Reorganizing Information Structure: CEO Johanna Cabildo of D-GN Redefines Artificial Intelligence Strategies Through Decentralization
New and Improved Interview
Hey there! Let's dive into a fascinating chat with Johanna Cabildo, fresh from Token2049 in Dubai where the AI future was hotter than a sandstorm. Between panel discussions and strategy sessions, Johanna sounded the alarm: the power of today's AI lies on exploitative foundations, but things are changin'!
As the CEO of Data Guardians Network (D-GN), Johanna is crafting an alternative. By gamifying and tokenizing data labeling, she's letting regular Janes and Joes from rural villages to urban gig workers, even refugee camps, claim their stake as tomorrow's AI trainers. With blockchain-backed provenance and community governance, D-GN doesn't just promise fair pay—it reimagines AI as a participatory, transparent system for human dignity.
In this tell-all, Johanna puts Big Tech's dirty data secrets under the microscope and explains how D-GN's community-driven data stewardship is flipping the script. From post-Token2049 reflections to a roadmap for investors and policymakers, here's why taking back the AI mirror has never been more urgent:
Q1. So, Johanna, you've just come off a wild week at Token2049 in Dubai-tell us the standout moments and insights from the conference!
Token 2049 had raw energy like a desert sandstorm. We discussed AI's future with executives from Hub71, droppGroup, Binance, Crypto.com, Tether, Pump.fun, you name 'em! The consensus? AI is as strong as the data that shapes it, and blockchain-powered Web3 is the key to a trustworthy future for that data. Meeting so many leaders reaffirmed D-GN's vision and showed the industry's readiness for a fairer, more inclusive data economy.
Q2. How did conversations at Token2049 resonate with D-GN's mission to decentralize AI training?
Our approaches aligned: we advocate gamification of user tasks and uphold the belief that data contributors deserve visibility, voice, and value. During the conference, we gained a massive boost of confidence. Our platform is not just exciting-it's a necessary next step in the Web3 space.
Q3. You've oft described today's AI as built on exploitative foundations. What do you mean by that?
Exploitation happens two-fold: first, public content is scraped without permission or compensation. Second, there's the underpaid labor of people labeling data under shady contracts. We want a more equitable, fair approach to AI training worldwide.
Q4. What aspects of AI's current data sourcing do you find most alarming?
What gets me is the illusion of neutrality. When AI is based on scraped content, it reflects the biases of its sources. And when it relies on undervalued laborers, we miss out on a wealth of diverse perspectives that shape the models. This combo creates brittle systems that ultimately fail those they're intended to serve.
Q5. Who decides what data gets included, and whose voices end up erased?
Right now, a few companies make these decisions behind closed doors. Their choices—what forums to scrape, what to exclude—shape the perspectives of billions of users. Marginalized communities and non-western narratives too often fall by the wayside.
Q6. How do these opaque systems fuel misinformation, and what real-world harms have you witnessed?
We've seen AI models confidently spread false medical advice or misidentify individuals, and often perpetuate discriminatory assumptions. Discrimination at scale becomes structurally harmful.
Q7. What does D-GN do to empower regular folks to be AI trainers?
We've built a gamified, mobile-first platform, optimized for entry-level smartphones and low-bandwidth LTE networks. It allows anyone—from students to gig workers, refugees to remote villagers—to participate in labeling and curating data. You'll earn USDT on the spot as you shape the future of AI.
Q8. What's an inspiring example of community-driven data stewardship you've seen thus far?
I dig the work of Mozilla Common Voice, which focuses on language preservation. It's all about bridging cultural ties, an area close to my heart. D-GN aims to take it a step further by scaling the impact and compensating contributors for their efforts.
Q9. How does D-GN's platform work, and how can someone in a rural area or even a refugee camp participate and earn?
You'll need a basic smartphone and internet connection. Our platform is designed for easy, quick access. In our gamified environment, you can engage in tasks such as tagging objects in images or validating translations. Upon completion, you'll receive instant USDT payments and gamification rewards like D-GN Points and badges.
