One of the biggest emerging tech trends in the past three years is the rise of artificial intelligence as a truly feasible technology. As computer processing and hardware improves, AI tools are more commonly appearing in many services we use daily, spurred in part by blockchain.
AI is becoming a central concern for businesses, with adoption rates soaring throughout multiple industries as perceptions rapidly shift positive. With this greater exposure also come questions about decentralization, accessibility, and data quality and sources.
The first is a problem of who controls data and for what purposes. Privacy and control of data has become a significant issue, and AI, which can learn users’ preferences to provide better services, remains a controversial topic. Decentralization poses an interesting solution that increases transparency. Accessibility is tied to decentralization and is vital towards promoting a stronger future for AI. The last question—data quality—is crucial for helping AI deliver useful solutions and continue learning.
Blockchain, originally created as the backbone for bitcoin, has emerged from the cryptocurrency’s shadow to become a platform on its own. With advantages that include data transparency and a fully decentralized infrastructure, the technology could be exactly what AI needs to take its next big step.
1. Decentralization Optimizes AI’s Data Streams
One of blockchain’s most touted benefits is its power to decentralize data and create more efficient distributed networks. By using fully decentralized network architecture, data can be distributed more efficiently to every node and allows for greater transparency, faster data communication, and higher reliability in terms of the data being stored.
This has a real impact on data storage, as it removes bottlenecks created by centralized databases and improves communication speeds by converting to a peer-to-peer model. Data is better distributed to every node in the network, information is verified more accurately and quickly, and provides greater confidence in the data’s reliability.
When it comes to AI, these qualities are vital as machine learning requires using valuable data to continue developing better habits. Offering access to broader datasets also means AI systems can make better decisions and provide greater value. Additionally, blockchain’s decentralization can generate more trust in AI systems, which can operate with higher quality data and thus deliver better results.
Furthermore, blockchain’s distributed ledger means there is no fear that a single organization or actor will tamper with data to manipulate results.
2. Accessibility Leads To Better Systems
Another major concern for AI as a technology is who has the keys to the system. Currently, AI remains firmly in the domain of enterprises and others with access to better technology and finances. However, blockchain has been greatly lauded for its ability to extend access to underserved populations.
Indeed, cryptocurrencies are being used to pay lower income workers in developing countries without access to banking services and other financial institutions. Combining blockchain and AI systems would create a more global community that could contribute to its development.
More importantly, it opens the door for greater innovation, disruption, and participation. There are already tools that employ blockchain data in conjunction with natural language processing and other software to create more accessible searches for users, with some companies already creating the backbones of these systems. Moreover, blockchain offers an easy solution for resource-intensive AI tools by creating a network of pooled bandwidth, storage space, and even processing power.
3. Data Quality
Finally, but no less important, is the question of data quality. AI depends on substantial amounts of data to continuously learn and provide more reliable answers. The more information an AI system has at its disposal, the better it can function and make real-world decisions. However, centralized networks and paradigms create friction in data transmission by adding unnecessary intermediaries.
Without a fast way to verify data and communicate it across a network, or even to store multiple data streams simultaneously, AI systems can quickly face insufficient data and bottlenecks that can impact their usefulness. Blockchain can offer solutions in terms of both data quality and ease of transmission.
Thanks to its immutable ledger, all transaction data stored on blockchain is both completely tamper-proof and verified almost instantly thanks to its consensus-building mechanisms. The result for AI is that data arrives to it faster and with higher reliability when compared against traditional networks.
Improving data quality also means using only that data which is necessary. Today, AI is used by companies like Facebook and Google to trawl through petabytes of user data. Unlike these centralized behemoths, blockchain offers a significant privacy upgrade, and means that users can share specific data without worrying about their private information being used against them for any purpose. This also results in a changing balance of power that benefits users over corporations, as they can retain ownership of the data they want.
AI is taking the world by storm, but to be truly disruptive, it needs to shed the vestiges of antiquated paradigms. By embracing blockchain, we can create better and more reliable AI tools that are widely available and above all, inclusive.