign identity (SSI) framework
6. Develop the verification processes and protocols for issuing a verifiable credential
7. Conduct rigorous testing and debugging to ensure the functionality and security of the issuer component
8. Simultaneously integrate the different modules and capstones and standards that will be used for verification of each skill under consideration

Success/Acceptance Criteria:

• Successful deployment of the issuer component and its integration with the SSI framework.
• Verification processes for issuing verifiable credentials implemented and tested.
• Comprehensive documentation was created for the issuer component.
• Skill verification modules for different skills under consideration

Milestone 2: Deployment of Holder and all its dependencies

Timeline: 2 months

Key Activities:

1. Develop the holder component, allowing talents to manage their credentials securely
2. Implement the necessary APIs and interfaces for the holder functionality
3. Integrate the holder component with the SSI framework
4. Design and implement the user interface for talents to interact with the holder component
5. Conduct thorough testing to ensure the functionality and usability of the holder component

Success/Acceptance Criteria:

• Successful deployment of the holder component, enabling talents to manage their verifiable credentials.
• Integration of the holder component with the SSI framework.
• User-friendly interface for talents to interact with the holder component.

Milestone 3: Deployment of Validator and all its dependencies

Timeline: 2 months

Key Activities:

1. Develop the validator component, allowing employers to verify talent credential
2. Implement the necessary APIs and interfaces for the validator functionality
3. Integrate the validator component with the SSI framework and issuer component
4. Design and implement the user interface for employers to initiate and perform verification processes
5. Conduct comprehensive testing and validation to ensure the accuracy and reliability of the validator component

Success/Acceptance Criteria:

• Successful deployment of the validator component, enabling employers to verify talent credentials.
• Integration of the validator component with the SSI framework and issuer component.
• User-friendly interface for employers to initiate and perform verification processes.

Milestone 4: Test and Deployment

Timeline: 1 month

Key Activities:

1. Perform end-to-end testing of the entire system to ensure its functionality and security
2. Conduct performance testing to evaluate the system's scalability and response time
3. Gather user feedback and conduct user acceptance testing
4. Address any identified issues or bugs and make necessary refinement
5. Prepare the system for production deployment, including setting up necessary infrastructure and security measure

Success/Acceptance Criteria:

• Successful completion of end-to-end testing and performance testing.
• Positive user feedback and successful user acceptance testing.
• Identified issues or bugs addressed and resolved.
• Production-ready system prepared for deployment.

.

[CAPABILITY/ FEASIBILITY] Please describe the deliverables, outputs and intended outcomes of each milestone.

Milestone 1: Deployment of Issuer and all its dependencies

Deliverables:

1. Skill verification modules: A robust database we will be using in an integrable manner for validating the talents
2. Issuer Component: A fully functional issuer component that allows Remostart (the issuer) to verify talents' qualifications, issue verifiable credentials, and securely store the
3. APIs and Interfaces: Well-defined APIs and interfaces for seamless integration with the self-sovereign identity (SSI) framework and other components
4. Verification Processes and Protocols: Robust and secure verification processes and protocols for issuing verifiable credentials, ensuring the authenticity and integrity of the issued credential
5. Documentation: Comprehensive documentation that includes the technical specifications, setup instructions, and usage guidelines for the issuer component

Outputs:

1. Integratable skill testing modules for at least 5 common modules
2. Deployed and functioning issuer components
3. Verified and trusted verifiable credentials issued by Remostart
4. Verified credential records stored securely

Intended Outcome:

• Remostart can successfully verify talents' qualifications, issue verifiable credentials, and securely store credential records. This milestone establishes the foundation for the subsequent phases.

Milestone 2: Deployment of Holder and all its dependencies

Deliverables:

1. Holder Component: A fully functional holder component that allows talents to securely manage their verifiable credentials, selectively disclose them, and maintain control over their digital identity
2. APIs and Interfaces: Well-defined APIs and interfaces that enable seamless integration with the SSI framework, issuer component, and other components
3. User Interface: A user-friendly interface that allows talents to interact with the holder component, view and manage their verifiable credentials, and selectively disclose them to validator
4. Documentation: Detailed documentation that outlines the technical specifications, setup instructions, and usage guidelines for the holder component

Outputs:

1. Deployed and functioning holder component
2. Talents can securely manage their verifiable credentials and selectively disclose them to validator
3. User-friendly interface for talents to interact with the holder component

Intended Outcome:

• Talents can independently manage their verifiable credentials, selectively disclose relevant qualifications, and maintain privacy and control over their digital identity.

