Learning Economy Foundation Report
October 11, 2022
Published by the Diplomatic Courier
JAIMY SZYMANSKI, YASEMIN DEMIRDÖVEN, GABRIEL GAROFANO, CHRIS PURIFOY, TERENECE LIFF
In this report, based on expert interviews, the Learning Economy Foundation explores Decentralized Autonomous Organizations (DAOs) as an Organizational Structure for the Internet of Education. It explores DAO’s key elements, their applications to public education utilities, and the governance questions that would arise during implementation. The intent of this report is not to propose DAOs as the solution for global or local education, but rather to learn from its many tenants through exploring scenarios where such a vast ecosystem of learning and employment might govern itself. It is our hope that in the process of this examination and extrapolation, we can unearth new ideas that prefigure an era of self-organization and governance.
UPDATE: This research led LEF to many unexpected conclusions, both proving the power and the liability of DAOs as an operating vehicle for governance. By the date of publishing, it was clear that the research had given us one clear answer—DAOs are not the answer, or at least not the whole answer, for governing the Internet of Education. As open source and standards based infrastructures came online throughout the stent of this report, it became clear that protocol driven federated network ecosystems could manage themselves, using W3C standards based protocols for verifiable credentials and digital ID, among others. The result will allow for a global autonomous network to form and self govern. An MIT License, open source software developer kit was published to allow anyone to setup their own decentralized learning and employment record ecosystem (See Dev Docs & Repo).
● A taxonomy of existing DAOs to better understand structural needs across a heterogeneous landscape of organizations.
● Threads that extend between a DAO’s intentional objective with its past successes and challenges—all the while, informing an ideal governance model that can improve efficiency while addressing interoperability.
● Categorical knowledge that can be used to generate regulatory frameworks and practices that may best benefit current DAOs and assist those to come.
● A decentralized Internet of Education ecosystem framework built around education utilities that will allow for the implementation of: equity networks, digital wallets with self-sovereign IDs and immutable credentials, skill libraries that contain transferable data, and other utilities that empower individuals with the value of their skills, education, and data.
Against a backdrop dominated by centralized and hierarchical organizations, one of the most prominent challenges a DAO faces is how it can participate and engage inter-organizationally without sacrificing the core attributes of decentralized governance and autonomy. At its origins, centralized corporations were structured to obviate potential inefficacies that can arise in dispersing power. Now, the open and immutable structure of blockchains enable real-time and transparent global participatory possibilities, making decentralized organizations a viable model that does not forfeit swiftness of action.
Yet, a common foundational structure that can both encompass the necessary flexibility a DAO needs and allow it to operate in a world of centralized organizations and corporations has not been fully defined or culturally accepted. In our taxonomy research, we rely on the structural foundation set forth in Decentralization: Technology’s Impact on Organizational and Societal Structure, by Calcaterra and 1 Kaal. The eight infrastructure institutions they define are included below, and serve as the backdrop for our exploration into best practices in DAO formation, governance, legalities, and community-building.
A decentralized economy requires:
1. Processing/smart contracts. The executive policing functions of our business and government should be automated to prevent corruption. Ethereum proved this was possible, to process secure and valuable business contracts in a decentralized network. Like Bitcoin, it won’t be efficient until it lives in a robust decentralized economy. It won’t last unless its governance is fixed.
2. Reputation. This is the proper goal, instead of money, for motivating good behavior in business and governance. Properly accounting for reputation switches the incentives from short-term zero-sum thinking to long-term positive-sum behavior. Without building a secure and meaningful reputational system, none of the other aspects of the decentralized economy will be effective.
Note: Though the authors cite History as its own institution for DAO governance, we have coupled it with Reputation as part of our research, as they are inherently linked.
“Eight Institutions for the Evolution of Decentralization,” By Craig Calcaterra and Wulf Kaal. https://wulfkaal.medium.com/eight- 1 institutions-for-the-evolution-of-decentralization-756e6a267b52
They both rely on the truth that a marketplace must be trustworthy, with past momentum, in order to be successful.
3. Governance. Decentralized power regulation has been a conscious goal since the 18th century. Today the technology has improved, so that it is possible to account for good and bad behavior on a near infinitesimal scale and reward and punish fairly. A sophisticated system of governance is required to effectively adjust to market changes and to maintain stability. Executive (automated policing), legislative (non-automated protocol development), and judicial (both automated and non-automated dispute resolution) governance must be considered.
4. Finance. Financial management within a DAO is complex and requires documentation and internal services to govern its use of a stablecoin to ensure long-term contracting for essential services; decentralized marketplaces for neutrality in trading platform; banking to absorb risk and increase efficiency of transactions; and underwriting to trust that transactions will be successfully processed.
Note: Though the authors cite Money/Coinage as its own institution for DAO governance, we have coupled it with Finance as part of our research, as they are inherently linked. They both require an existence and management of a decentralized representation of value that can be used widely, whether in fiat, coinage, or token format.
5. Services. A diverse DAO ecosystem is crucial. Consumers require many services our current economy provides, that all need to be decentralized, such as commerce and trade jobs. The gig economy is rife with horror stories, but a fully decentralized structure with proper governance could solve such problems.
6. Transcendental Values. DAOs derive unity from their ideals, their common goals and aspirations beyond the protocols. This final requirement is the most important for long-term stability, and will require eternal reevaluation. Decentralized institutions require strong unifying values to remain coherent.”
7. Legal Entity. In addition to the eight institutions described by Calcaterra and Kaal, we have added a ninth: legal entity, as a way to survey possible DAO legal structures. There are many issues to evaluate when it comes to the “legal wrapper” within which a DAO operates, including: attack surfaces, single point-of-failure, recognized legal structure, legal liabilities, and crypto regulations (some of which are further details in finance and coinage sections).
We recommend reading the remainder of their book, wherein Calcaterra and Kaal explore these categories in full, which have mostly been neglected by P2P engineers. The new tools of information technology can make major efficiency improvements in these traditional institutions.
In order to anticipate what is needed for long-term adoption of DAOs, we must use case studies and existing governance models to more accurately uncover the benefits and strains an organization may face in becoming wholly decentralized. This research aids our understanding of readiness to implement a DAO model. Within this section, we take a “literature review” approach to our research, sharing best-in-class resources from Web3 experts and organizations in order to outline general conclusions in each of the eight institutions previously defined. We also provide exemplary case studies of existing DAOs that have successfully implemented one or more elements of DAO governance and management.
At its bedrock, a digital smart contract is an innovative system for facilitating fully automated transactions. For DAOs and other blockchain-based interactions, where autonomy and transparent governance are indispensable attributes, the possibility to simplify and fortify inter- and intra-organizational agreements is pivotal and engendering. As such, smart contracts offer an elegant and reliable option that provide for the ever-evolving potential of truly decentralized and autonomous integration.
The nuclear principle that allows smart contracts to operate is simple: They are coded as conditional statements that function as iterations of an if-then proclamation. Contractually, this means automatic and independent fulfillment. When a set of predetermined terms and conditions are met, a smart contract selfexecutes. Tantamount to the implicit fact of convenience, precision, and autonomy, this self-acting function makes agreements possible without the need of a governing third party.
While traditional paper contracts rely on ponderously co-dependent agreements and manually overseen enforcement, smart contracts offer swift and punctilious
efficiency. Perhaps most importantly, by eliminating the bureaucratic hang-ups of third-party governed transactions, the potential for human error is also diminished. As a result, smart contracts not only mitigate the inefficiencies of third-party involvement, they improve fiscal savings by reducing the cost of intermediaries who are otherwise needed to handle, execute, and interpret contacts.
In addition to improved speed and accuracy, plus eschewing the many potential hurdles of human administration, the self-implementing nature of smart contracts also means an added level of security. Because they function unassisted and immediately, they eliminate the potential for nefarious interference that can occur at each transactional tier of a more traditionally processed contract.
One key element of DAO governance resides in reputation management and transparency; are those individuals who are contributing to the DAO through performing tasks, voting, and conversing the ones who are rewarded, or is it simply based on the “loudest in the room” mentality? The most successful DAOs have a well-documented approach to their meritocracy (including a wide array of contributions, from marketing to operations to judicial), one that easily travels and transitions among other DAOs and Web3 entities.
Self-sovereign identities are one way to track on-chain reputation within one or more DAOs, as engagement credentials are captured by decentralized identifiers, unique to individual participants. One a participant’s value is proven within a DAO in accordance with its meritocracy policy, they are rewarded with certain credentials that are now part of their self-sovereign identity (e.g. greater weight in voting, perhaps), in addition to any other coinage or token awards, which are also commonplace.
Opinions vary in our research on if reputation is contextual to individual DAOs, or if it should be transferable among Web3 properties. Additional research is needed into these questions, as well as the desired formula for reputational decay over time. According to Alchemy, tools like Govrn, Gitcoin, RabbitHole, and SourceCred are all 2 working on solutions to various reputation problems. As the applications of Proof of Attendance Protocol (POAP) grow, eventually these might be used for reputation management as well.
“Starting a DAO: The Definitive Guide to Creating a web3 Community,” by Alchemy. Updated March 11, 2022. https:// 2 www.alchemy.com/overviews/the-definitive-guide-to-starting-a-dao#dao-7
There are immediate questions regarding governance implicated in the very creation of decentralized tech-enabled systems. On the one hand, although a DAO revolves around the salient principle of decentralization, there must be an entity that creates, monitors, and ultimately, is held responsible for failures and corporate injuries.
To begin thinking about these questions is, in a way, to address a technological paradox:
● How can tech that distributes governance be governed?
● Who will be held accountable for technology that is, in its very nature, not operated by any single entity?
In our literature review, we uncovered several models for DAO governance and decision-making, each dependent on the goal of the organization and the community to be built. Below, we share the key elements of a token-based governance model as thoroughly authored by Alchemy.3
1. “Once you’ve set up your token system, the first step is Delegation. Commonly used by the DAO community are Tally and Boardroom, which allow for members to decide whether they’d like to retain their vote (self-delegation) or delegate it to another community member. Once this process is complete, token-holders can vote on active proposals according to the vote weighting system you’ve chosen for your DAO.
2. The proposal and voting process for most DAOs begins with Proposal Submission. New ideas for projects, initiatives, spending, and changes to DAO structure originate in working groups dedicated to these ideas, and they go through a period of informal discussion, undergoing refinements and iterations along the way. Eventually, an official proposal is submitted to the DAO. Initial proposal discussions take place in channels on the DAO’s Discord or Telegram.
