2.1 Background: Data Explosion and the Lack of Trust
[Paradigm Shift from Quantity to Quality] In the early 21st century, humanity believed that "Big Data" was the new oil and engaged in a frenzied rush to collect and accumulate it. As a result, the volume of data in the digital space has continued to explode. According to IDC's (International Data Corporation) "Data Age 2025" report, the amount of data generated and consumed globally is predicted to reach an unimaginable scale of 175 Zettabytes (ZB) by 2025.
[The Paradox of the AI Era] This is an amount that, if recorded on DVDs and stacked, would travel between the Earth and the Moon 222 times. However, now that the AI era has fully arrived, we face a cruel reality. It is the paradox that "while there is more than enough quantity of data, 'trusted data' to make AI smarter is hopelessly depleted."
["Digital Pollution" by Generative AI and Model Collapse] Ironically, it is AI technology itself that is accelerating this crisis. With the spread of generative AI, the internet is flooded with blog posts, images, and code created by AI. This "Synthetic Data" looks high-quality at first glance, but in reality, it often contains factual errors, subtle noise, and biases.
[The Danger of Model Collapse] What happens if AI models continue to indiscriminately learn from this "inaccurate data made by AI"? Researchers call this "Model Collapse" and are sounding the alarm. This model collapse leads to a loss of data diversity and quality, causing AI to become unable to correctly perceive the real world, thereby amplifying hallucinations (plausible lies) and extreme biases.
["Trust" as a Scarce Resource] Traditionally, the internet brought about the "democratization of information," but currently, the "dilution of truth" is progressing. In a sea overflowing with articles by unknown authors, manipulated evidence images, and public opinion manipulation by bots, AI development companies and decision-makers have no way to verify, "Is this data truly correct?"
[Garbage In, Garbage Out] AI performance is governed by the principle of "Garbage In, Garbage Out." No matter how high-performance the GPUs or algorithms are, if the training data is polluted, the output is nothing more than sophisticated garbage. Therefore, the resource that is skyrocketing in value and most scarce in the AI era is not computing power, but "Trusted Data" with clear origins and guaranteed content. The DEP Protocol meets the demands of the times as infrastructure supplying this depleting resource.
2.2 Challenges: The Macro Situation
[The $15 Trillion Cost of "Bad Data"] It is said that "data is the new currency," but what if much of that currency is counterfeit? The modern economy is in exactly that state. Inaccurate, incomplete, duplicate, or tampered "Bad Data" disrupts corporate supply chains, worsens marketing ROI, and leads to erroneous management decisions.
[Astronomical Economic Losses] According to a famous IBM study, losses due to poor quality data in the US economy alone reach $3.1 trillion annually. Extending this estimate to global GDP and system-wide inefficiencies, the loss balloons to an astronomical figure of $15 trillion to $20 trillion annually worldwide.
[Absence of Proof of Humanity: Threat of the "Dead Internet"] More serious than economic loss is the "loss of humanity" in digital space. The "Dead Internet Theory," which suggests that nearly half of internet traffic is occupied by bots (automated programs), is becoming a reality.
[Ad Fraud and Impersonation] This problem is particularly prominent in the digital advertising industry. Advertisers pay huge sums to be "seen by humans," but in reality, bots click on ads and drain budgets. According to Juniper Research predictions, losses from such ad fraud will exceed $172 billion annually by 2028. Furthermore, public opinion manipulation on social media and impersonation scams using sophisticated deepfakes are rampant, creating a state where we cannot even confirm the obvious fact that "a human is on the other side of the screen."
[Urgent Need for Infrastructure] This absence of "Proof of Humanity" is shaking the trust foundation of digital society to its core, making the establishment of solid infrastructure as a technical countermeasure an urgent task.
2.3 Solution: The Verified Data Economy
[From "Storage" to "Verification": Transformation of Infrastructure] The role of traditional cloud storage and databases was to efficiently "store" and "transfer" data. However, in the current flood of fake data, mere storage functions can be a risk rather than valuable. The DEP Protocol redefines the definition of data infrastructure from "Storage" to "Verification."
[Strict Checkpoints] Our network establishes a strict "checkpoint" before data is recorded on the blockchain (L1). Here, anomaly detection by AI algorithms and cross-checks by decentralized human validators are performed.
[Multilateral Examination] For example, when data indicating "task completion" is sent by a user, we multilaterally examine its authenticity by combining GPS information, device gyro sensors, consistency with past behavior patterns, and visual confirmation by random humans (Human-in-the-loop).
[A Clear Stream of "Authenticity-Guaranteed Data"] Only data that passes this verification process is given a cryptographic signature and engraved on the blockchain. The data generated this way is no longer a mere list of information. It is "Verifiable Data" where the provenance (traceability) of "when, by whom it was generated, and who guaranteed its correctness" is fully proven.
[Value for Data Buyers] For data buyers such as AI development companies and advertisers, this means obtaining a "clear stream" filtered from muddy water. By using the DEP Protocol, they can minimize the risk of their AI learning wrong information (hallucinations) and prevent ad spend from being exploited by bots.
[Creation of a Clean Data Economy] Furthermore, we make this system function as an economic sphere. Users who provide high-quality data and participants who perform verification work (validation) are paid fair compensation (DEP Tokens) according to their contribution. This creates an economic incentive to generate and circulate "honest data," forming a "virtuous cycle" that gathers even more high-quality data from around the world.
[The Anchor of Trust] The DEP Protocol will become the "Anchor of Trust" as a social infrastructure in a future where information uncertainty is increasing, building a clean data economy where AI and humans can operate with peace of mind.