Web3 and AI: A Blueprint for Learning Architecture in the Digital Age

I recently gave a guest lecture in a Technology Leadership class for Doctoral Candidates, and in that conversation, we spent some time reflecting on the significant impact over the last two decades brought on by the exponential growth of technology. We watched a brief clip from the Today Show (1994), where the hosts were trying to describe things like email and the internet, and to think, a mere 30 years later conducting our class over Zoom, ordering our groceries online with delivery to our door, and on and on. Access to mobile hardware and the web has transformed our lives in many ways, but I posit that education has changed very little in that same time.

I would contend that education today remains largely unchanged from the designs found in the early 1900’s where the focus was producing student generalists capable of plugging into the machine of the Industrial Revolution. Students are tracked by age and grade, subjects are siloed, and methods for measuring learning have remained largely unchanged, or even in the case standardization doubled down with the push for measurement of learning through test scores.

Meanwhile, the world outside has faired very differently where technology has touched just about every part of our lives. In the last 5 years we have seen the maturation of web3 technologies like the metaverse, blockchains, digital assets, and more recently the explosive growth of AI-powered technologies. Given the immense change we have seen in the last decade, we can expect that we are approaching the next technological renaissance affecting every facet of our lives; education notwithstanding is on the precipice of its own transformation.

The digital age demands an educational paradigm that transcends the rigidity of standardized systems focused on testing and other incomplete metrics of learner growth to one that embraces the fluidity and dynamism of personalized learning experiences. This is where the combined forces of Web3 and AI come into play, together these complimentary technological forces can usher in revolutionary learning architectures better suited to the digital age.

In this post I aim to more clearly define a possible future where these two technologies can work together to build an architecture for learning that transcends the confines of school classrooms, traditional transcripts, and siloed learning experiences. While I believe there is immense potential in this technology, it doesn’t come without its drawbacks or at least areas we must consider. I hope that my views here remain balanced between being a techno-optimist and a techno-realist and would emphasize that this piece is meant to generate discussion around one possible future for these technologies. I would encourage further conversation around these ideas both on the web and in your contexts.

The Interplay of AI and Web3 in Personalized Learning

There has certainly been a buzz around AI and its potential implications for education. The power of Large Language Models (LLMs) has been truly impressive and in just the last 12 months we’ve seen a significant increase in the capabilities of such systems due in part to larger data sets and improved algorithms. We’ve seen a Cambrian explosion of such systems in the last 12 months starting with ChatGPT, and now there are a variety of generative AI tools that can produce text and other types of media content. These tools are largely designed to be generalists meaning you can go to ChatGPT and have conversations about just about anything. While there are instances where these tools can be wrong while asserting they’re correct (hallucinate, yes that’s the actual term) they are impressively reliable across a wide range of topics.

Recently ChatGPT launched functionality to allow users to be able to create custom GPTs, which are versions of ChatGPT to focus on a specific use case. By providing the bot with specific instructions, guidelines, and even providing it specific information, you can in a sense train the bot to serve very specific use cases. In addition to ChatGPT there are other platforms allowing for this level of customization, one of my favorites is https://poe.com/ which allows you to provide some simple training and prompt boundaries and select the AI model you want the bot to use. I’ve created some sample bots that you can check out here:

Education AI Integration Strategy Bot: From the bot “I specialize in assisting educational leaders in developing a comprehensive AI strategy. Expect guidance on setting clear AI objectives, aligning them with your institution’s goals, and engaging stakeholders in this transformative journey.”

Instructocon- InstructoCon ensures every student’s learning needs are met. With this AI-powered coach, differentiated instruction is not just a strategy; it’s a daily reality.

More broadly we can see this type of focused AI emerge in some of the tech tools that we are all very familiar with. For example, Khan Academy recently released its Khanmigo bot, which is designed to serve as your personal learning assistant inside of Khan Academy. The tools functionality extends to both students who can benefit from a personal tutor, and to teachers who can use the AI to help glean insights and provide more personalized learning experiences.

AI: The Engine of Personalization

If we extrapolate some of these early examples that I shared above we can begin to see the potential to use AI to adapt to individual learning preferences and paces which could in turn usher in a revolution in personalized education. The ability of AI to analyze vast amounts of data to provide insights into learning patterns identify gaps, and offer predictive interventions would be a game changer in every classroom, every school, and every district.

Much of the discussion around the use of AI in education has centered around improving efficiency, preventing plagiarism, or creating more assessments; ie practices that further entrench teaching practices of the traditional system. It is sooooo incredibly important that we start thinking beyond where we stand today. It’s critical that we begin to scan the horizon and plan for further disruptions in and outside of education in order to prepare learners for the world of tomorrow.