3. Temperature and Consensus Checks. The next step in the process is offchain signal voting, and depending on the size of your DAO, you may not need these, or you may need multiple rounds. Uniswap has a temperature check
that assesses interest in the proposal and requires the involvement of 25k $UNI tokens to move forward, then a consensus check that requires 50k tokens to participate. These signal voting processes are usually conducted via hybrid Web2/3 platforms like Snapshot or Discourse, but can also be conducted via in-chat polling on Discord.
4. Next, the proposal moves to an On-chain Vote. You can use tools like Tally, sybil, boardroom, and Compound Governor for this process, but as mentioned above, often the final execution responsibility lies with the signers of the multisig wallet.
There are a number of emerging governance tools that streamline the process outlined above, and provide checks and balances to ensure execution reflects the goals of the community. Among these is Gnosis SafeSnap, a plugin that utilizes an oracle to verify that a proposed multisig transaction was actually voted for, keeping administrators accountable to the community.
Another developing governance framework is judiciary infrastructure: tools like Kleros, Aragon Court, and Tally SafeGuard allow for working groups to move quickly and execute while still maintaining accountability via independent value and budget checks. These “courts” have the power to revoke transactions or reclaim funds if deemed necessary.”
As previously outlined in the excerpt from Decentralization: Technology’s Impact on Organizational and Societal Structure, finance governance within a DAO requires 4 keen attention to detail in four categories as documented below by the authors:
“Stablecoin: This is a currency that doesn’t fluctuate in price. The artificially scarce bitcoin currency is deflationary as long as its market expands. Like gold, its fluctuation makes it unsuitable for daily commerce. Without stability, typical consumers will never hold their checking account in the currency. No one will make a long-term contract for an essential service.
Decentralized Marketplaces: Neutral platforms for trades in properties and services are needed for thriving business with various rules for participation.
Banking: provides a necessary service to absorb the risk of less secure but more efficient small transactions. These are then bundled before a more expensive but secure transaction happens with the central bank. In P2P, the redundant and eternal storage of the blockchain takes the place of the central bank.
Underwriting: We need trust that the transactions in the marketplaces will go through, or that otherwise the contract will be made whole by the platform running the marketplace. Underwriting is essential for every type of business transaction, every type of property, every type of worker/service you hire. Every type of economic action is made more efficient when decisions are hedged, so we can confidently change our investments, keeping the market liquid. Lending and insurance are essential catalysts for business that require someone to underwrite the risk. Like policing, underwriting can be decentralized and automated, giving each member the power to control the level of security they require.”
In implementation of treasury management, Alchemy offers several vendor considerations: “The standard for DAO treasury management is a multisignature 5 wallet tied to a treasury committee, which authorizes all transactions. Gnosis Safe is a reliable, lightweight solution for DAOs that don’t have specialized use cases. Multisis is an analytics dashboard built upon Gnosis, allowing for multi-wallet fund tracking, payments, and reporting. If you’re building on Solana, Squads is another powerful
multisig option. Other options to consider include Llama, which allows more complex analytics tools and proposal linkages, and Parcel/MultiSafe, which enable mass payouts in ETH/ERC-20, spending limits, and provide a comprehensive analytics dashboard”.
There are many different aims of DAOs, and with their goals come different service offerings. Below (Fig. 1), Twitter user @Cooopahtroopa has curated a master list (continually updated) of different types of DAOs and their corresponding core service offering.
Source: @coopahtroopa
Our research finds that, from the myriad of service offerings in the preceding image, there are four most common variants:
Fig. 1. DAO Landscape as Curated by @Cooopahtroopa2. Investment DAOs work like investment funds, governing venture capital, dApp projects, and more.
3. Grants DAOs are tailored for funding new projects, generally in the DeFi ecosystem.
4. Social DAOs are akin to exclusive clubs wherein participants gain membership by purchasing a specific amount of the DAO’s tokens.
Alignment of vision for the DAO, as well as incentivizing members in a valuable way, are core to the long-term success of a DAO.
Alchemy again offers expert guidance on cementing a framework in place on 6 transcendental values and community buy-in. They share, “The beauty of Web3 is in the fragile balance of game theory: a careful dance of stakeholders who all want different things, held together by complex cryptography. … The fundamental challenge for any DAO founding team, perhaps more critical than any that comes after, is the challenge of providing value, purpose, and incentive to every member of the organization.”
They go on to recommend incentive alignment and encouraged participation through meaningful experiences: “The best way to build resilient and scalable DAOs is to invest time into creating robust governance systems that enable flexibility in the face of changing circumstances and ensure a symbiotic relationship: the DAO continues to best serve the core community, and vice versa.” More on values and vision alignment, as well as incentivization, can be found on their site.7
Alignment on values is also of utmost importance in forming the DAO community and leadership circles as it applies to voting delegation. Many members of DAOs pick a steward to delegate their vote to, someone who has greater reputational pull within the community, but who shares key opinions and values on issues that matter most. There should be balance within each DAO in terms of priorities and interests, though all must share the same underlying vision for the DAO’s purpose and shared narrative to clarify its direction, services, and decision-making over time.
A DAO’s inherent feature of decentralization—which architecturally opens exciting possibilities for transparent governance, self-sovereignty, and equitable opportunities—also creates structural and legal complications. In order for a DAO to preside and interact in a overwhelmingly centralized and corporately-structured market, it needs to adopt a framework that allows its novel centerless form to correspond to the current models of operation. This can perhaps be most readily seen by examining the impediments a DAO faces in registering as an entity that can be legally recognized.
Currently, there are no concrete and complete precedents that inform the legal establishment of a truly decentralized organization. The ontological implication of how a DAO “exists” raises the important questions: What country or state laws do a decentralized organization operate under? And who is ultimately responsible for its actions? As they are now, DAOs occupy what amounts to a legal lacuna in which their boardless, decentralized shape is crudely fit into an extant legal mold. In other words, they need what is called a legal wrapper to house themselves in that establishes a single body that can hold legal liability. This allows a DAO to function in the simple modes of being taxed, attaining registry, and importantly, protecting members from being personally liable in the case of systemic contingencies such as litigation.
For now, a DAO can wrap itself in many of the existing corporate structures (NonProfit, General Partnership, LLC, etc.) until one is designed and designated that recognizes the unique tenets of decentralization. If a DAO does not choose a specific legal wrapper, it’s typically considered to be an unincorporated general partnership. Regrettably, this poses a high risk position for the DAO members who won't have liability protection, leaving them potentially vulnerable and personally liable. Conversely, many DAOs choose to be recognized as a Limited Liability Company that provides the structure and protection of a more traditional organization. The figure below (Fig. 2) shows some of the common routes a DAO can take to find the most appropriate legal wrapper for their particular goals.
There are however a few exceptions in the U.S. that begin recognizing DAOs for their distinct structural posture and requirements.
Below, we share multiple DAO case examples gathered during our literature review that exemplify successful governance principles and strategies for one or more of the previously defined institutions. Please follow the relevant hyperlinks for more detailed information from their sources.
Fig. 2. DAO Legal Wrapper Flow Chart, from Paradigm8
● DAO.AM is a case study of public authority governance, decentralized by DLT. It is noteworthy due to its voting governance template that separates token ownership and voting power into two different currencies. The first is the fungible token in form of wealth e.g. DAOstack native token GEN or BTC or ETH. Second is the voting-power it refers to as reputation which cannot be bought or directly transferred peer-to-peer.
● Bootsy Labs needed legal support for a new venture, the “Boosty Labs project”, and asked Legal Nodes for help setting up a legal structure for a decentralized project. They wanted their project to be able to attract investments, generate IP, and become a DAO in the future. Legal Nodes assembled and managed a virtual legal team operating across three countries to ensure a successful registration for both an operational company and a token-issuing company.
● BrightID is an open-source project with a global community of remote contributors who must collectively allocate work and payments to accomplish their goals. Aragon enables the governance structure BrightID has been longing for. BMAIN, the BrightID DAO, has a constitution ratified by its members that outlines their requirements and responsibilities. In February of 2020, BMAIN's members formed a legal entity and operating agreement.
● Finally, as an example of a DAO that is still undergoing growing pains, CityDAO gained international recognition with its communal ownership of a piece of land in the most remote corner of America. CityDAO’s Discord has channels in four non-English languages, sold out of citizenship NFTs, and has $15+ million sitting in a treasury. Administratively, their resources are dispersed and aligned objectives are just now starting to emerge. The ever-growing community continues to squabble on what to do next, as the council slowly develops the frameworks needed for structuring.
In Part I of our research, we outlined the critical infrastructure, governance, and legal considerations of DAOs in order to successfully bring multiple stakeholders together for decision-making and collaboration in an increasingly digitized and decentralized world. In Part II of our research, we will explore how to apply the characteristics of effective DAOs to the incredibly large and diverse Internet of Education (IoE) ecosystem.
A fundamental belief of the IoE is that the future of education must be centered on the learner, including a decentralization of data ownership from siloed structures. This new vision of education and employment is one in which data is not a source of friction, but instead equips individuals by establishing and recognizing the value in their work and skills––all while protecting their privacy. In part, this can be achieved by connecting the currently fragmented systems into a cohesive network of impact and accountability, governed by an IoE DAO.
In connecting disparate education and employment data streams, a future emerges wherein every learner amasses a Learning and Employment Record (LER). A term often used interchangeably with Comprehensive Learner Record (CLR), LERs serve as an extended transcript of every skill learned by an individual over a lifetime, accessible via digital wallet applications or other software via way of blockchain storage. Key qualities of LERs include: transparency, relevancy, equity, privacy, security, portability, and interoperability.9
The idea of a CLR initially evolved out of collaboration between the American Association of Collegiate Registrars and Admissions Officers and the Mozilla Open Badge specification. The more recent 1EdTech CLR specification, “enables multiple providers to create, transmit, and render a learner’s achievements in a digital, machine-readable format that can be curated and shared as verifiable digital credentials.” In parallel, the W3C has published a draft data model and set of 10 standards for Verifiable Credentials, the U.S. Military has begun work on a Universal Learner Record as part of its Total Learning Architecture, and the U.S. Chamber of Commerce and American Workers Policy Advisory Board have promoted IEEE’s work on an Integrated Learner Record.
