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Humans and data:
where will they go next?

In a moment where investors have just begun to scratch the surface of big data and machine learning, the new and upcoming opportunities that can come from data science and its tools appear to be endless.

Looking at the research in the field of machine learning and artificial intelligence, experts say the complexity of data analysis and the diversity of the data itself are only set to increase over the next decades.

Logan Graham, a PhD student at the Machine Learning Research Group at the University of Oxford believes all the activities humans are doing now will be partially automated. He also thinks many of the current models used to analyse data will become more complex, eventually generating data themselves.

He says: “Even if we have just as much data, it will probably be a hundred times as diverse as the data that we’re using today, with models dispersed a hundred times more than they are, working on ten times as many problems as well.”

The developments in big data and its models will also touch on the way people communicate with each other. Ben Hookway, CEO of Relative Insight, a company that extracts data by analysing different types of languages, says that languages are often underestimated as a data asset.

“Even if we have just as much data, it will probably be a hundred times as diverse as the data that we’re using today, with models dispersed a hundred times more than they are, working on ten times as many problems as well.”

Logan Graham

PhD student at the Machine Learning Research Group at the University of Oxford

He adds: “We’re certainly going to see that how you communicate is as important as who you try and communicate with and we’re all about optimising that layer. Language, in particular, is relatively untouched as a data asset, but I think that is the case for most emerging technologies, people tend to overestimate the short-term impact and massively underestimate the long-term and that’s basically a truism for almost every new tech and I don’t see this being any different.”


The big scandals surrounding fake news and data breaches might not push people toward trusting the power of big data in the future. This is why many are calling for regulators and governments to step up and take more control over the way data is generated and used. Some new rules, like the recent GDPR regulation in Europe, have already been put in place to guarantee a higher degree of data protection.

Hookway says it is important to look at the way governments and policies are going to keep up with the speed of data in the medium term to make sure people feel more confident. He notes: “It’s rarely the long-term vision [on the future of big data] that’s hard, it’s the building blocks to it.” 

Petronella West, CEO at Investment Quorum, also stresses the importance of data security and the necessity for consumers to understand data in order to feel more secure. She says: “There’s a perception of not understanding big data. For example we got hit with a crypto virus recently and it makes you think how safe is your data? How safe is the information that I’m storing about clients?

As big data analytics have proven to be a powerful way to detect and combat the rising threat of cyber-attacks more organisations are now embracing it in their businesses. 


West hopes that future improvements in technology will lead to a better connectivity between the different parts of the investment value chain. Importantly, the advancement of technology should help drive costs down for both clients and businesses, she says.

“Price is key because I think we’re going to live in a world of lower returns, but there are just going to be more efficient ways to do things. However, I still think that the relationship that we have as client to adviser, that DNA, is still a key aspect of what we do day-to-day. But, can we do it better?,” asks West.

Meanwhile, as investors learn how data and the methods of extracting information continue to evolve to produce alpha, fund managers say it is important that the whole asset management industry embraces what data and machine learning can offer in the future. 

Simon Weinberger, managing director and portfolio manager at BlackRock says: “If I take an industry view, I think the general adoption of more data and some of these new things will accelerate. Now there’s still a lot of sceptics and I’m not claiming that the way we do things is the only way to incorporate data in the process, but I think every single one will need to figure out a way to leverage the opportunities that come with new data and machine learning. 

“That can still be the case in a concentrated portfolio, but you’ve got to go beyond looking the CEO in the eye and making a punt on whether this is going to be a good investment or not.”


[2] IDC

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