Decentralized AI: The Key to Unleashing the Full Potential of Artificial Intelligence

The Artificially powered world as we know it

Artificial Intelligence has firmly established itself as a cornerstone of modern technology, with ChatGPT reaching 13 million unique visitors daily, influencing everything from daily conveniences to complex business processes. It’s not just ChatGPT though, AI is powering industries from logistics to healthcare. It’s becoming more ever present in our lives, most of the time without us being acutely aware.

However, as we delve into 2024, AI faces a number of challenges that threaten to impede its progress and potential. Privacy concerns, a growing trust deficit, and ethical dilemmas are just the tip of the iceberg.

These issues highlight a critical flaw in the current landscape — the centralization of data and decision-making power, which often leads to biases, security vulnerabilities, and a lack of transparency.

Decentralised AI: An Overview

A shift from centralised systems to a distributed framework is pertinent.

We must move away from the traditional model where data and decision-making are dictated by the few; where big tech companies dominate over the common man. A move towards a more democratic structure is required.

Centralisation is an outdated and antiquated model, and an outdated mindset. Unbounded centralisation lacks the guardrails that we, as a populace, require to keep AI safe. A democratised and decentralised future must now be embraced.

If these concerns are left unresolved we could see a heavy hand from regulatory bodies, hindering the advancements for humanity that AI has proved it has to offer. Web3 has the potential to mitigate these issues before we reach the stage of heavy regulation that is coming as the powers that be catch up.

In a decentralised model, the computational power and data storage of AI are spread across a network, reducing central points of failure and bias. It’s clear that this isn’t just about dispersing data; it’s about embedding AI processes within a framework that inherently values transparency, security, and collective intelligence.

By leveraging a decentralised network, AI’s decision-making becomes a reflection of diverse inputs and collaborative data analysis, paving the way for a more ethical and balanced AI landscape.

One of the most high profile examples that decentralised AI hopes to alleviate is the ethical use of training data. OpenAI, known for its advanced language models, recently faced potential legal action from The New York Times over the use of its content without explicit permission. In a decentralised system data sets like this could be tokenized and receive revenue shares for their usage, in the same manner that we’ve seen done in other industries such as digital art.‍

The Challenges DeAi Faces

Shifting to a decentralised AI future brings its own set of challenges. One major hurdle is blending blockchain technology with AI systems. This is crucial for decentralisation but requires a lot of compute power and needs to work efficiently with the massive amounts of data that AI processes.

Another big challenge is keeping data consistent and high-quality across a decentralised network. Unlike centralised systems where it’s easier to manage data standards, in a decentralised setup, it is essential to ensure that a variety of data is reliable and uniform within its structure, so that AI can learn and make decisions correctly.

Other obstacles include motivating people to participate in decentralised AI networks and dealing with legal and ethical issues. For decentralised AI to work well, it needs active input from many people, which means finding ways to encourage data sharing and teamwork. This might involve creating reward systems for contributors or a DAO system for governance.

The Trailblazers of Decentralised AI

Ocean Protocol are aiming to advance the decentralised data economy by enabling secure and transparent data sharing and monetization. Offering a platform where individuals and organisations can exchange data with trust and efficiency. The $OCEAN token facilitates data asset curation and acts as a medium of exchange, incentivizing and rewarding data sharing.

SingularityNET is a decentralised marketplace for AI algorithms. It allows anyone to create, share, and monetize AI services at scale, making AI and machine learning models more accessible to the general public.

Fetch.ai is a blockchain project that integrates AI with Web3 technology. It augments existing systems with AI without changing their existing APIs, allowing businesses to level up their systems and infrastructure without rebuilding them from the ground up with AI in mind.‍

Embracing a New Era of AI

In conclusion, as we progress into 2024, the shift towards decentralised AI is not just a technological necessity but a step towards a more ethical and equitable future in artificial intelligence.

The challenges we face with centralised AI — from privacy concerns to ethical dilemmas — highlight the urgent need for a more distributed, transparent, and collaborative approach. Decentralised AI, with its inherent focus on security, diversity, and collective intelligence, offers a promising solution to these issues.

The question now is, how will we, as a society, as industries, and as individuals, contribute to and shape this new era of AI? The future of AI is not just in the hands of developers and the MAG 7’s of the world; it’s in all of our hands. It’s time to think about how we can actively participate in and benefit from a decentralised, democratised AI world.

This blog was originally posted on Bionicdao.com. For more insights into the world of DeSci, Extended Reality, Artificial intelligence or Web3 Infrastructure, visit our website & sign up to our newsletter!