As further scoped in Part I of this report, decentralized Web3 structures offer new solutions for digital governance of organizations, though the feat will not be without its challenges. That’s why, in the sections ahead, we outline key governance
“Learning and Employment Records: Progress and the path forward,“ American Workforce Policy Advisory Board Digital
Infrastructure Working Group, September 2020. https://www.commerce.gov/sites/default/files/2020-09/LERwhitepaper09222020.pdf
Nadeau, Greg. “Ed 3.0: The Internet of Education,” IEEE https://docs.google.com/presentation/d/
1I8vrcL4pnQpiWO_4KGep2R_fPgrnj-bpH_UtteCrgW4/edit?pli=1#slide=id.g6f5abd05d0_0_378
questions to be answered in regard to each of the IoE’s seven utilities (see Fig. 3) in order to move forward with an IoE DAO. It is our plan at the Learning Economy Foundation to answer the general and utility-specific governance questions outlined in this report in future research efforts.
1. Equity Networks: Equality in broadband access for all as a foundation for innovation.
2. Digital Wallets: Application layer to store and manage learner data.
3. Skills Libraries: Detailed skills descriptors for use in developing courses and assessing learner knowledge and experiences.
4. Credential Networks: Solutions for verifying that a learner earned a skill.
5. Skills & Career Compasses: Application layer to aid learners in mapping their skills to career choices and opportunities for growth.
6. Skills Clearinghouses: A skills marketplace for third-parties to analyze and act on learner data, shared securely and with data sovereignty.
7. Coinage & Incentives: Introducing an earn to learn model that pays learners for data labor, among other incentive structures for other ecosystem stakeholders.
Fig. 3: The Seven Utilities of the Internet of Education
In addition to the emergence of governance questions specific to each of the aforementioned utilities, our research uncovered more generalized questions surrounding DAO governance that apply to every Utility that must also be addressed, documented, and published transparently (see Fig. 2). Because, for decentralized solutions to make an impact where they are most needed, they must be more than theory. They must also be clearly governed, ironically oftentimes more so than centralized systems.
Additionally, federal and state governments have a critical role to play in advancing the development of many components of the IoE DAO and its utilities, including tracking and coordinating public initiatives with the private sector, as well as supporting and incentivizing Web3 innovation, infrastructure development, and entrepreneurship with program funding and policy reform. We have only begun our 11 research into answering the questions posed within this report, and will be continuing our research in the coming months.
Business
1. How can the IoE DAO avoid single points of failure? Eg. people who have too much influence or reputation or delegated voting rights.
2. What is the governance process for agreeing on decisions/ proposals and coming to consensus? Eg. the very structure of the DAO and how many days a proposal stays at a current level, time for questions, ratification, etc. Particulars requiring governance may include:
a. Process of posting topic/proposal on forum
b. Discussion timeline
c. Draft stage timeline
d. Timeline for contribution, edits, and questions
e. Level of engagement that must be reached to move to next stage (including level of stewards engaging)
f. Voting protocol and platform (eg. Snapshot)
g. On-chain ratification and platform (eg. Tally)
h. Automated process for executing on ratified proposal (if applicable, eg. when a budget proposal is ratified, money is transferred from DAO treasury)
3. Will different members have different voting powers or more/ less power?
4. Will vote delegation to a steward be allowed? If so, what is the governance structure/protocol?
5. How will DAO members be held accountable for actions, followthrough, communication, taking appropriate time to consider decisions, etc.?
6. Who in the IoE DAO are responsible for “policing” other stakeholders if they are in violation of the governance framework protocols?
Legal
1. If a legal issue arises, and the DAO doesn't incur the liability, who does within the IoE ecosystem?
2. What liabilities does each stakeholder have, and how are they communicated?
Technical
1. Should there be one agreed upon underlying technology infrastructure to support lifelong learning?
The principle foundation of the first IoE Utility, Equity Networks, is as simple as it is complicated: We must equip all learners with access to broadband and a digital device, regardless of location, background, demographics, or socioeconomic status. This is especially challenging on a global scale when considering unique populations like migrants or communities without access to base level broadband infrastructure. Access to the internet is the universal equalizer in ensuring that educational and employment opportunities are available to all. Though many other important technologies power the IoE’s utilities and end goals, internet connectivity and device ownership (or easy device access) are critical to success.
Though many private organizations are continually working to provide computers and devices to schools, a homework gap still exists in many communities wherein students can access the internet at school but do not have the means to do so at home to complete coursework. The same problem grows beyond primary education and into college and adulthood for many individuals who do not have the socioeconomic ability to access devices. Additionally, some geographic areas simply do not have access to reliable broadband service, if any at all. This paints a complicated picture of the ecosystem cooperation needed on a private- and publicsector level in order to truly deliver equity in broadband access on a national and global scale.
These pains often leave the responsibility of providing student access in the hands of post-secondary institutions, typically funded by grants or corporate donations. This was the case with Motlow State Community College in its 2021 partnership with TMobile, which provided 2,100 students free 5G smartphones with service. Each Galaxy A32 5G was pre-loaded with the college’s customized learning management system so students could connect with their coursework, classmates, and faculty at any time, from anywhere. This example showcases the bigger potential for strategic 12 partnerships to improve accessibility, to higher education audiences and other populations that may be otherwise socioeconomically or geographically disadvantaged.
“Motlow State Partners With T-mobile to Provide 2,100 Free 5g Smartphones With Service to Students,” Businesswire, Sept. 27, 12 2021. https://www.businesswire.com/news/home/20210927005780/en/Motlow-State-Partners-With-T-mobile-to-Provide-2100Free-5g-Smartphones-With-Service-to-Students
Though the initial logic of Equity Networks inclusion in the IoE utilities has centered on providing broadband access, the IoE at large will foster equity in additional areas for each learner as they traverse their unique educational and career path. Decentralization of learner data in the form of CLR/LERs affords new advantages over traditional transcripts and resumes, especially for people who have developed their skills through a wide or non-traditional range of experiences.13
Jobs for the Future and the AWAPB are two key organizations advocating for Web3-driven equity in workforce development, focusing on what individuals can do versus the degree they have. A recent AWAPB report posits: “The adoption of LERs will increase economic mobility for individuals who have been disproportionately impacted by degree-based hiring. Hiring and promotion practices that focus on skills will enhance the power of LERs and the efficiency of the labor market.”14
Delivering true equity in broadband access and career opportunity both nationally and globally is out of the scope of the IoE DAO if acting as the only governance body, as it’s a complicated problem that involves both public utilities and private sector innovation. However, many governance questions did emerge in our research regarding the jurisdiction, advocacy, and support of the IoE DAO in aiding the development of Equity Networks (see Fig. 5). Additionally, the LearnBit token economy, as enabled by the IoE DAO, may serve as the foundation for a new stream of income for learners who are paid for their data labor––income that could be funneled back into internet access or device ownership.
Deegan, Joe. “Digital Learning Records Make the Job Market More Equitable and CBOs Can Help,” Jobs for the Future, March 13 5, 2021. https://www.jff.org/points-of-view/digital-learning-records-make-job-market-more-equitable-and-cbos-can-help/
“Learning and Employment Records: Progress and the path forward,“ American Workforce Policy Advisory Board Digital 14 Infrastructure Working Group, September 2020. https://www.commerce.gov/sites/default/files/2020-09/LERwhitepaper09222020.pdf
Business
1. What role does the IoE DAO play in solving the wholeness of equity that impacts education? Eg. in developing countries, low income areas, and other socioeconomic problems on a global scale.
2. Are broadband networks eligible to become stewards in the IoE DAO economy? If so,
a. will they have voting rights?
b. will their incentivization be payment in tokens/ fiat to provide greater access?
c. are there other ways to incentivize them to provide greater access to broadband or devices?
1. Are all IoE utilities dependent on Utility 1?
a. What level of progress can truly be achieved without equity in internet access for all?
b. What can we move forward with without this Utility’s problems being solved?
2. Are there some network access points that are priority over others? g. mobile phones, school computers, libraries?
Legal
1. Will the IoE DAO involve itself in the lobbying and/or advocacy process required to ensure equitable internet access and infrastructure development? If so,
a. at what government level? Municipal too?
b. in the nonprofit sector?
c. will it lobby for corporate support? Eg. vote to fund donation to Apple to continue giving away computers to schools
Technical (None immediately identified during our research)
(None immediately identified during our research)
1. How do you determine who is qualified to receive a computer or device, and is this justification something IoE is part of conceiving?
The key value proposition of the Digital Wallet Utility of the IoE is to enable portability of a learner’s credentials. A digital wallet allows for easy access and control over sharing of individualized data with any educational institution or employer, regardless of location, data standards, and technology application used.
The digital wallet layer of the IoE relies on multiple elements to function: the wallet, the self-sovereign identity (SSID) owner, the distributed blockchain ledger, and a decentralized identifier (DID). In effect, digital wallets are applications created in the free market by developers to store any type of data point; in this case, learning credentials.
One key benefit of the Digital Wallet IoE Utility is that it provides greater autonomy and ownership to the learner in regard to their educational and experience data. In a future of SSIDs and verifiable learning credentials, learners not only have access to their data, but they can choose who to share it with on a granular level within their CLR/ELR. However, though laws are in place via the Family Educational Rights and Privacy Act (FERPA) around data privacy, verifiable credentials still do not protect learners from third-parties sharing the data once they’ve been granted primary access. There is still a trust layer that has not yet been solved for within digital wallets, verified credentials, and the IoE.
Focus on Digital Wallet
Proof-of-Concept: LEGO Foundation’s Super Skills! SuperSkills! is a learning game ecosystem and digital wallet for kids aged 5-12, developed in partnership with LEGO Foundation, to showcase W3C's Universal Wallet, a packaging of draft standards and open source frameworks by MIT, Transmute, and Learning Economy Foundation.
In SuperSkills!, children go on quests (playful experiences) to learn core skills, collect resources and creations, and adventure in seasonal narratives. SuperSkills! falls into the category of informal learning, but with the use of DIDs, VCs, and digital wallets,
Learning Economy Foundation was able to issue provable credentials for children that persist outside of the game. They can be presented and verified without having to communicate with our systems or LEGO, capturing the learning and putting control into the learner’s hands.
