Can Blockchain and AI Become Brothers-in-Arms?

With the dramatic fall in popularity of cryptocurrencies and the wave of unpredictable volatility in the value of these immaterial currencies, comes a seeming drop in the interest in blockchain. Yet, the development of this technology and its application are still charging ahead in full force and its full potential is yet to be seen, understood and implemented.

“We have been entertaining ourselves mainly with dress rehearsals so far but much more lies ahead of us.”

At the same time, the general public and media appear to have shown a much greater fanfare for artificial intelligence (AI). This is not surprising as this technology is advancing at breakneck speed. It is therefore only a matter of time before these two technologies join up. Or at least this is a scenario we tend to believe plausible, out of the many speculations.

Blockchain can be described as a foundational technology, which operates as an infrastructure on which a time-stamped series of immutable record data managed by a cluster of computers that are secured and linked to each other using cryptographic principles. As a result of this setup, the data that is stored on the blocks act as a single trustworthy source of information to be shared by different parties simultaneously. It is equally associated with a modern form of storage of value, this being interpreted in its most multilateral definition.

On the other hand, the rapid advancements of AI have led to the possibility of using machines to take on a widening range of human tasks. Yet, one of the biggest challenges and constraints to the developments of AI is the quality of data – it requires data to be as complete and comprehensive as possible to train new models and for existing models to perform well.


The benefits AI and blockchain can jointly bring

As blockchain can act as an unprecedented trustworthy information source, it is possible to feed AI with validated and authenticated data. This would prevent the “garbage in, garbage out” nature of some machine learning models, thereby enabling the machines to be much better at decision-making. This may sound mundane, but it is an important consideration. In the years to come, the number of alleged biased AI systems and algorithms may increase as a result of the inferior quality and lack of comprehensiveness of data. This is a quite grave problem, probably more significant than what one may think, as poor data choice has shown to lead AI models to display manifested bias of all kinds, if not downright discriminations, ranging from gender to racial and cultural. In addition, blockchain can also be used to monitor and record any abnormalities in data that could result from bias, which in turn, would enable machine learning algorithms to evolve in efficacy and to minimize the chance for specific bias to show up again in future AI models – and the feed into AI systems. It would act somehow as a guarantor of the quality of the data used for machine learning and a safeguard for the infiltration of poor or bad data into the algorithm.

Another benefit is data privacy. Very often, data contains sensitive and personal data which is susceptible to data breach and/or identity theft. EU has already implemented general data protection regulation (GDPR) in order to protect personal data. Blockchain can be used to protect identities from theft, handle the issues of authentication and create encrypted digital identities. As such, blockchain becomes a perfect gateway that leads to secure data transfer over the internet, although the reality of what we describe, still lies in potential terms rather than actual.

Examples from the healthcare sector

All things considered, there are areas where a combination of Blockchain and AI could demonstrate their synergy. For example, in the healthcare sector we could utilize all the benefits from blockchain technology in terms of providing validated, secured and GDPR aligned data in order to enhance cancer diagnosis. By cross-examining the private data collected, processed and validated through blockchain, AI would be much more able to identify early signs of cancer in patients. Better yet, the benefits are also reciprocated, AI can assist blockchain in smart contract testing by providing for example, automated troubleshooting or debugging and root cause analysis and identification. Imagine the foreseeable benefits of medical information that do not get compromised by bad storage or loss of storage and allows for even more meaningful iteration to occur, improving the efficacy of the code used to run the algorithm.

Another possible use of the combination is clinical trials. For instance, they can be used to directly increase the quantity and quality of patients recruited for clinical trials. With the use of natural language processing, patient data on paper can be converted into structured digital files with greater accuracy and speed, all at lower cost than what humans can do. Using blockchain, on the other hand, individual patients can store and control access to their medical data, and make it visible to trial recruiters, who could then reach out to the patients if their data qualifies for the clinical trial. The decentralized nature of blockchain gives the patients control over their data, and consent and its revocation. Blockchain can also be used to handle trialed results properly while AI can produce better insights into certain clinical matters than the conventional human-based process.

Even though the developments of both blockchain and AI are still in their infancy, their respective potential is enormous. The combined use of these two general purpose technologies will most definitely open-up a great deal more opportunities and possibilities and in all likelihood, more jobs. It is only a matter of time before they start to join forces and ultimately become the brothers-in-arms, serving as the basis of the technologies that are an integral part of daily lives, purported to serve us better and to place human-centric values back to where they belong.

This article is also featured on frog, and is written by Mark Esposito, and Terence Tse.

Mark Esposito

Professor of business and economics at Hult International Business School and at Thunderbird Global School of Management at Arizona State University; a faculty member at Harvard University since 2011; a socio-economic strategist researching the Fourth Industrial Revolution and global shifts.

Terence Tse

Professor at ESCP Business School and a co-founder and executive director of Nexus FrontierTech, an AI company. He has worked with more than thirty corporate clients and intergovernmental organisations in advisory and training capacities.

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