Big data metaphors are overused clichés of the 21st century. Big data is either new gold, new oil or some valuable asset which is limited to the tangible nature of the metaphors and the industry seeking to define it. However, do you always receive tangible value from the data left behind for companies based on your active or passive digital footprint?
By 2025, the average data consumer will have at least one digital data engagement every 18 seconds, which translates into almost 4,900 interactions per day. In the course of these interactions, the data consumer also grants additional ‘free’ access to their digital footprint, which is further analyzed, by companies, to supply the consumer with personalized experiences.
It is therefore, crucial for the consumer to understand and reap the full value of their contribution. There are two ways of gaining value from big data—non-financial incentives, and financial incentives. The latter is almost untapped in India.
Big data analyses correlations which means that it mostly delves into ‘what’ rather than ‘why’. For instance, can your clothes monitor your health? Yes. Could this data on health thereafter be used by insurance companies to provide better policies? Maybe.
These secondary uses and correlations are the valuable non-financial incentives offered. Additionally, these correlations and secondary uses are the long-term impacts of big data use, which may or may not be determinable ahead of time. This is evidenced in the draft Personal Data Protection Bill, 2018 which does not aid in digital transformation in a big data world. One example is the requirement of ‘purpose specification’ while collecting data, which nullifies the impact of secondary uses and correlations between data points. The primary concern is that the requirements and liabilities of big data varies from the concerns surrounding personal data.
According to a Cisco report, Internet of Things (IoT) connections will represent more than half (14.6 billion) of all global connected devices (28.5 billion) by 2022. This increase in connected devices is directly proportional to the increase in data collected and analysed by companies. An increase in volume of big data fuels technological innovations for various purposes including healthcare and education.
For example, YouCode Intelligence Solutions—the brainchild of Suriya Prabha K.—creates consumable interactive Artificial Intelligence (AI) content for educating children in rural India. Her focus is to convert the complexity of the technology into an opportunity to solve the technology skill gap through an ‘AI4Kids’ campaign. “Our AI learning system works on reinforced learning, so we collect the responses from kids, which is further used for enhancing the deep learning model” says Suriya.
Startups like YouCode aim to make a difference by freely utilising accessible data which could spiral the growth of AI, with a keen eye on securing privacy by-design. Also, improved algorithmic predictions and trend spotting only occurs with large data sets. Therefore, ideally access to big data should be expanded across sectors on a worldwide basis and not be polarised or restricted with few companies.
Data exchanges, and getting your cut
Don Gossen, Co-Founder of Ocean Protocol—a decentralized data exchange protocol, agrees that “Because data is consolidated and largely locked up within large enterprises, startups struggle to access the data they need to flourish.”
“Ocean Protocol aims at changing the paradigm by giving access to more data to all, especially AI and machine learning startups; thus creating a more equitable ecosystem to sustain the new data economy.”
Ocean is currently working with Next Billion in rural India to create a data sharing model to increase sustainable livelihoods for local stakeholders.
“At present, several aspects in the Indian regulatory system hinder the process of digitalisation through data exchanges.”
Data exchanges—with traditional or non-traditional financial incentives as confirmed by the Government of India, will assist in identifying larger correlations between data points and permit data sharing across the IoT between various stakeholders worldwide.
Ocean Protocol, is a Singapore based non-profit foundation, which unlocks data for AI by connecting providers and consumers of valuable data, while providing open access for developers to build services. “Ocean Tokens will function as utility tokens, acting as a proxy for the underlying assets like data, that can be exchanged only within the Ocean ecosystem.” says Gossen.
However, at present several aspects in the Indian regulatory system hinder the process of digitalisation through data exchanges.
For instance, it would be difficult for data exchanges which connect with several marketplaces for ’… proactively identifying and removing or disabling public access to unlawful information or content”, as required under the draft Information Technology (Intermediary Guidelines) Rules, 2018.
In traditional data exchanges enabling tracing of the originator of information, in a borderless data ecosystem, may be difficult due to the fluid nature and malleability of big data. However, as confirmed by Gossen, Ocean tackles this issue by focussing on provenance and attribution, thereby coupling accountability to traceability. “By recording transactional information on a blockchain, Ocean can create an immutable ‘virtual paper trail’” says Gossen.
New technologies and the growing applications of big data can be effectively managed through cross-sectoral coordination between technologists, policy makers and the Government. In the meantime, subjecting data exchanges to the same guidelines without a variation, is problematic. Additionally, the draft guidelines also require monthly compliance notifications to be sent out by the intermediary to the data user. With the inversely proportional speed of technological innovations vis-à-vis judicial actions, it would be prudent to lay down the requirements and regulations for ‘proactive’ actions of data intermediaries in India.
This does not mean that concerns over privacy and accountability are ill-founded. It simply requires the big data infrastructure to be revamped with a focus on improved regulatory and legislative measures. Knowledge on the growing value of big data and the incentives to be gained from it, will over time assist in creation of guidelines to regulate the use, analysis and reliance on big data.