There is a digital learner wallet incorporated directly into the SuperSkills! application. It does not store any material on the end device. As co-owners of the Universal Wallet Interoperability Specification with MIT and Transmute, Learning Economy Foundation incorporated an implementation of the wallet and built out some important functionality around issuing and storing credentials remotely. The beta application was developed and launched to assist in championing the importance of three learning primitives of tomorrow’s educational landscape: decentralized identifiers (DIDs), verifiable credentials (VCs), and digital wallets. More information on LearnCard can be found here, and open source programing operations can be found here.
The data accessed by a digital wallet is most often stored and verified on a blockchain, though it is technically blockchain agnostic in that credentials can travel among blockchains as needed as part of a global infrastructure. By ensuring the global IoE is built around blockchain agnostic standards, we enable other organizations to innovate through use of the shared credential network (eg. IBM, Greenlight, Microsoft, and Salesforce, as they adopt the standards created by the Learning Economy Foundation). The design of digital wallets needs to remain in a free and competitive space that delivers choice to learners and ensures they cannot be beholden to one vendor for a lifetime, but rather have the ability to transfer among wallet vendors due to a foundation of standard protocols that are potentially upheld and governed by the IoE DAO.
Fig. 6. Sample SuperSkills! Mobile Application Wallet & “Gameplay”Many vendors are also emerging that offer blockchain and data solutions in support of Web3, the IoE, and decentralized identity and data solutions. One such company, Ontology, aims to increase privacy, transparency, and trust by offering the Ontology blockchain: A high-speed, low-cost public blockchain designed to give its users the flexibility to build solutions that suit their needs while also ensuring regulatory compliance. Key features include trustless universal authentication for websites and applications (allows users to log into multiple platforms without having to remember passwords); and a solution for online identity verification and accessing verifiable credentials, such as KYC verification, while also allowing users to protect their privacy through independent information authorization.
One type of digital wallet, a universal wallet, can store multiple types of data. There is currently a software development kit (SDK) being developed by Learning Economy Foundation (LEF) and MIT for W3C, in two parts: First, as a pilot for the Lego Foundation, and secondly, for the U.S. Department for Higher Education. The SDK doesn’t influence the application layer; however, it is simply built as guidance in recommendations on how to build applications following standard protocols on top of the digital wallet layer (the infrastructure).
Key governance questions emerge when considering the jurisdiction and limitations of the IoE DAO within the free market of digital wallet software applications. Digital wallets also have a symbiotic relationship with credential networks within the IoE (and therefore the latter’s governance framework), as the information accessed by wallet applications must first be verified by a credential network prior to encoding onto the blockchain. The Learning Economy Foundation
has previously identified multiple governance layers required within the digital wallet ecosystem (see Fig. 7), some of which will be addressed through the launch of and/or collaboration with the IoE DAO.
Business
1. What is the reach of the IoE DAO’s governance oversight when considering the free market, intermediate infrastructure layer of digital wallet software, and applications?
2. How does the IoE DAO governance framework impact pre-existing governance of other institutions working to create protocols (if at all)?
a. Eg. W3C already has its own governance procedures, so do they apply their pre-existing standard to digital wallets and ID registration? Does W3C simply become a stakeholder to vote in the IoE DAO?
3. How does the IoE DAO incentivize companies, developers, and institutions to utilize the same standard in order to create a global network?
a. Is there a penalty for not using it?
b. Are there some overlapping areas?
4. How do we incentivize the richness of reporting without incentivizing over-reporting or exaggeration that could happen in self-reporting without credentialing?
5. How can the IoE DAO ensure that a learner doesn’t get locked in to one specific software/app wallet vendor and remains the true owner of their credentialed data?
1. Who is allowed to write a credential into a wallet?
a. Who is allowed to delete?
b. What about when considering self-reporting?
2. Is each individual issuer responsible for creating governance and rules around written credential expiration? Or is it up to the wallet?
3. Are there ways to have multiple learner IDs on-chain?
a. Within a wallet, can there be different learner profiles with the same data using SSID?
b. How can we guard against a learner creating a “profile” of themselves that fits a job, while omitting other information that could potentially work against them?
4. How can the newness of digital wallet technology be overcome in order to entice people to participate in the IoE?
5. How can multiple versions of CLR/ELR that exist work together within the digital wallet ecosystem?
Legal
1. How does IoE DAO protect against third-party sharing of data and related threats? How do you:
a. incentivize or protect against bad actors?
b. protect learners and increase awareness of their rights and data protection?
2. How can the IoE DAO protect learners/wallet holders from AIdriven insights being gathered from combining multiple data sources, including traditional identity, to inform products/services/ opportunities outside of education?
Technical
1. What future ongoing role will the IoE DAO have in the development of SDK for universal wallets? Eg. Currently being developed by LEF and MIT for W3C.
1. How does SSID this impact know your customer (KYC) efforts?
a. What is the minimum KYC to verify the identity of a wallet holder?
b. Should biometrics be involved?
2. How can a key be kept truly private to avoid misrepresentation or identity theft/fraud?
1. Can any entity or stakeholder have a wallet ID on-chain?
2. Is there different functionality based on an entity’s classification? Eg. learner vs. HR system vs. government?
3. What governance is needed around registration/naming of digital wallets on chain?
The current model for tracking and proving skills data over a lifetime of learning approaches skills credentialing at a macro level. For example, an individual earns a degree or a job promotion to prove one’s knowledge of facts, skills, and other learnings. Unfortunately, in these broad, macro-level assertions, there isn’t an accurately documented understanding of the hundreds of skills and experiences that culminate into its creation. This leads to the need for the IoE’s third Utility: Skills Libraries that house detailed metadata or microskills that are used to better define, classify, and categorize broader learnings into a useful dataset.
Skills library taxonomies create the foundation needed to analyze skills data to produce new pathways for learners, find suitable employment opportunities, and even impact the workforce and skills gaps assessment at a national and global level. These libraries are ideally suited to be used by educational institutions and employers to create courses and job descriptions in the future that directly align with exact skills and proven competencies.
Part of the skills libraries ecosystem also includes badge credentialers (eg. Open Badges), and organizations focused on specific subsets of skills classification, like the
Open Skills Network’s (OSN) work on Rich Skills Descriptors (RSDs). RSDs are the microskills that compose any multitude of larger skills. With so many stakeholders in the skills library ecosystem, all with their own priorities and schemas, it becomes paramount to come to consensus on a foundational standard that is followed in order to link databases, interoperate, and ultimately make them actionable.
Interoperability is at the root of most challenges associated with creating a universal skills library that is essentially a master database of multiple smaller databases, each prescribed to their own skills schematic and taxonomy. According to the OECD’s 2021 Digital Education Outlook, the primary obstacle to automated credit transfers to date has not been technological, but social: Every jurisdiction (down to even the university or school) often has its own credit definitions and may be reluctant to make those transferable by using definitions established elsewhere. It’s doubtful 15 that every stakeholder within the IoE will ever adopt the same global standard for skills classification; rather, the choice will be up to the individual organization or employer. The goal is to incentivize them to adopt a standard that is universal and interoperable, in order to create a truly global skills infrastructure.
Separate from analyzing interoperability of data is assessing its exchangeability. Interoperability refers to the structure of the data on a technical level.
Exchangeability refers to the ability to assert whether one skill’s makeup is indeed similar enough to another. Skills descriptors may reside in separate skills libraries that use different taxonomies and definitions, so exchangeability is critical in order to understand which skills can be equated in analysis of capability.
One organization progressing in skills exchangeability is 1EdTech Competence and Academic Standards Exchange™ (CASE). A CASE skill is a statement of what a student can do, broken down into multiple levels of granularity within a relationship/association table (see Fig. 9 at right). The taxonomies at each level of definition are described as statements that
are associated with and dependent on other levels of the table, as well as other tables with interdependent associations. Through the interdependency and associations within multiple tables, students, educators, and employers can begin to understand skills pathways as well.
By breaking skills down to their granular level within each relationship table, they also begin to emerge as psychometrically equivalent to other skills descriptors in taxonomies that are independent of 1EdTech CASE, due to the transitive property. CASE is both a way of indexing content according to state academic standards and indexing assessment reporting categories.
Another significant challenge within the Skills Libraries Utility is usability; ie. how can learners, educators, employers, or other stakeholders easily access and browse the skills library? And, how can the IoE DAO help stakeholders understand what to do with the information within the library in a user-friendly way? 1EdTech CASE is tackling this problem as part of its work, beginning with an interlinked database and building an infrastructure to address UX on top of it. Of course, digital wallets are part of the UX compatibility conversation and infrastructure layer as well.
In parallel with educational institutions and other technology organizations developing skills schematics and databases for classification, corporations are also developing highly detailed, proprietary skills libraries to serve their own interests in hiring, training, cross-skilling, and talent retention. One challenge (and a goal of the IoE DAO) will be to incentivize such companies to not only share their skills classification criteria, but ideally transition to the adoption of a global skills schematic that is both interoperable and exchangeable. At the very least, a middleware layer of exchangeability would be critical to involving the private sector with the public goals of the IoE DAO.
Incentivization remains a challenge not only in the private sector but also in convincing universities and other educational institutions from the ground level to create courses based solely on rich skills descriptors or other microskill taxonomies.
Once courses and degrees can be broken down on a granular level of black-andwhite competencies, they are no longer unique, which is a core value proposition of choosing one university over another, as well as within their seemingly differentiated identities. Therefore, universities do not always see the incentive to break their existing courses into microskills, nor give other institutions access to their data. Without their agreement and cooperation, the IoE will have to rely on civil servant support and heavy-lifting, requiring years of regulation change and lobbying that will ultimately force university participation versus incentivizing it.
Preceding the implementation of core technologies that will underpin skills libraries and the IoE DAO at large, it’s important to consider how to best introduce the concept of decentralization to the many incumbent education and employment stakeholders that are accustomed to the status quo. When a technology solution is not completely understood by the people it’s intended to help, serve, or even disrupt, stakeholders quickly over-project what they think the technology can and will do to solve the problems most important to them. For this reason, it’s critical to spend time building confidence and understanding in the reality of the technological capabilities and those of a decentralized structure, in order to build trust and a foundation for collaboration.
This concept also applies to the eventual learner introduction to managing and having authority and ownership over their data, as well as how they can utilize it to drive their education and career forward. The idea of owning one’s own educational history and skills data––and having control over its storage, use, and sharing––is an entirely new concept to the majority of learners today. This realization can contribute to significant culture change within a school or company, as witnessed at IBM upon implementing its internal credential network.