Assessments Reimagined

In a system enhanced by AI, assessments need to evolve from standardized tests to a more holistic evaluation of skills and competencies. I would argue that it is critical we begin to move past the idea of assessing standardized skills through traditional testing methods because these are things that machines are becoming increasingly good at. You may have seen news reports that made headlines last year about AI taking medical boards, SATs, and so on and the stellar scores it produced, out-competing the average test taker on most tests. While the scores are impressive, it is important to note that in order to take these tests, the AI had to be given training data to take the test. This point has led to a lot of debate around these scores and whether this is just hype.

Regardless of where you stand on the issue, the reality is this technology is advancing rapidly. In the article, AI Can Pass Standardized Tests, but Fail Pre-School the author points out that AI is still relatively narrow in its ability to prove “common sense.” To be fair the article was published in 2019 and much has changed since then, but I would argue that one of the most important pieces of subtext here is that in an age of AI we must lean into those things that make us most human. In education that means focusing on skills and competencies that complement this power technology NOT competing with it.

Beyond the Screen: Experiential Learning

AI has the potential to greatly enhance experiential learning and open up new career pathways. When it comes to experiential learning, AI can provide learners with immersive and interactive experiences that go beyond traditional classroom settings. Through AI-powered simulations and virtual reality, students can engage in hands-on activities and real-world scenarios, allowing them to apply their knowledge in a practical manner.

By using AI, educational platforms can also personalize the learning experience based on each student’s individual needs and progress. Adaptive learning algorithms can analyze a student’s performance, identify areas of improvement, and provide customized recommendations and feedback. This personalized approach can greatly enhance the effectiveness of experiential learning, as it caters to the specific strengths and weaknesses of each learner.

Moreover, AI can play a significant role in expanding career pathways. With the rapid advancement of technology, the job market is constantly evolving. AI can help individuals identify emerging career opportunities and develop the necessary skills to succeed in those fields. By analyzing vast amounts of data, AI algorithms can provide valuable insights into labor market trends, helping learners make informed decisions about their career choices.

AI has the potential to revolutionize experiential learning by providing immersive experiences and personalized assessment. It can also help individuals navigate the changing job market by identifying career opportunities and offering tailored guidance. Through the integration of AI technologies, education can be more dynamic, inclusive, and responsive to the needs of learners, ultimately expanding their horizons and career possibilities.

The Good with the Bad

A world where every child gets a personalized learning assistant that can help propel them towards a future where they have the skills and competencies they need to do the work they wish to do is great, there are some real challenges here that need to be addressed.

AI models like ChatGPT represent a significant centralizing force requiring mountains of training data in order to be effective raising questions like what data? who is training it? what are they doing with user inputs? These questions carry a lot of weight, particularly in the education context where we are talking about the use of AI by our learners.

It is fascinating to explore how the convergence of web3 technologies, such as blockchain, and artificial intelligence (AI) can potentially address critical challenges in the field of education. While we are still in the early stages of this intersection, envisioning the possibilities can shed light on promising solutions.

When we consider the introduction of AI into education, we often encounter concerns about centralization. However, web3 technologies like blockchain can offer a decentralized framework, counterbalancing the centralizing force of AI. In a way, it can be seen as a harmonious balance between two powerful concepts, a yin and yang relationship. To illustrate this relationship, I’d like to highlight a few areas including:

• Data management and privacy
• Credentialing
• Access and Equity
• Quality Control

Data Management and Privacy

In the rapidly evolving realm of education technology, data management, and privacy stand at the forefront of concerns for students, educators, and institutions alike. If we are to consider how AI could be implemented in the educational context it could require the collection and analysis of large swathes of data to personalize learning experiences, assess progress, and predict educational outcomes. However, this raises significant privacy concerns, as sensitive student information could be at risk of misuse or breach. This is where the innovative application of web3 technologies, particularly blockchain, can provide a compelling solution. Blockchain’s inherent design encrypts data and ensures that it can be shared securely, granting access only to those who have been given explicit permission. This not only enhances security but also empowers users with greater control over their personal information.

The synergy of AI’s data analysis prowess with web3’s secure, transparent ledger systems has the potential to revolutionize how educational data is handled. Imagine a digital ecosystem where student data is treated with the same rigor as financial transactions—meticulously recorded, securely stored, and only accessed under strict protocols. This combination ensures that while AI works to uncover insights and foster learning innovations, web3’s ledger technology maintains an immutable record, safeguarding the data against unauthorized alterations and access. Such a structure not only protects privacy but also builds trust in the technology that underpins modern educational practices.

