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The PEW Internet & American Life project is part of PEW Research who call themselves “a nonpartisan, nonprofit “fact tank” that provides information on the issues, attitudes and trends shaping America and the world”. PEW publishes all kinds of analyses of internet usage, demographics and effects on society. A visit to their website (pewresearch.org) for example will lead to the current state of news organizations, how people have watched the Olympics and what is happening in the race for the American presidential elections.
Recently, PEW Internet published a report that collects a wide overview of opinions about the future of Big Data, and it gives a nicely balanced view of the topic. Looking forward to the year 2020, the main conclusion of the report is this:
Experts say new forms of information analysis will help people be more nimble and adaptive, but worry over humans’ capacity to understand and use these new tools well.
The report is well worth the read, as it touches not only the positive sides, but also tries to pinpoint potential downsides to big data. And there are many listed, from questions about control, to more societal questions. Some experts for example expect that Big Data will help to widen de divide between rich and poor, haves and have-nots. Or as the report calls it, there are concerns about ‘the power agendas of governments and corporations, the interests with the most Big Data resources’. These questions are backed up by opinions and viewpoints from experts: professors, public speakers and authors. I’m tempted to repeat many of the thought-provocative quotes from the report, but would
rather urge the reader to read the report itself, since the quotes come out even better when read in context. I would like to share one though, as it brings some highly needed realism to our conversations about Big Data. It’s from Dan Ness, principal research analyst at MetaFacts: “A lot of ‘Big Data’ today is biased and missing context, as it’s based on convenience samples or subsets. We’re seeing valiant, yet misguided attempts to apply the deep datasets to things that have limited relevance or applicability. They’re being stretched to answer the wrong questions. I’m optimistic that by 2020, this will be increasingly clear and there will be true information pioneers who will think outside the Big Data box and base decisions on a broader and balanced view. Instead of relying on the ‘lamppost light,’ they will develop and use the equivalent of focused flashlights.”