Addressing governance is three-fold when considering the Skills Libraries Utility of the IoE: 1. Governance of the IoE DAO as it relates to skills libraries and descriptors; 2.
Governance of the universal skills standard framework (may fall under the former DAO governance); and 3. Individual skills library governance that will be left in the hands of individual developers outside of the oversight and jurisdiction of the IoE DAO. All three governance protocols must also consider data quality control as part of governance in order to increase the value of the data across stakeholders and analysis applications. Quality data yields more meaning from its analysis, ultimately creating greater value and incentivization to participate in the IoE DAO ecosystem.
Business
1. What is the IoE DAO’s role in encouraging and incentivizing educational and corporate adoption of skills schemas in courses, catalogs, training, etc.?
a. Or in sharing their skills schema with the rest of the IoE?
b. Or incentivizing the adoption of skills-based hiring practices?
2. What is the IoE DAO’s role in ensuring existing skills schemas and standards are interoperable and exchangeable?
a. Does the IoE DAO have any governance, voting, procedure over skills additions? Tagging?
b. How can the IoE DAO incentivize quality data creation by its member stakeholders?
3. What is the IoE DAO’s role in ensuring interoperability among other technology/application layer stakeholders in the skills libraries ecosystem: standards orgs, wallets, credentialers, HR software, etc?
4. How can the IoE DAO incentivize companies to share their proprietary skills libraries and RSDs with the greater IoE?
1. What standard for skills mapping and skills schema will be regarded as the universal standard, if any?
a. Is it even necessary to have a universal standard?
b. Who should define the metadata of skills libraries —the ich Skills Descriptors or microcredentials? A neutral party? OSN?
c. Who should define the inter-relationships of microcredentials, the taxonomy, the associations, the pathways?
2. Is some data more relevant than others, and is it therefore weighted differently?
a. Is this part of the RSD score?
3. Is all skills data included in a learner wallet?
4. What is the role of context (and related detail) and learning outcomes (proficiency) in a skill or microskill?
a. Across languages, locations globally, how does this differ and how can we plan for that?
5. Can anyone/entity create a new skills library/schematic?
Legal
1. Is the IoE DAO responsible for dispute resolution or any involvement among skills libraries creators when it comes to interoperability, exchangeability, descriptors, etc?
(None immediately identified during our research)
Technical
1. What role does IoE DAO have in the data structure (interoperability) that makes up a skill or microskill?
a. Or the technology required to analyze datasets?
2. How can we make the skills standard databases and individual learning records easily accessible, browsable, usable?
a. Is there a role for IoE DAO in this? At the infrastructure level?
3. How does the IoE DAO ensure the completeness, maintenance, and longevity of skills libraries at any given point in time?
1. What infrastructure is needed for learners to easily browse skills libraries and understand what meta skills they have earned, can earn, etc.?
2. How can we aggregate or combine fragmented data to create more meaning?
A credential network creates the protocols needed for data verification and sharing among wallets, issuers, educational institutions, companies, government agencies, and others in the education ecosystem. Without a credential network as part of the IoE, the aforementioned technologies and stakeholders are simply decentralized nodes waiting for connection and activation.
As conceptualized by IEEE (see Fig. 11 below), when a learner meets a standard as 16 defined in a skills library, an issuer asserts a cryptographically signed credential that can be held in any standard digital wallet app. This credential achievement may include associated evidence, results, context, or other metadata. Learners can control verifiable presentation to a reviewer in any jurisdiction without having the need for a data sharing agreement with the issuer.
A credential network provides verified proof that the credentials issued within wallets do indeed exist, that the culmination of them exists (eg. degrees), and that the skills were learned. Utilizing a public blockchain, the credentialed data is written and stored, immutable and verifiable, free from corruption. Blockchain technology can solve many governance issues before they even begin, including eliminating records fraud, streamlining and reducing the cost of records sharing and verification, returning control of personal data to individuals, and reducing institutional risk in
the process. The same benefits cannot be guaranteed if utilizing a private 17 blockchain or database. Below, IEEE shares a helpful graphic (Fig. 12) connecting IoE Utilities 1-4, showing the interconnected relationship among programmable credentials, learning and experience ledgers, credential publishers, digital wallets, and talent marketplaces.
The primary goal of IoE DAO within this Utility is to protect the learners, ensuring each credentialer is indeed legitimate, that credentials issued are of quality, and issued by those of authority. Quality assurance of credentials in educational contexts is an arduous, slow-moving task in many countries, adding governmental and legal complexity to the already complicated task of credential verification on a global scale. Adding employers that utilize credentialing for skills-based talent management to that endeavor requires additional interoperability and flexibility in verifying competencies over a lifetime––not only of-the-moment, but also recognizing prior learning in order to increase employability.
There is consensus among those we interviewed that credential verification will reach its full, intended use cases only if moving beyond knowledge acquisition as the primary element being verified. There’s richness in enhancing verification with the application of knowledge as well, and the illustration of an individual’s ability to absorb content and transfer it into practice. If only the credentialing the acquisition of knowledge, the IoE DAO will merely succeed in defaulting to existing, archaic educational structures that outline achievements without taking context into account. Credential decay and the need for re-verification is also yet to be addressed.
Four years ago, IBM recognized the need to change its career development program for employees to focus more on skills-based hiring in order to remain competitive in attracting a diverse and inclusive talent pipeline. They found that simply requiring a four-year college degree for a job was limiting, especially in communities where individuals may not have the opportunity to obtain a university certification but have the skills to be successful at IBM. As a large, fast-moving technology company, IBM’s roles also change quickly, translating into a constant need for up- and cross-skilling among employees to meet the demands of talent retention.
To provide guidance to its employees on career options and pathways, IBM first needed to understand what skills their employees had. They built a skills inventory to take stock of individual employee skills, eventually leading the company down the path of digital credentialing as a way to ensure an objective view of the skills employees claim to have, and also ensure the credentials are reliable and accurate. Digital credentials are earned, verified, and stored in individual employee wallets, and they expire after a certain period of time if an employee is not recertified.
Though IBM’s program is private and its data are stored on internal databases versus a public blockchain, its tangential Skills Build program allows individuals outside of IBM to take the company’s training, build skills, and get IBM certification through Credly. Credly badges move with them between jobs in and out of IBM. That’s where blockchain becomes important, in order to reduce the friction and barrier of transferring skills out of IBM and to another employer.
Credential networks may consist of many stakeholders within the IoE, leading to potentially cumbersome governance processes and decisions in managing roles, duties, permissions, dispute resolution, crisis management, and other abilities. Simply because a DAO is inherently autonomous in many of its decision-making protocols and verification, doesn’t necessarily mean its leadership is decentralized. It’s likely that upon the creation of the IoE DAO, and its credential network, certain stakeholders would naturally emerge as leaders, oftentimes based on engagement level with DAO activities (proposal review, voting, ratification, discussion, etc.). Legal liability of each IoE DAO member must be made clear and is wholly dependent on the legal structure chosen and outlined in greater detail earlier in this report.
In the future, the IoE could become a “credential network of credential networks,” acting as an overseeing governance body that ensures open-source development packages are available, and interoperability and data standards are upheld as new credential networks are created. More critical than the intentions of the IoE in creating a master credential network with packaged developer protocols, is the question of how to govern both the IoE’s network and the subsidiary networks that are connected within it. Governance considerations include credentialer identity verification and trust (including reputation within the IoE DAO and other Web3 environments), as well as credential revocation, publishing, protocol creation/ changes, and credential issuance.
Fundamentally, the IoE DAO needs to consider what degree of gatekeeping is needed within the IoE credential network by a governing body, versus what degree of governance for each stakeholder is left to the free market (eg. Credly, Badger). Is the role of the IoE DAO one of authoritative control over who can issue a skill, a watchdog role over negative activity, or a governor of skills decay and recredentialing? Questions of the ability for the DAO to scale arise when considering these potential roles of the IoE DAO.
1. Does IoE DAO need to be the authority for a credential network?
2. Who can issue credentials on the IoE network?
a. Why does IoE need to be in control and play a gatekeeper role on who can issue skills?
b. How can IoE maintain scale as gatekeeper against speed of credentialing?
3. Can any school or employer connect to the IoE’s credential network? Are there certain criteria that must be met?
4. How does IoE DAO incentivize universities to transition from National Student Clearinghouse (NSC) when they’re profiting off of the current model?
5. How does IoE convince learners and stakeholders that there is value in cryptographically verifying credentials?
1. How do we differentiate a credential for attaining/acquiring knowledge (eg. taking a course) vs. the application of that knowledge and illustration of an individual to absorb content and transfer it into context?
2. What types of credentials can be published to a credential network?
a. How are credentialing criteria different for an educational institution vs. employer vs. another steward in the network?
3. Who can issue a protocol change to how credentials are shared?
4. Under what circumstances can credentials be revoked?
a. What is the process for dispute resolution?
5. How is self-reported skills information handled, and who governs it?
a. Does it have to be credentialed by a third-party within the credential network?
6. How do you account for the saturation of credentials and badges? Eg. when different third-parties are issuing credentials that are comparable to other intermediaries, which is the trusted one?
a. Does this enable or inhibit the free market?
7. Is reputation part of being a “trusted issuer” on a credential network?
a. Is reputation transferable?
b. Does it decay over time?
Legal
1. How do we protect against bias and subjectivity in credentialing in order to protect the learner?
2. How does IoE protect against one organization dominating the credential network—to protect against them controlling it for their own interest?
1. What protections are in place for learners to ensure their skills are being issued by a verified and trusted credentialer?
a. Is there a registry of trusted issuers?
b. How do you become part of the registry?
c. Can you be revoked from the registry?
d. Do you have to re-register after a period of time?
2. Who has the authority (and what is the process) to challenge a credentialer? To prove fraudulent activity? Quality assurance? Legal?
3. What are the recognition authority counterparts in governments, globally, to authoritative providers?
Technical 1. What is included in the IoE credential network’s software package of protocols?
1. How do proprietary credential networks communicate with public credential networks?
2. How do you ensure the data protocols and standards are interoperable and comparable?
3. How do “middleware” companies fit into the equation? Eg. National Student Clearinghouse.
Skills and career compasses are the “GPS of learning,” using AI to analyze myriad skills assertions that a learner amasses throughout life to map out opportunities for career and educational growth and pinpoint potential skills gaps. Also referred to as skills pathways, these career compasses would require triangulation of three types of data in order to create pathway recommendations: job requirement data from an employer, learner wallet data, and course-level data.