Milestone 3: Deployment of Validator and all its dependencies

Deliverables:

1. Validator Component: A fully functional validator component that allows employers to verify the authenticity and validity of talents' verifiable credential
2. APIs and Interfaces: Well-defined APIs and interfaces for seamless integration with the SSI framework, issuer component, and other relevant components
3. User Interface: A user-friendly interface that enables employers to initiate and perform verification processes, view the validation results, and make an informed hiring decision
4. Documentation: Comprehensive documentation that provides technical specifications, setup instructions, and usage guidelines for the validator component

Outputs:

1. Deployed and functioning validator component
2. Employers can verify the authenticity and validity of talents' verifiable credential
3. User-friendly interface for employers to initiate and perform verification processes

Intended Outcome:

• Employers can efficiently and confidently assess talents' qualifications by verifying their verifiable credentials, leading to streamlined talent assessment and improved hiring decisions.

Milestone 4: Test and Deployment

Deliverables:

1. End-to-End Testing: Comprehensive testing of the entire system to ensure its functionality, security, and performance
2. Performance Testing Results: Performance evaluation of the system to determine its scalability and response time under different loads and usage scenarios
3. User Feedback: Gathering user feedback through user acceptance testing to identify areas for improvement and refinement
4. Documentation: Updated documentation that incorporates any refinements, bug fixes, and user feedback from the testing phase

Outputs:

1. Fully tested and validated system
2. Performance evaluation results and optimization
3. Refined documentation based on user feedback and testing result

Intended Outcome:

• A robust and production-ready system that has undergone thorough testing, performance evaluation, and user feedback. The system is prepared for deployment and uses in real-world talent assessment scenarios.

[RESOURCES & VALUE FOR MONEY] Please provide a detailed budget breakdown of the proposed work and resources.

Phase 1: Deployment of Issuer and all its dependencies

• Skill verification modules: 20,000 ADA
• Development resources: 40,000 ADA
• Infrastructure costs: 10,000 ADA
• Documentation: 5000 ADA

TOTAL= 75,000 ADA

Phase 2: Deployment of Holder and all its dependencies

• Development resources: 10,000 ADA
• User experience and interface design: 15000 ADA
• Infrastructure costs: 10000 ADA
• Documentation: 5000 ADA

TOTAL= 40,000 ADA

Phase 3: Deployment of Validator and all its dependencies

• Development resources: 10000 ADA
• User interface design: 15000 ADA
• Infrastructure costs: 10,000 ADA
• Documentation: 5000 ADA

TOTAL = 40,000 ADA

Phase 4: Test and Deployment

• Testing resources: 40000 ADA
• Bug fixes and refinements: 20,000 ADA
• Infrastructure costs: 10,000ADA
• Documentation: 5000 ADA

TOTAL = 75000 ADA

Additional Costs:

• Research and collaboration: 40,000ADA
• Project Management cost for 9 Months: 50000 ADA

GROSS TOTAL= 75,000 +40,000 +40,000 + 75,000 + 40,000 + 50,000 = 320,000 ADA

[RESOURCES & VALUE FOR MONEY] How does the cost of the project represent value for money for the Cardano ecosystem?

The cost for project management, infrastructure, and developer resources(both wage for paying developers and talents and resources they will need for development) is calculated using global rates as the team is a distributed team with persons from Germany, India, Nigeria, etc as such global standards were applied. A link to the cost of paying an average blockchain developer and PM is attached below

https://www.knowledgehut.com/blog/blockchain/blockchain-developer-salary

https://www.ziprecruiter.com/Salaries/Global-Project-Manager-Salary

Our rates were calculated using global standards but adaptable and minimized a bit to our need

[IMPORTANT NOTE] The Applicant agreed to Fund10 rules and also that data in the Submission Form and other data provided by the project team during the course of the project will be publicly available.

I Accept