Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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Will big data create a new untouchable business elite?

Jun 14, 2017 | 915 Views

Will the ascent of artificial intelligence (AI) and machine learning built by big data create an unstoppable inequality of innovation?

‚??Last week we interviewed veteran investor Bill Janeway, and it was fascinating.

Janeway described the way AI could allow an elite group of firms to innovate at speeds the rest of the world could only dream about. When I listened to his interview with Kenneth Cukier, it made me wonder whether economic ideas could be applied to the world of big data.

In the spring of 2014, all my friends were suddenly holding copies of the same book. "Capital in the Twenty-First Century" was 700 pages long, but the central idea was remarkably simple. The author, Thomas Piketty, claimed that if the value of assets, such as houses, farms and factories, grew faster than the overall economy, then the inequality of wealth between the haves and the have-nots would be exacerbated over time. If you were lucky enough to own property, you would be able to monetise it and make money faster than those who didn't. If you don't own assets, you have to earn your money and earning money usually takes a lot longer than collecting it. Every year the people who own assets increase their dividends faster than wages can catch up and that creates a systemic growth in the divide between the rich and the rest. But what if Big Data has the potential to do something very similar to the world of business by concentrating what is fast becoming the primary the source of innovation?

Now fast forward to May 2017 and The Economist's front cover hailing data as "The world's most valuable resource". If you haven't read our briefing on big data you really ought to.

Essentially, the briefing argues that data is the oil of the 21st century. Companies in Silicon Valley are harvesting data from all of us all the time by monitoring our interaction with our services. Those with the most data will have the advantage when it comes to innovation because they'll know the most about us. For instance, companies testing self-driving vehicles in Silicon Valley are currently collecting vast amounts of data on the way we drive so that they can develop the best AI. Once a clear leader emerges they will presumably be the first to roll out self-driving vehicles en masse. Once they do that, they will be able to monitor their own vehicles as they manoeuvre through our cities and once they have that it is hard to see how any competitor will be able to catch them because nobody else will know anywhere near as much about driving. Will any sector be immune from this trend? It seems likely that whoever gets their hands on the best data first will be able to innovate at an unprecedented speed, at the expense of their rivals. Here's how Janeway summarised it in a recent Medium post:

"The more data, the better the algorithms. And the better the algorithms, the better the quality of service offered by Amazon, Facebook or Google. This is the positive feedback law of machine learning. Previous sources of market power have been patents (Xerox), network externalities (IBM) and government regulations and franchises (AT&T). All of these still matter, of course, in the age of the internet. But machine learning as a source of competitive advantage adds another, technological driver whereby those whose offerings‚??-‚??for whatever initial reason‚??-‚??achieve market leadership are endowed with an amplifying ability continuously to improve their relative market position."

In our interview, Janeway cites an OECD study showing that the top 5% of global companies are already leaving their rivals in the dust. And yet, Janeway also thinks that the ability to hoover up so much big data could potentially be offset if the analytic capabilities of AI and machines learning were utilised across the economy. If everybody, in every business in every sector had access to the growing troves of big data, in the same way that every business in every sector once gained access to electricity, then the age of AI could instigate an explosion of innovation across the world. In "Capital in the Twenty-First Century", Piketty proposed a ‚??global wealth tax' to keep inequality in check. Perhaps big data requires a similar prescription. What do you think? Will advanced AI create a widening gulf between the elite firms who have it and rest of the world? Should big data, which is created by all of us, be in the public domain? And if so, how might we incentivise those who wish to collect it?

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Source: The Economist
Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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