Disclosure: The opinions and opinions expressed here belong to the authors solely and do not represent the views or opinions of the crypto.news editorial.
On the surface, AI and blockchain share many commonalities. Both are transformative technologies that could rebuild every industry you touch. Both have attracted enormous amounts of investment, not to mention the hype. And both are dull tools, their full power only appears when they are fiercely sharp and equipped with precision.
You might like it too: AI is built closed rooms, but that’s a dangerous mistake | Opinion
When AI and blockchain are intelligently combined, you can achieve strange things. AI effectively zeroes the marginal costs of intelligence, while blockchain effectively zeroes the marginal costs of adjustment, and hence rich. Intelligent autonomous system. A verifiable framework for data tracing and content attribution. A circular economy for allocating digital resources. But that doesn’t mean that every pair brings to the table. When blockchain is carefully combined with artificial intelligence, it has the ability to address the most concerning flaws of the latter. They are troubled by the current form of AI, so they don’t make mistakes.
Who do you trust?
Artificial intelligence is rapidly revolutionizing the industry, from automating common tasks to improving customer experiences. But AI is deeply embedded in critical decision-making, from healthcare to transportation, transparency and accountability alarms, so it rings loud. Bias, manipulation, and opaque decisions threaten to erode trust in AI and undermine its great potential. Here is the chance for blockchain to shine. As a distributed, immutable ledger acts as the basis for truth, AI can seep into the currently lacking verifiableness and ethics. Blockchain brings trust to technology that is currently missing.
AI bias is like climate change. It’s nowhere, nowhere. It’s impossible to argue, but it’s often difficult to put your fingers on. Occasionally exaggerated, such as Google’s Gemini tool, producing prominently inaccurate historical images. But more often, what we have is the feeling that something is off, let alone not only dealing with it (for example, Deepseek R1 claims that Trump is the former president of America). And don’t start “Alignment Faking.” AI aims to please while secretly maintaining its own agenda.
Beyond bias, backdoor attacks pose a terrible threat. Malicious actors can embed hidden triggers during training, and when AI is activated, they misinterpret and misinterpret images with certain patterns. Such vulnerabilities run the risk of putting your system at risk in real time without any simple fixes. As AI becomes more human, it tells us that it is inheriting our worst habits.
There’s one thing AI can ruin with image generation. The other is because of autonomous driving algorithms that ignore stop signs. And that’s not the worst that can happen when AI isn’t going well.
High Stakes Game
In highly safe fields such as aviation and robotics, reliable AI cannot be negotiated. Aviation is increasingly dependent on AI in air traffic management, predictive maintenance, and autopilot systems. Here, failures for biased or hacked algorithms are fatal. AI is good at predicting mechanical failures, but saves billions of dollars in downtime, but its reliability requires monitoring. Aviation AI diagnostic tools can misinterpret and misinterpret data when trained on a defect set. Public safety relies on transparent and accountable AI.
When cars were first invented, accidents were not uncommon, but were not fatal due to slow and shortages in vehicles on the road. However, once the automotive industry speeded up and engines became more powerful, safety measures were needed to reduce traffic accidents. AI is currently a Model T-stage: Game Changer, but the final form has not yet been realized. As artificial intelligence moves into gear and becomes embedded anywhere, the risk of failure and bias increases exponentially. This is why it’s time to act to fix AI flaws. This is where blockchain can prove to be invaluable.
Accountability as a Service
Blockchain brings accountability to artificial intelligence. Distributed, invariant designs can record training data, model parameters, and decision logs, allowing for independent verification of AI integrity. Every time a model shoots, the DATA input, training cycle, output – is auditable by anyone and cannot hide behind a secret source that is an opaque algo – the Provevial Black Box.
Now, Blockchain does this work with our money, providing a record of truth that allows us to deeply trust and transfer billions of dollars each day thanks to public verification. This same transparency prevents AI models from being tampered with and allows unstable behavior to be returned to its source. It’s not about manually checking all AI actions. It’s about having the ability to do that. If everything is verifiable, nothing is hidden.
In a distributed system, multiple nodes can verify the actions of AI agents and discover anomalies such as bias, backdoors, or glitches through consensus, just as blockchains protect cryptocurrency networks. If AI works unpredictably, the node flags it and exchanges it, ensuring real-time corrections. This fusion of decentralized AI and blockchain creates a robust framework for trust, turning opaque “black box” models into transparent, verifiable systems.
Don’t forget governance
There is one more thing that blockchain works very well in the AI context. This is governance that we haven’t yet worked on. AI without proper governance risks committing fraud and makes untraceable decisions that are scrutinized. Blockchain counters this with an accountable, decentralized governance structure and is verifiable (again, that term).
Smart contracts can encode ethical standards and implement fairness and transparency in AI development. They can mandate unbiased training data or flag non-compliance, and stop the model deployment until it is corrected. Blockchain also empowers stakeholders, such as developers and users, to participate in governance and vote to shape AI rules. This collective surveillance curtails autonomous overcommittees and promotes accountability in cases of inadequate traditional systems.
Symbiotic relationship
Blockchain is the ideal technology to fix the most terrible flaws of AI, but it’s a relationship that works both ways. In turn, artificial intelligence makes the on-chain universe a safer, more efficient, and ultimately a more profitable place for work and play. But that’s another blog. The key here is that if AI makes the most of its potential, it not only benefits from blockchain, but it is necessary. Otherwise, all the problems bundled into AI (bias, backdoors, and opaque algorithms through which haywire moves) threaten to derail progress.
By recording the inner workings of AI in a constant ledger, blockchain addresses bias and manipulation head-on, and in high-stakes fields like aviation, it enhances safety and confidence. If AI is a watcher, then blockchain is the watcher when scanning databases to analyze systems. AI makes the world a better and more intelligent place. Additionally, actions and inputs are recorded in the blockchain’s immutable ledger, resulting in a more fair and open ledger.
read more: AI could break the code within 5 years | Opinion
Michael Heinrich
Michael Heinrich He is a graduate of Stanford University who previously worked as the founder and CEO of Garten. Michael, the top 100 entrepreneur of 2022, has published his work in a journal from Harvard Business Reviews to Hacking Awareness. While at Stanford, he was appointed to work with the Institute of Industrial Technology (ITRI) to transform Taiwan’s entrepreneurial education. His previous company, Garten, was accepted by Ycombinator in 2016, procuring multiple rounds and eventually gaining Unicorn status. Using 0G Lab, Michael leads the development of the first modular AI chain, supporting data verification for chain-off chains.
