It’s no secret that big data analytics is taking the business world by storm, imparting a whole new world of corporate intelligence value. What is not so clear is how businesses seek to deal with the copious quantities of data that will be generated by big data applications. Blockchain poses a possible solution as it represent an immutable, consensus driven, self-verified platform for transactions. Clear audit trails and transparency regarding data origin all contributes to an effective framework for dealing with the complexities of big data.
Besides improved data integrity, blockchain technology introduces a shared data layer that opens up greater possibilities of artificial intelligence and understanding of the scale of this technology and its AI applications.
The benefits of blockchain for AI practitioners
Blockchain provides a decentralized database for data, which is not controlled by any one entity, thus encouraging data sharing. For AI and big data applications, the more data available through open blockchains results in more accurate models and more precise predictive power of analytics. Qualitatively, new data leads to the emergence of new models. Furthermore, blockchain technology allows for shared control of AI training data and models.
The immutability of the data is key to the precision of big data analytical models. Accurate provenance of data improves the trustworthiness of the data and models, making the whole process transparent and easily audited.
Blockchain extends the ability to turn insights into assets as a consequence of training and testing data. This leads to decentralized data and model exchanges allowing superior control of upstream usage of data.
Lastly, AI applications leveraging blockchain technology yield the potential for AI decentralised autonomous organizations (DAO) which are essentially self-running and self-improving businesses that run independently. These run on a decentralized processing and storage framework and the ingrained feedback loop takes inputs into consideration, effectively updating and reallocating resources and actuating outputs accordingly.
An offshoot benefit of using blockchain technology to run big data analytics is the cost implications of data storage. Big data storage has traditionally been a limiting factor for many businesses as the cost of centralized storage providers exceeded budgets. This will create pressures on current SaaS providers as they too will need to move to decentralized storage to deal with the volumes of big data. Decentralized storage enterprises are likely to experience some initial bargaining power in the wake of the increasing popularity of blockchain technology and the estimated savings compared to AWS, for example, which is predicted to be close on 90 percent.
How exactly is blockchain going to change AI as we know it?
It is anticipated that the rollout of blockchain driven AI will occur in three phases. Firstly, blockchain will be used within the present enterprise, such as running news aggregation like New Break and similar services. Then it will be used within the immediate ecosystem of interconnected nodes and then finally by opening up the technology completely.
The expansion of big data from isolated data silos to blockchain shared data layers will shift the power from proprietary to those who can access the data and gain insights the most swiftly. The implications are existential and customer data will no longer remain property of the company stored in databases, but rather the ownership shifts to the individual and will be represented by tokens in an identity blockchain. The onus is on the customer to grant accessibility to stakeholders.
The reasoning behind this is a shift in competitive edge. Owning the data becomes moot, and the analysis and interpretation of the data becomes important. Moving data onto public blockchains essentially levels the playing field and the onus is on the organization to extrapolate and interface that data with competitive applications. A blockchain is fundamentally a distributed database that cannot be modified and there is a strict protocol for how entries are made. In this, an opportunity exists. Dubbed data industrialization, it is essentially throwing down the gauntlet to organizations to develop the best AI, machine learning and big data analytical models for open blockchain data layers. Therein lies the competitive advantage and will drive innovation and technological advancement.
Blockchain may indeed be exactly what big data analytics needs to scale the ecosystems appropriately. This technology will undeniably help AI realise its potential and open up development opportunities that have previously only been available to proprietors of data.
