Dataism is a term that has been used to describe the mindset or philosophy created by the emerging significance of Big data. It was first used by an American political and cultural commentator David Brooks in the New York Times in 2013
In his latest best-seller, Homo Deus: A Brief History of Tomorrow, noted Israeli historian and author Yuval Noah Harari redefined the term ‘Dataism’, arguing that all competing political or social structures can be seen as data processing systems: “Dataism declares that the universe consists of data flows, and the value of any phenomenon or entity is determined by its contribution to data processing” and “we may interpret the entire human species as a single data processing system, with individual humans serving as its chips.”
According to Harari, a Dataist should want to “maximise dataflow by connecting to more and more media”. Harari predicts that the logical conclusion of this process is that eventually, humans will give algorithms the authority to make the most important decisions in their lives, such as who to marry and which career to pursue.
What is Big Data?
Big data is a term applied to data sets whose size or type is beyond the ability of traditional relational databases to capture, manage and process the data with low latency. Big data has one or more of the following characteristics: high volume, high velocity or high variety. Artificial intelligence (AI), mobile, social and the Internet of Things (IoT) are driving data complexity through new forms and sources of data. For example, big data comes from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media — much of it generated in real time and at a very large scale.
What is Big Data Analytics?
Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes.
Analysis of big data allows analysts, researchers and business users to make better and faster decisions using data that was previously inaccessible or unusable. Businesses can use advanced analytics techniques such as text analytics, machine learning, predictive analytics, data mining, statistics and natural language processing to gain new insights from previously untapped data sources independently or together with existing enterprise data.
Source: IBM
Dataism: A New Religion?
In a review of ‘Homo Deus: A Brief History of Tomorrow’, David Runcimanan, an English academic who teaches politics and history at Cambridge University, observes that Dataism, a new religion, will replace liberalism, democracy and personal autonomy in the coming age and the individual will disintegrate from within:
“In place of the founding tenets of modernity – liberalism, democracy and personal autonomy – there is a new religion: Dataism. Its followers – many of whom reside in the Bay Area of California – put their faith in information by encouraging us to see it as the only true source of value. We are what we contribute to data processing. There is potentially a huge upside to this: it means we will face fewer and fewer obstacles to getting what we want, because the information needed to supply us will be instantly accessible. Our likes and our experiences will merge. Our lifespans could also be hugely extended: Dataists believe that immortality is the next frontier to be crossed. But the downside is obvious, too. Who will “we” be any more? Nothing more than an accumulation of information points. Twentieth-century political dystopias sought to stamp on individuals with the power of the state. That won’t be necessary in the coming century. As Harari says: “The individual will not be crushed by Big Brother; it will disintegrate from within.”
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