The more data points included in the analysis of a learner record to create an ideal career pathway, the better. Consider the impact that existing databases could also have (Indeed, LinkedIn, Upwork) when included and verified in a learner’s wallet. The best and most accurate skills and career pathways systems will be those that are
connected into the existing infrastructure of related utilities, versus ones that rely on a learner to self-report.
Studies show that learners are ready and willing to embrace the open, objective model of methodologically earning credentials to fulfill technologically prescribed career path requirements. A 2021 Oracle survey reported 85% of employees want technology to help define their future, to identify the skills they need, ways to learn those skills, and take the next step in their career. More specifically, the same study found that 82% of the same cohort believe AI can support their careers better than humans. As IBM has witnessed in its program, uptake is quick, and adoption grows 18 rapidly when the company culture shifts toward embracing growth, upskilling, and cross-skilling to achieve ultimate success, happiness, engagement and satisfaction.
Companies like iQ4 have developed learning supply chain models and product offerings to connect relevant datasets among learners, educators, and employers to create career compasses that benefit all stakeholders (see Fig. 14 below).
Doniger, Alicia. “In this job market, more workers are choosing AI over humans for career advice,” CNBC. Oct. 26, 2021. https://
www.cnbc.com/2021/10/26/82percent-of-workers-say-ai-can-support-career-growth-better-than-humans.html
Employers are incentivized to input data into a learner’s skills wallet in order to contribute to creating the most accurate picture possible of their credentials, and then utilize those very credentials in the future to determine appropriate skills and fit for a position, or plan a promotion or upskilling opportunity based on algorithmic interpretation. If the IoE DAO can contribute to the delivery of qualified individuals— who have demonstrated and proven their skills—to employers in the exact context and timing they’re needed, it can dramatically improve the efficiency of a hiring organization.
Examining this on the macro level, skills pathways data is also being used in economic development on national and global stages:
● In a pilot program managed by the U.S. Chamber of Commerce, skills data is being used in talent pipeline management (TPM) and in determining skills gaps at a national and global level, which ensures students and employees are learning 21st century skills needed to compete in today’s labor market and fill unemployment gaps.
● Walmart has provided a grant to Credential Engine to work with various states to inform how learning and employment records can be effectively implemented through linked, open data that provides people with the ability to manage their credential and skill information, and to facilitate
employment and economic development.19
● Education 4.0 is also a subset of a critical World Economic Forum addendum stream as part of its reskilling agenda. Today, most countries have poor structures in place to reskill their workforce and prepare them for jobs of the future. Using the utilities and principles of the IoE, we can begin to provide the tools needed to transform education systems around the world to be more oriented toward lifelong learning.
Within this Utility, much product development and innovation will be needed to create the machine learning algorithms that analyze learner data for gaps and opportunities, while also aligning with employer expectations and talent pipeline planning. Career pathing requires complex algorithms, unlike the more linear model that exists today (eg. the structure behind a medical degree), especially in industries like technology where jobs and skills are constantly evolving. For this reason, an algorithm must be able to not only see a learner’s skills and match them to an eventual career goal, but also be able to reverse engineer those individuals who are already in the “goal position” to determine the hard and soft skills that they have earned and other determinants of success in the role.
One skills category that becomes critical within this Utility, and is not yet solved for, is soft skills: skills like leadership, communication, empathy, problem-solving, temperament, and more. Many times, soft skills are not as rigorously assessed, if at all, as part of a learner’s record. Or, they are left up to being analyzed by individual teachers or managers without adherence to a standard or metrics for comparability and exchangeability. However, these skills and their psychometric profiling are of
“Credential Engine Will Use Linked, Open Data to Improve Learning and Employment Records,” Credential Engine, Jan. 19, 19 2022. https://credentialengine.org/2022/01/19/credential-engine-will-use-linked-open-data-to-improve-learning-and-employmentrecords/
critical importance when assessing an individual’s likelihood to succeed within a certain role, team, or occupation. The application of new machine learning algorithms will also be necessary in order to extrapolate soft skills data from existing data on past experiences and learning outcomes.
The “free market” nature of developing within this Utility is an important distinction to remember when assessing the IoE DAO governance needs, as much of the governance procedures will likely be left to each individual company to assert and manage in the private sector.
Legal (None immediately identified during our research)
1. Who/what institutions at the government level needs to be involved in the IoE DAO to ensure national, global skills (and reskilling) pathways are connected to economic and workforce needs in both the short- and long-term?
1. How can the IoE DAO change learner perceptions of career planning to utilize skills and career compass applications and share data with their employers/future employers?
2. How can the IoE DAO incentivize employers to share skills and career compasses that are unique to the pathways within their organizations?
3. How can the IoE DAO incentivize educational institutions to consider eventual career pathways in their course skills catalogs?
a. What governance role does the IoE DAO have in employers incentivizing learners to earn a credential/learn a skill in order to receive tokens?
b. Do employers have to follow a protocol to do so, submit a proposal, etc?
4. Who is responsible for determining the “single point of truth” for what skills and experiences are needed to achieve a certain career, position, etc.?
a. Is there a standard from the IoE DAO, or is it up to each individual company?
b. Should the IoE DAO offer templates to begin with?
c. Are members of the IoE DAO required to share career paths with the ecosystem?
5. What is the IoE DAO’s role in coordinating between employers and education providers in order to assess what skills are needed in the workforce (job market) and aligning that to educational competencies?
1. Can anyone access skills pathways?
a. Do you have to be a member of IoE DAO?
2. How can today’s adults who have been learning for a lifetime translate their skills into a new pathway?
3. How are workshops and event data incorporated from millions of sources into a career pathway?
a. Do workshops and events also need RSDs?
4. How are soft skills tracked and their development incentivized amidst more quantifiable hard skill credentials?
5. How can exchangeability and interoperability among career pathways application/software providers be ensured?
1. Does the IoE DAO have a role in the software/application layer of browsing skills pathways resources?
2. Does the IoE DAO “own and operate” a skills pathways data lake that can govern who can use it and for what purposes?
1. What infrastructure is needed to connect online job databases to career pathways applications?
2. What role will AI and automation play in guiding learners through career pathways, gap analysis, opportunity analysis, hiring, promotions, and firing?
a. Will there be human stopgaps for approval and analysis?
A skills clearinghouse is essentially a decentralized data marketplace wherein learners own their data and get paid for the data labor they create. Their data is anonymized using differential privacy tools and aggregated into a decentralized data clearinghouse for analysis by third-parties. The learner is always unilaterally in charge of the decision on how much data to share, and what identifiable details the data includes (eg. demographics, psychographics).
The idea behind an IoE skills clearinghouse is that big data can help solve big problems. The data from learners, educators, employers, and other relevant education stakeholders within the clearinghouse can be queried to solve challenges across the ecosystem, and at a macro level within government and society to improve learning outcomes, provide educational opportunities to disadvantaged populations, and solve complex issues related to unemployment and talent pipeline management.
As the United States emerges from a historic economic downturn and seeks to decrease unemployment, there is a critical need for improved labor market information and enhanced employment data for evidence-based policy and the administration of government programs. JEDx is a data standards-based approach for how employers can produce enhanced and more timely data on both jobs and employment.
JEDx aims to streamline and improve how employers report data to government agencies. This produces better longitudinal data about jobs and employment to power new workforce analytics while protecting privacy. It will also empower
Americans with data and trusted records to verify their work history as well as their eligibility for government benefits.20
Once a learner has opted into sharing their data with the marketplace (either on a one-time basis or continually, even as new data is created), they are paid for the labor of their data within any number of analyses over time. Rather than being paid for the marginal contribution of the data itself, being rewarded for the labor of the data creates greater incentive as the total net profit can scale and accrue faster over time.
The fundamental technology underpinning a skills clearinghouse is the blockchain, as it allows for decentralization of all data while maintaining security, privacy, immutability, and transparency in how the data is being used by stakeholders. Other technologies that enable the use of a skills clearinghouse are artificial intelligence and software that can analyze the data for trends and patterns, which are ultimately displayed in a dashboard for easy consumption. Such analysis may include understanding which individual skills are contributing most to workforce development, which teachers are most impactful, and which workforce tools lead to advancement. Ultimately, the answers to these questions could also impact the value of steward tokens and certain types of learner data.
Governance within this Utility centers on data protection, control, access level, ownership, and data labor. With the right protocols in place, the only way to access the clearinghouse is to become part of the larger IoE DAO economy, paying tokens to access it. By doing so, value is created for the whole economy, token demand increases, and the value of data rises as the value of tokens being owned and sold by learners grows.
Business
1. Can anyone access the data clearinghouse/marketplace? Do you have to be a member of the IoE DAO?
2. What is the best economic model for paying learners for their data labor?
a. Does frequency, longevity, types of data, etc. impact payment?
b. Who will monitor the economy of the Learnbit (and scarcity) as it relates to buying access to aggregate skills data?
3. Will the IoE DAO govern the possible use cases for using the skills clearinghouse dataset?
a. What is the revenue model for querying the data (eg. do organizations pay more for more crosstabs)?
1. What transparency expectations and protocols will be in place for the clearinghouse and those using it, and to what purposes?
2. Who will absorb the costs of ratifying all cleared data on the blockchain?
Legal
1. How does the IoE DAO ensure there are no illegal or otherwise nefarious uses of the “big data” in the clearinghouse?
1. Who owns the data once it is in the clearinghouse? IoE DAO?
Technical
1. How can the IoE DAO also ensure the learners and their data are protected, and that they understand their options for privacy, data sharing, and risks for exploitation?
1. How will AI be used in the querying of the skills clearinghouse database?
a. How will AI ethics be monitored?
The key theme of incentivization of each stakeholder within the IoE culminates in the seventh and final Utility: Coinage and Incentives. At the most basic level, individuals who participate in the IoE DAO by providing data or performing data labor become part of a (potentially) three-sided economy and token exchange that benefits learners/employees, educators/data stewards, and investors/organizations performing data labor (see Fig. 17 below). The coin used within the IoE, a LearnBit, is valued on a baseline, plus impacted by the supply and demand of learner data available and being used at any given time.