Q10. What safeguards ensure D-GN's decentralized intelligence doesn't create old power imbalances in a new guise?
Transparency is our ace: all transactions, votes, and rewards are visible on the blockchain. Second, we embed ethics from the get-go—curating diverse annotator cohorts and introducing reputation systems that boost quality contributors.
Q11. What advice do you have for investors, builders, and policymakers ready to take back power in the AI realm?
Invest in ventures sourcing ethical data and keeping people at the forefront. Builders should make ethics a priority from the start. Policymakers can enforce transparency and recognize data contributions as real labor. We're flipping the focus from data quantity to pure quality now.
Q12. What milestones can the AI community expect from D-GN over the next 12 months?
We're moving from pilot to scale, launching the first two full modules and our Telegram mini app. We'll deliver standard text and image datasets, as well as rich voice, lip sync, and video datasets. Several Fortune 500 companies are already linking up to source ethical training data through D-GN.
Q13. Finally, for someone intrigued by data stewardship but unsure where to start, what steps can they take to enter D-GN's network?
Step in now! Explore a few bite-sized micro-tasks on our platform, join our Telegram, connect with our team, and secure your place on the early access list. Don't wait. Curiosity and lived experiences are enough. With D-GN, you're not just contributing to AI—you're shaping its future.
Token 2049 was like a whirlwind of energy, filled with insightful discussions about the future of AI with executives from various companies like Hub71, droppGroup, Binance, Crypto.com, Tether, Pump.fun, and more. The consensus was clear: AI's strength lies in the data that shapes it, and blockchain-powered Web3 is the key to a trustworthy future for data.
These conversations resonated deeply with D-GN's mission to decentralize AI training. The platform, which gamifies and tokenizes data labeling, emerged as a necessary next step in the Web3 space, gaining confidence from leaders in the industry.
Johanna often describes today's AI as built on exploitative foundations, with public content being scraped without permission or compensation and underpaid laborers contributing to data labeling under shady contracts. D-GN aims for a more equitable, fair approach to AI training worldwide.
One of the most alarming aspects of AI's current data sourcing is the illusion of neutrality. When AI is based on scraped content, it reflects the biases of its sources, and when it relies on undervalued laborers, a wealth of diverse perspectives that shape the models is missed. This combination creates brittle systems that ultimately fail those they're intended to serve.
Currently, a few companies make decisions about what data gets included, often erasing the voices of marginalized communities and non-western narratives. In opaque systems, these decisions shape the perspectives of billions of users.
These systems can fuel misinformation, leading to real-world harms such as spreading false medical advice or perpetuating discriminatory assumptions. Discrimination at scale becomes structurally harmful.
To empower regular folks to be AI trainers, D-GN has built a gamified, mobile-first platform that allows anyone, even those in rural areas or refugee camps, to participate. Users earn USDT on the spot as they shape the future of AI.
One inspiring example of community-driven data stewardship is Mozilla Common Voice, which focuses on language preservation. D-GN aims to take it a step further by scaling the impact and compensating contributors for their efforts.
To participate and earn on D-GN's platform, users need a basic smartphone and internet connection. The platform is designed for easy, quick access, allowing users to engage in tasks such as tagging objects in images or validating translations.
D-GN's platform ensures its decentralized intelligence doesn't create old power imbalances in a new guise by maintaining transparency and embedding ethics from the get-go.
For those interested in taking back power in the AI realm, Johanna advises investing in ethical ventures, making ethics a priority from the start, and enforcing transparency and recognizing data contributions as real labor. D-GN is moving from pilot to scale, with milestones such as launching the first two full modules and a Telegram mini app on the horizon.
For someone intrigued by data stewardship but unsure where to start, Johanna suggests exploring a few bite-sized micro-tasks on D-GN's platform, joining their Telegram, connecting with the team, and securing a place on the early access list.
