SINGAPORE - Source data has been expanding exponentially in recent years, and this pace is being increased by a new perspective of the convergence between the physical and virtual worlds. In this scenario, paradigms such as artificial intelligence (AI), augmented reality, digital cryptocurrencies, next-generation technologies, and virtual reality, all have a major impact on this rise in source data. Understanding the social determinants of health data further accelerates the expansion of source data. AI methods represent a rapid advancement in field technology and have the potential to significantly improve human well-being.

All existing AI systems share a common characteristic: they are all vertically structured, using algorithms of varying complexity around functions with centralized human control. As humans reach their limits in the deep analysis of large amounts of unstructured data available on online platforms, the algorithms created are divergent enough to make progress in the field of AI.

In today's world, known as Web 2.0 designed in a centralized mode, many online services are used on the Internet, and these services monetize a huge amount of data due to the interaction between the customer and the service. For this reason, the data shared with the online platform has no market value from the customer's perspective - otherwise, an online platform has extreme value for this data. This scenario is not improved by AI technology, and the goal is to use the decentralized autonomous organization methods know as Web 3.0 using secured multi-party computations, decentralized finance, homomorphic encryption – “a special type of encryption technique that allows for computations to be done on encrypted data, without requiring access to a secret (decryption) key. The results of the computations are encrypted, and can be revealed only by the owner of the secret key,” according to Microsof