1. Learners - Choose which of their data to share with the marketplace
2. Stewards - Educators, schools, employers, teachers
3. Investors- Those performing data labor or investing in the market by purchasing LearnBit outright
Fig. 17 Note: Initially, a two-sided economy will likely be implemented that accounts for learners and investors only, with stewards added at a future date once a proof of stake/learn mechanism of unlocking “learn blocks” on the blockchain has been further researched and tested, and transaction verification protocols have been established within the economy.
Learners choose what data to share anonymously within the Skills Clearinghouse, according to their privacy selections, and are paid LearnBit for the data labor as their data is used in any variety of analyses by third-party stakeholders. The LearnBit can then be reinvested in their lifelong learning. This is often described as an earn to learn model. Stewards earn LearnBit based on the value of their contribution to learning outcomes, workforce development, or other positive impact as determined by longitudinal algorithmic analysis. There may also be the opportunity for a general “investor” within the IoE, an individual or organization that either performs data labor/analysis for a set token price or invests capital in an educational steward or learner who they believe will have a positive impact on future learning outcomes.
There are numerous possibilities for tokens within the IoE, utilized as economic instruments to stimulate and balance various parts of the economy. Sample tokens may include:
● Talent Token helps employers find talent for their hiring and employee development pipeline. Employers could create a talent token for a skill that pays an amount to a learner who can either verify they have that skill or will earn the credential. Once the learner has shared their verified skill with the employer through their wallet application, they are paid the bounty and are entered into a hiring relationship with the employer. This benefits the employer’s pipeline, as they can put bounties on skills for emerging positions or future opportunities. Talent Tokens and bounties may also be offered to existing employees in order to incentivize up- and cross-skilling.
● Scholar Token works similarly to the Talent Token, but the bounty given is in the form of a scholarship, “micro-scholarship,” or grant. A foundation could create a scholarship to fund future learners in a certain field they believe is important to solving a societal or economic problem. The individual scholarships within the fund would then only be available to learners who could prove they have a package of verifiable credentials that fits with the criteria of the scholarship. Programmed with smart contracts, once verified, scholarship funds are automatically sent directly to the school.
The scholarships could fund education in phases, beginning with partial micro-payments, and eventually growing into full scholarships that will require additional standards development. When considering microscholarships, they would be made possible through ongoing micro-payments for individual credentials as they’re added to learner digital wallets––truly enabling an “earn to learn” (or, even, “earn to live”) tokenomics model that aides in solving last-mile equity challenges. Scholar tokens could also be used for urban development that would pay entrepreneurs seed money for creating businesses, jobs, and contributing to their community.
In another approach as outlined by Bankless DAO, members of the IoE DAO 21 could invest in students and fund school expenses and in return receive an allotment of each students’ LearnBit token. Upon graduating and starting a career, a percentage of the student’s income would be reinvested in the IoE DAO for a select period of time to make it self-sustaining. This may also benefit the IoE DAO if there is a price increase of personal tokens from the time they were issued and/or invested in.
“Funding the Future through Scholarship DAOs | State of the DAOs,” Bankless DAO, April 2022. https://
banklessdao.substack.com/p/funding-the-future-through-scholarship?s=r
● Steward Token (in a three-sided economy only) is also an equity instrument, wherein the equity being sold is off of future earnings within the economy. For example, a teacher could do an IPO of themselves, selling a certain percentage of their Steward Tokens to people who believe in them and the educational outcomes they will create. Then, as they earn tokens from the eventual impacts they create, those are repaid to the investors and also in part to the steward themselves. Steward tokens could be earned and sold by any stakeholder who is responsible for creating a learning outcome.
● Work Token is simply paying a bounty for completing a project. Much like the popular Gitcoin marketplace, a project with bounty is posted that includes details, work to be completed, and timeline. In order to “unlock” the project and bid on it or complete it, the contractor must have one or more verified credentials as set by the employer. The Work Token has the potential to disrupt the current model for gig economy workers as set by websites like Upwork where skills and experience verification are difficult, if not partially impossible.
● Index Token is similar to the stock market indices, as in it’s the “every man’s investment” vehicle to get involved with the IoE economy. An investor chooses a certain skill or skills grouping (e.g. Leadership Index), and disperses funds into those assets in a one-time or recurring investment that earns the investor money over time if the skills index chosen proves valuable in frequency, job creation, or any other metric that indicates impact.
Another factor of the IoE economy resides in the financial equity of leadership and participants in the governing IoE DAO. Active DAO contributors will be those who have proven they bring value to the DAO and the IoE ecosystem––whether in marketing, operations, or other leadership excellence––and that value should be translated into a verifiable credential that ultimately rewards the most active and impactful contributors with both greater share of voice/voting power, and/or coinage or tokens within the economy.
From a cost standpoint, depending on what blockchain the IoE DAO is governed on, it costs a varying amount of money to delegate or cast a vote. This fee goes toward the cost of ratifying it on the blockchain (eg. approximately $80 to cast a vote that is
ratified on Ethereum at the time of this writing). It stands to reason then, that the most active, engaged, collaborative, and impactful members of the DAO should be rewarded with additional token share in order to cast or delegate votes, among other revenue uses.
These verifiable credentials tied directly to outcomes within the IoE DAO would become part of each individual’s on-chain reputation, with the potential to carry that reputation (just like any other verified credential) to prove their skills and engagement in any other DAO.
Technical 1. What middleware layers need to exist for “work tokens” to function properly? Eg. a productivity gauge that renders you ineligible at a certain threshold.
1. Who sets the criteria for what makes “good data” that can be used in data labor?
2. Is there an autonomous exponential effect that continues to reward the original credentialier if their credential is used as part of another skill or credential grouping in its downline?
1. How is the value of a LearnBit determined?
2. When and how will the IoE DAO transition from a two-sided economy to a three-sided economy?
3. What is the general incentive for participation in any part of the three-sided economy, beyond an initial token drop?
a. How can the IoE DAO maintain motivation throughout onboarding and through engagement and participation?
4. Who determines the right algorithm for calculating steward impact?
a. How is it tracked longterm?
b. Who is responsible for longevity studies (qualitative or quantatative) to determine impact?
c. Can any steward do an IPO of themselves?
5. Is the machine learning layer of impact analysis similar to digital wallets in that it’s a free market and different vendors will emerge? Or is it something IoE DAO governs?
6. Is it the responsibility of the IoE DAO to track reputation or a thirdparty intermediary layer (where it’s free market, app layer)?
a. Should an IoE DAO member have a greater reputation score if they’re an active steward or token holder at any level of the DAO itself? Or does that preclude them?
7. What is the formula of equity in the IoE DAO over time?
8. Does being a member of the IoE DAO offer intangible benefits outside of currency? Eg. streamlined support and services.
1. What is the value of quantity vs. impact in units of learning?
a. How do we define value over time?
2. Who decides what tokens can exist as dependent on LearnBit coin?
a. Who is responsible for their creation, governance, etc.? The IoE DAO?
b. What if an employer creates a token for a certain skill bounty?
3. Who develops and decides which model for reputation-based governance is best for stewards within the economy?
a. What elements go into reputational score or decay?
b. What weight do elements like longevity have in reputation score? Eg. a teacher who has been teaching a long time.
c. How can a steward’s reputation score be "gamed," and is it the responsibility of the DAO to police reputational gaming?
Legal
1. How does IoE protect against bounty “gamification,” mining for bounties, nefarious actors, etc.?
a. How are people sanctioned if they are trying to “game” the incentive or revenue systems?
2. How can IoE DAO work with governments and city infrastructures to incentivize developments, entrepreneurship, and lifelong learning built on tokens?
3. How can people exit the IoE DAO and immediately get refunded for any investments?
1. What laws govern the skills index tokens? Is it similar to how a mutual fund works in the stock market? Who tracks impacts of indices over time—third party or IoE?
The prospect for an IoE DAO, and those who will use it to create revolutionary ripples in the existing currents, is not so far off. A global interest in decentralization is already underway, and the exciting possibilities are beginning to take the hopeful shape of reinvigorated policies and procedures. It’s our hope and commitment at the Learning Economy Foundation that this research will contribute to the devoted community of decision-makers pushing the borderline of transparency, accessibility, and equitability in education.
● Info Storage: Ability for any individual to be authoritative holder of DAO entire records of history.
● Data Processing: individuals equally participate in filtering and curating information.
● Networked Communication: speedy and affordable global connections (i.e. Internet) allows fully transparent bureaucracy.
● Interoperability: Standards for connecting nodes on a network.
● Cryptography: security, privacy, control of personal info.
● Distributed computing: security, trust, transparency.
● Smart contract security and encryption, continued: Digital contracts are encrypted, and each transaction is connected to previous and subsequent records on a distributed ledger, further heightening contract security, as any transaction would have to be complexly modified across multiple ledgers to be altered. Unfortunately, while this in theory prevents fraudulent activity, in practice, this has proven not to be an infallible approach, and in 2016, a smart contract was used to steal 50 million . While the potential for smart contracts 22 to improve the security of autonomous transactions is viable, they are still in fact vulnerable and need refinement to prevent the kind of malicious security attacks that result in breaches and pecuniary loss . 23
For the Internet of Education (IoE) DAO, specific conceivable security risks can only be identified once the distinct parameters of the contracts that will be used are determined and attack surfaces can be pinpointed. Once that is finalized, the best solution to forestall those precise vulnerabilities can be investigated and implemented. Importantly, much progress in the protection of smart contracts has been realized and enacted since the 2016 transgression, and organizations such as Oyente (a smart contract auto-auditing tool) , 24 SmartInspect (which identifies bugs, automatically finds solutions for reported issues, and monitors applications) , and ContractFuzzer (a novel 25 fuzzer to test Ethereum smart contracts for security vulnerabilities.) have all 26 offered some promising and pioneering solutions that address some of the most pressing vulnerabilities and security risks for smart contracts . 27
WIRED: A 50 million hack just showed that the DAO was all too human. Available online at https://www.wired.com/2016/06/50-
million-hack-just-showed-dao-human/ (2016).