Credentialing:

As AI crafts personalized learning pathways that help learners blend learning experiences both in and out of school, as well as in-person and online education, there is a need for developing ways to enable learners to accrue and demonstrate competencies, skills, and understandings acquired from a variety of learning experiences.

Web3 technologies can be leveraged by generating unique credentials for learners and anchoring these credentials in a bedrock of verifiability and permanence. Blockchain technology, a cornerstone of web3, excels in ensuring that credentials remain tamper-proof and resistant to fraud. This is crucial in maintaining the integrity of the certification process, which has historically been susceptible to fraud. The trust established through blockchain’s immutable ledgers ensures that credentials issued within this new paradigm are both credible and innovative.

The richness of data in education can be overwhelming, but it is also a reservoir of untapped potential. Web3’s secure infrastructure provides a foundation for credentials that are not only portable across educational and professional platforms but also firmly in the control of the learner. This democratization of credential ownership marks a departure from institution-centric models, placing learners at the heart of the educational narrative. AI can assist in refining the learning journies through adaptive learning experiences, web3 complements it by making sure that the milestones and endpoints of these journeys—be it badges, certificates, or degrees—are recognized and respected universally. Such credentials are more than just records; they are emblems of a learner’s growth and capability.

Access and Equity

Access and equity in education are critical concerns that AI and web3 technologies are uniquely positioned to address. While AI has the potential to revolutionize personalized learning, its reliance on substantial computational resources can introduce barriers to access, exacerbating educational disparities.

The decentralized architecture of web3 can mitigate this by distributing the power required to run massive AI models across a network, reducing costs, and by extension, lowering the barriers to entry. This democratization of technology enables more widespread adoption of AI in education, ensuring that the benefits of personalized learning are not exclusive to those with more resources, but are available to a broader audience. By aligning with the ethos of web3, educational technologies can foster a more inclusive learning environment where every student has the tools to succeed.

AI’s capacity to enhance learning is undeniable, yet the concerns of algorithmic bias loom large, threatening to entrench existing inequalities. Web3’s transparent and collaborative framework encourages the creation of diverse and representative data sets, which are fundamental for developing fair and unbiased AI algorithms. In this collaborative ecosystem, stakeholders from various backgrounds have a voice in shaping the algorithms that drive educational AI, ensuring that these technologies evolve to serve a diverse student body. By prioritizing inclusivity in both the development and deployment of AI, web3 can help to level the educational playing field, creating opportunities for all learners to thrive.

Through the lens of access and equity, the partnership of AI and web3 in education represents more than technological advancement—it symbolizes a commitment to creating a fair and equitable learning landscape. As these technologies continue to mature, their role in forging an education system that is accessible, inclusive, and just becomes increasingly important. It is through the concerted efforts to address these fundamental issues of access and equity that AI and web3 will truly revolutionize the educational experience for learners worldwide.

Needs of a Shifting Paradigm

I would contend that in order to realize a future in which we achieve personalized learning in the manner which has been discussed for the last decade we must find a way to synergize the transformative powers of AI with decentralized web3 technologies. As we enter a new educational paradigm, empowering educators is critical. Just like for learners, AI stands ready to support educators’ professional development, providing personalized learning tools and insights that enhance their teaching methodologies. Web3 technologies offer a means to acknowledge and credential their professional milestones, fostering a culture where continuous learning and growth are not just encouraged but also recognized and valued. This harmonious blend of AI’s capabilities and web3’s validation system ensures that educators are not only well-equipped to navigate the new landscape but are also celebrated for their dedication to lifelong learning.

At the same time, we will confront many complex challenges ahead of integrating these advanced technologies into educational systems. Ed3 DAO is dedicated to abstracting this complexity into friendly community spaces, accessible educational content, and open events that empower rather than overwhelm. By doing so, we ensure that the focus remains on human-centric learning experiences, where technology acts as a facilitator rather than a focal point.

In uniting AI’s capability to serve as a personal learning guide and tool to scale personalized learning paths with web3’s capability to track and credential progress, we lay the foundation for a more equitable, inclusive, and dynamic educational experience. The interplay of these technologies promises a future where learning is a lifelong journey, credentials are a true reflection of one’s abilities, and education is a gateway to personal fulfillment and societal contribution. As we forge ahead, Ed3 DAO is committed to leading the charge in crafting an educational ecosystem that is not only effective and secure but also inspiring and aspirational for every stakeholder in the journey of learning.

If you’ve made it this far, thanks so much and I’d love to hear your thoughts!