Worried about your data? You should be — It’s just the beginning of the privacy war!
It’s 2019 and we are only just at the beginning of an era of the human war with privacy.
Over the past several years, the damage has already been inflicted with the processes that have enabled large amounts of data to be acquired and stored. According to IMC & EMC ,
“By 2020, the digital universe would include 44 zettabytes of information. That’s nearly as many bits as there are stars in the universe.”
However, it is in the not-so-distant future that will we see the real missiles of sensitive personal data surface, firing away erratically into the age of the internet, media, society and our lives. In the past decade, technological growth, has enabled the exponential acquisition of data. But only recently, we have made leaps in our ability to analyze, process, model and compare massive scales of information. As we advance towards commercializing this on-demand, let’s give a round of applause to Machine-Learning As-A-Service (MLaaS) as the next major shift in the technology industry that will leave no corner of data untouched…
Explosion of Data
In the past decade, there has been a magnificent explosion in the way individuals, societies, governments & enterprises have consumed technology. Day 1 came with the smartphone; we became a growing active real-time moving data point for consumption. The data points multiplied with new devices, better hardware, stronger social interactions, and a growing engagement ecosystem until eventually, our digital footprint today became a reflection of our lives.
Cloud computing has grown to a market cap of ~$200B, the social ecosystem has grown to a cap of ~$500B and 77% of enterprises use the cloud. Businesses are starting to embrace the concept of “data being the new oil” .
SaaS, PaaS, and IaaS have enabled effortless, easy integration of technology across individuals and organizations in this world. And at this point, we have successfully built and maintained a self-sufficient ecosystem that constantly, hoards data from our lives (Typically, with our consent!). By 2020 experts estimate a 4300 % increase in annual data generation. Furthermore, we are also driving collaborations among the data hoarders (Open Data Initiative). However, until not too long ago, the majority of this data was useless.
Machine Learning As a Service (MLaaS)
But now, with the maturity of products that enable MLaaS such as Amazon SageMaker, Azure ML Studio, Google Cloud ML opened the doors for truly understanding the nature of our data. It also opens the door for intelligent application in the understanding of the patterns of our data for every company that is connected to the general cloud ecosystem.
According to the Market Research Future , MLaaS is expected to grow to $4630 Million by 2022, at ~40% of CAGR between 2016 and 2022.
Privacy & Risk of Data Breach
This exponential growth exposes the vulnerabilities at a pace company’s are not statistically experienced to handle. The size and impact of data breaches have severely increased. And as the quality, interactions, and richness of data increases the individual cost of data breaches are going to become much more severe. We are possibly only a bad nail away from leaking highly contextual, intelligible personal information at the hands of thousands of sources without any globally effective or enforced regulation to protect the rights of the management and utility of our data. The majority of breaches we have seen so far have been tied to raw information affecting only a part of our lives. The data leaks we are going to see this year and going forward are going to expose much more to the world, connecting the greater entirety of our lives. Our personal information will speak of our past, our financial data will speak about our money habits, our social data will speak about our character, our DNA will define our personalities. Every interaction we have today and every data point we create or have created will become a part of these systems. It will have total power over defining our identities. And when we expose a mature system capable of generating such invaluable insights as a service, we risk finally opening a can of worms. Imagine every institution you interact with every day having the power that Google or Facebook has today on your data. Machine Learning had been a niche area controlled by experts just like software, infrastructure and platforms were before the SaaS, IaaS & PaaS revolution of Cloud Computing.
Conclusion
In summary, the wide-scale adoption of MLaaS will be inevitable, carrying with it, the moral responsibility data which we have not been equipped to handle. We have been integral to the process of generating data and by now we may have already given too much. The high growth, of data acquisition, data storage, and data interactions, in combination with the lack of enforced global regulation and upwards trend in data breaches, will amplify the risk associated with companies using MLaaS. As we speak, we are already enslaved into the future of our own doing and only a blink away from another bigger privacy incident.