[5] https://link.springer.com/article/10.1007/s12083-021-01127-0
Atzei N, Bartoletti M, Cimoli T (2017) A survey of attacks on ethereum smart contracts (sok). In: International Conference on
Principles of Security and Trust, Springer, pp 164–186
Luu L, Chu DH, Olickel H, Saxena P, Hobor A (2016) Making smart contracts smarter. In: Proceedings of the 2016 ACM SIGSAC
Conference on Computer and Communications Security. Association for Computing Machinery, New York, pp 254–269
Bragagnolo S, Rocha H, Denker M, Ducasse S (2018) Smartinspect: Solidity smart contract inspector. In: 2018 International
workshop on blockchain oriented software engineering (IWBOSE), pp 9–18
Jiang B, Liu Y, Chan WK (2018) Contractfuzzer: Fuzzing smart contracts for vulnerability detection. In: Proceedings of the 33rd
ACM/IEEE International Conference on Automated Software Engineering. Association for Computing Machinery, New York, pp 259–
Praitheeshan P, Pan L, Yu J, Liu J, Doss R (2019) Security analysis methods on ethereum smart contract vulnerabilities: A
survey. arXiv preprint arXiv:1908.08605
In July 2021, the state of Wyoming made monumental progress by passing laws that redefine how digital organizations and cryptocurrency companies can operate within their state. Saliently, under the Wyoming Bill, a DAO is legally recognized as a unique entity. Under the Bill, DAOs are treated as an LLC, which provides a concrete legal status and gives DAO members liability protection. Although in effect, this does have a very similar application as a DAO that is simply operating as a traditional LLC, it does set a foundational precedent on which to define the needs and legitimacy of a DAO’s idiosyncratic structure.
On the other hand, the Wyoming Bill has certain cardinal limitations. Most immediately, the bill requires that a DAO LLC must be recorded with a Wyoming registered agent who meets the statutory requirements (W.S. 17-28-101 through W.S. 17-28- 111). In essence, this ties the DAO and at least one of its members to the state of Wyoming, which conspicuously contrasts a DAO’s very core feature of decentralization. In a sense, the Wyoming Bill can be understood as a bridge that connects the tangible and corporately organized business world to that of DAOs, but also one that needs further construction to meet the needs of full decentralization.
After Wyoming, on April 6, 2022, Tennessee became the second state in the United States to create a statute to recognize DAO’s. The new legislation amends Tennessee Code Title 48 to allow LLCs to register as DAOs. Like the Wyoming Bill, what is 28 perhaps most critical for Tennessee’s legislative adoption is a forward reaching gesture that demarcates the need for new jurisprudential methods of recognizing DAOs. Noteworthy in the case of Tennessee is that it’s possible for DAOs to be registered as a DO (Decentralized Organization), broadening the practical scope of operation by acknowledging that DAO’s are not always completely automated. Similarly, the new Tennessee Legislation, under section 115, opens the possibility for foreign DAOs to apply for a certificate of authority as long as they are based within the United States, continuing to widen jurisdictional limitations from state to nation. If the Wyoming Bill is an unfinished bridge, the Tennessee legislature gets closer to connecting the current gaps, although there are still opportunities to develop legal precedents that incorporate full decentralization.
Although in its consultation phase (as of August 2022), The Coalition of Automated Legal Applications (COALA) has put forward a Model Law that details procedural practices giving DAOs more thorough legal palpability. Principally, The Model Law, just as the Wyoming Bill and Tennessee's new legislature, will recognize and treat a DAO like an LLC. What makes The Model Law unique is that it offers a possible unified national approach toward DAO identification. One way it posits this can be accomplished is by stipulating that if The Model Law is adopted by one state, any DAO that operates within a certain prescribed set of rules and regulations will have legal identity in any state that has adopted the law. This transient property of recognition means wider and more complete legal options for the DAO community. Moreover, The Model Law also suggests that instead of requiring a geographically positioned present individual (like the Wyoming Bill), DAO’s should be able to simply use a registered mailbox to establish themselves, which would further grant the possibility for national and even global recognition.
As evident in the preceding legal examples, the issue of location is a critical factor in addressing solutions for decentralization. It makes sense, because of their inherent principles, DAO’s are not obviously based in any one certain jurisdiction, and the very fact of being decentralized precludes many of the traditional forms of governance that are both geographically and structurally based. Currently, there does not seem to be a clear-cut answer to what jurisdiction a DAO may pick to protect its projects and members. To choose the most suitable legal wrapper, first the DAO’s intent/ scope must be decided, as a legal wrapper will act as a protective shield between a DAO and the real world. The table below (Fig. 19) might be a helpful example in determining the path a DAO might follow.
Q1: If a legal issue arises, and the DAO doesn't incur the liability, who does within the IoE ecosystem?
To assign liability, the DAO will need to be registered and or adopt legal rules to qualify as a legal entity. DAO’s that are registered as a corporate registry which
means that they have adopted a national set of laws. However, DAO’s that are unregistered have legal uncertainty. Unregistered DAO’s can be classed as illegal.
The current structure of a DAO does not follow traditional hierarchy, as they are decentralized organizations they do not protect their members from unlimited liability. As there is no hierarchy in DAO, there is also no limit to the liability of each member. For example, a member of an Limited Liability Company (LLC) would only risk their capital contribution (limiting the liability to the percentage the LLC member owns/ has invested).
The main concern here for DAO members is that they are classed as unincorporated partnerships which means each member has unlimited liability. The general partnership rules make it possible for the contributors to be liable personally for debts. This means that if DAO goes bankrupt or is sued, each member will be liable until the debt is paid. If the debt is not satisfied they could take personal assets to recover and repay the debt.
Q2: What liabilities does each stakeholder have, and how are they communicated?
This will depend on what structure the DAO embodies. For example, if a DAO registered as an LLC, certain members will have certain liabilities and equally will be protected from certain liabilities. However, within the DAO’s decentralized structure it is unsure how liability would be assigned. To assign liability one must know the identity of the member.
If the stakeholders have liabilities the following must also be answered: Does liability increase with experience within DAO, and how can the DAO be sure that the member identified is capable of taking on the task before becoming liable? For example, if liability will not increase with experience/more investment as in a traditional company, is it fair to assume everyone is equally liable?
Q3: How does IoE DAO protect against third-party sharing of data and related threats?
a. How do you incentivize or protect against bad actors?
b. Protect learners and increase awareness of their rights and data protection?
A lot of the protection that surrounds DAO will depend on the legal identity it chooses to have. For example, considering IP rights, how would the DAO protect itself against infringement?
This would depend on how the DAO in question identifies itself legally and the jurisdiction that the case is being considered in. Under U.S. law, a group of people working together towards making a profit will be classed as an implied partnership and therefore can enforce their rights. Legally partnerships are recognized and can go to court.
Q4: How does SSID impact “know your customer” (KYC) efforts?
a. What is the minimum KYC to verify the identity of a wallet holder?
This would depend on the jurisdiction/ governing body. Generally:
● Minimum one form of government issued identity/ some jurisdictions require 2. (ID, passport, driver’s license.)
● Some jurisdictions require a validation of address. (ie, letter with address on, driver’s license etc).
Looking globally, Switzerland, Liechtenstein, Singapore and Cayman Islands have a high standard for KYC. On the other hand, Panama, the British Virgin Islands, or the Marshall Islands have much more tolerable requirements for KYC or do not require it altogether.
Q5: Is the IoE DAO responsible for dispute resolution or any involvement among skills libraries creators when it comes to interoperability, exchangeability, descriptors, etc.?
A system within IOE DAO to resolve issues may be a good option as to not involve the outside governing body. Keeping it within the DAO with the rules and regulations appointed could avoid disputes being taken to court, where governing jurisdiction will play a big role.
Q6: Who has the authority (and what is the process) to challenge a credentialer? To prove fraudulent activity? Quality assurance? Legal?
This would mainly depend on who the verifier is. Who is the credentialer? How vigorous is the system in ensuring the credentials are verified correctly? Depending on the rules of the credentialer, the remaining could be answered.
Again, if the DAO is registered with a jurisdiction, the answers would depend on the certain laws within that jurisdiction.
Q7: How does IoE protect against bounty gamification, mining for bounties, nefarious actors, etc.?
Within the DAO, registering as an LLC may pose some questions as to the abuse of limited liability of members. This might lead to various attack surfaces being created. However, if all members make a financial contribution to a reserve pot of fund through a smart contract executed within the DAO, the contributions could be used for possible liability claims.
The more the rules and regulations there are, the more possibility of attack surfaces are created.
Q8: How are people sanctioned if they are trying to game the incentive or revenue systems?
This could depend on the legal identity the DAO choses to have. The DAO could enforce the rules and regulations that the legal identity provides for sanctions, or it can make its own sanctions coded within smart contracts, like limiting voting or limited issuance of new tokens.
Q9: What laws govern the skills index tokens? Is it similar to how a mutual fund works in the stock market? Who tracks impacts of indices over time - third party or IoE?
If the token is recognized as a “security,” it will fall under domestic law. SEC issued a report investigating whether DAO tokens were securities. In the United States, securities mean “investment contracts.” SEC uses the 'Howey test' established in the case SEC v. W.J. Howey Co., If there is an investment of money in a common enterprise with a reasonable expectation of profits to be derived from the entrepreneurial or managerial efforts of others, there is an investment contract. SEC has underlined that regardless of whether the entity is a traditional company or a DAO. the securities law will apply.
This research was developed through extensive primary and secondary qualitative research and literature review methods. We interviewed 20 web3 and DAO experts, members, influencers, vendors, and other adopters between November 2021-April 2022. Input or mention in this document does not represent a complete endorsement of the report by the individuals or the companies listed herein.
● Kerri Lamoie, Digital Credentials Consortium, MIT Open Learning
● Sharon Leu, Jobs for the Future
● Wesley Teter, UNESCO
● Jason Tyszko, U.S. Chamber of Commerce
● Primavera de Filippi, Harvard University
● John Goodwin, Learning Economy Foundation
● Robert Hawkins, World Bank
● Alex Kaplan, IBM
● Greg Nadeau, IEEE
● Humpty Calderon, DAOversity, BanklessDAO
● Frank Cicio, iQ4
● Duncan Cox, Learning Economy Foundation
● Bhaumik Patel, Ceramic
● Simona Pop, Gitcoin and SuperRare
● Chris Purifoy, Learning Economy Foundation
● Jackson Smith, Learning Economy Foundation
● Wulf Kaal, DEVxDAO
● Sheila Warren, Crypto Policy Group
● Jason Yonker, ReToken DAO
● Tyler Yonker, ReToken DAO