What Big Data experts thought the world would look like in 2020

In the past, the year 2020 has been presented as the point in time when many technological innovations would come to fruition. For instance, it was the year when we would have self-driving cars routinely roaming down our roads and streets; and, even, flying cars. It was also the year when we would have conscious AI, able to control devices with thought. Or, when we would be hopping on a commercial flight to the moon.

 

Sometimes, I wish that I could go back in time, and listen to people projecting the future of technology. See why they thought that we would have reached a particular technological milestone by now. Alas, as it is not yet possible to travel back in time, I found the next big thing: a report from the Pew Research Center looking at the role of Big Data in 2020.

 

Back in 2011, the Pew Research Center surveyed more than one thousand experts on digital technology to gather their views on the future of the Internet. One of the questions asked participants to reflect on the likely influence of Big Data in the year 2020, and I thought that it would be interesting to revisit their predictions, and their rationale.

Pew

The report can be found here. But, before we look at the predictions, and the reasons for them, a quick note on how the study was conducted.

 

The approach

The vast majority of the participants were based in the US, which is likely to have had a significant effect on their perspective on this issue and, thus, the responses.

 

Their professional affiliations were as thus:

  • 40% were academics
  • 12% worked for an IT company
  • 11% for a non-profit organization
  • 10% said that they worked at a company that used information technology extensively
  • 8% were business consultants
  • 5% worked for a government agency
  • 2% in media
  • The occupation of the remaining 12% is not detailed.

 

There is no information regarding the gender or the age split of the sample.

 

The participants were presented with two alternative scenarios for the state of Big Data in 2020. They had to choose the scenario that they believed was most likely to occur, and then elaborate on the following:

What impact will Big Data have in 2020? What are the positives, negatives, and shades of grey in the likely future you anticipate? How will use of Big Data change analysis of the world, change the way business decisions are made, change the way that people are understood?

 

The scenarios

The researchers developed two scenarios that directed the participants to consider specific uses of Big Data, and specific consequences that might arise from those uses, leading to two opposing outcomes for society.

 

One scenario depicted a future where Big Data had given rise to very positive outcomes for society:

Thanks to many changes, including the building of “the Internet of Things,” human and machine analysis of large data sets will improve social, political, and economic intelligence by 2020. The rise of what is known as “Big Data” will facilitate things like “nowcasting” (real-time “forecasting” of events); the development of “inferential software” that assesses data patterns to project outcomes; and the creation of algorithms for advanced correlations that enable new understanding of the world. Overall, the rise of Big Data is a huge positive for society in nearly all respects.

 

The second description depicted very negative outcomes for society:

Thanks to many changes, including the building of “the Internet of Things,” human and machine analysis of Big Data will cause more problems than it solves by 2020. The existence of huge data sets for analysis will engender false confidence in our predictive powers and will lead many to make significant and hurtful mistakes. Moreover, analysis of Big Data will be misused by powerful people and institutions with selfish agendas who manipulate findings to make the case for what they want. And the advent of Big Data has a harmful impact because it serves the majority (at times inaccurately) while diminishing the minority and ignoring important outliers. Overall, the rise of Big Data is a big negative for society in nearly all respects.

 

The results

The participants were split in their view of the impact that Big Data would have on society by 2020: 53% chose the positive scenario, while 39% chose the negative one. The remaining 8% did not choose any scenario. In other words, from those research participants that picked a scenario

  • 58% supported the prediction that, in 2020, “the rise of Big Data” would be “a huge positive for society in nearly all respects”
  • 42% predicted that, in 2020, “the rise of Big Data” would be “a big negative for society in nearly all respects”.

pseudo-ai-640x360

 

What led the participants to predict such diametrically different outcomes?

To get a glimpse into their minds, we can look at how the participants answered the follow-up question:

What impact will Big Data have in 2020? What are the positives, negatives, and shades of grey in the likely future you anticipate? How will use of Big Data change analysis of the world, change the way business decisions are made, change the way that people are understood?

 

Those that had predicted mostly negative outcomes from Big Data noted that, to fully take advantage of Big Data, we need both strong analytical skills and technological capacity. Therefore, the benefits of Big Data would mostly be accessible to those with the resources and the power to do so, meaning that “The rich will profit from Big Data and the poor will not.”

 

Furthermore, they noted that people would use Big Data to support their agendas. Given that governments and big corporations were the ones with the most data, as well as the biggest incentive to analyse them, these experts predicted that the exploitation of Big Data would be informed by the drive to scrutinise and influence users.

 

They also predicted that Big Data would be manipulated to lend support to lies. So, it was imperative to educate the public about these risks. Finally, they hoped that trust features could be built in Big Data solutions.

 

Those that had predicted mostly positive outcomes agreed that strong analytical skills and advanced technological solutions were needed in order to fully benefit from Big Data; and they felt that “humans just won’t be able to keep up”. They also shared the view that data and statistics could be used to lie, and that it was necessary to develop tools to provide “checks and balances”.

 

However, unlike the other group (that had predicted that Big Data would mostly be used to advance the surveillance and influence agendas of governments and big corporations), they predicted that Big Data would be used mostly to “improve our understanding of ourselves and the world”. The merger of pattern recognition tools, on the one hand, and real-time data analysis capabilities, on the other, would enable “Nowcasting” (a term borrowed from meteorology to describe the ability to predict the very short term). They referred to Google Flu Trends, a Google initiative that claimed to be able to identify flu trends and predict outbreaks, by monitoring people’s online searches and conversations… but which was abandoned in 2013, after it failed to predict a major flu outbreak (this article does a great job at unpacking why that was the case).

flu

These experts also foresaw a future where innovation would be democratised, via “do-it-yourself analytics” and access to open tools.

 

So, who was right? And why?

I think that the very early days of Big Data supported the positive view. There were several examples of apps being developed to solve common problems (e.g., through citizen science) and improve daily lives (e.g., monitoring traffic and generating alerts).

 

However, the subsequent period proved the negative view right. We saw the proliferation of free apps that pursue very aggressive data collection (e.g., Cambridge Analytica). We have also seen the use of social engineering techniques, by free online services, to keep us hooked on those platforms, with complete disregard for the individual’s or society’s well-being (e.g., YouTube’s algorithms which serve us increasingly extreme content). And there are the numerous examples of data being used selectively to propagate lies and misinformation, including the manipulation of elections.

 

What do you say?

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