“Big data is everywhere.” George, Haas, Portland (2014), In: Academy of Management Journal, 2014, Vol. 57, No.2, p. 321
“In a work environment that is increasingly globally connected, rich in online media, and smart computational systems, sensemaking, interdisciplinarity, and computational thinking are being identified as part of an interrelated set of vital work skills for the future …” Calvard (2016), In: Management Learning, 2016, Vol. 47(1) 65-82, p. 71
Want to have a bright future? Learn statistics, computer science, mathematics and data science. I highly recommend not to go for an MBA. Nearly everybody can do that.
„Although this may sound obvious, the ethical implications of collecting such [sensor] data, coupled with issues such as data ownership, are likely to be complex, and thus call for revisiting formal guidelines for research procedures.” George, Gerhard et al. (2016), “Big data and and data science methods in management research”, In: Academy of Management Journal 2016, Vol. 59, No. 5, p. 1498
Big data is starting to effect management research with all the same ethical questions it has in the non-scientific environment.
“To a criminal, life must have been so much easier before Big Data and powerful analytics applications like face recognition.“ Marr, Bernard (2015), “Big data: using smart big data, analytics and metrics to make better decisions and improve performance”, p. 130
If you consider the recent terrorist attacks in Europe, especially in London, which is permeated by video cameras, this statement seems not to be true. I think it will also not reflect the perception of people, which feel more unsafe nowadays. In no other developed country is the murderrate through weapons as high as in the USA (30 per million per year). Since 2001 this number is constantly increasing in the country which can be considered as the pioneer of big data. Something seems to not fit here.
“In the furore about Big Data it’s easy to forget that it’s just data.” Marr, Bernard (2015), “Big data: using smart big data, analytics and metrics to make better decisions and improve performance”, p. 57
“There is little doubt that Big Data is changing the world. … As a result there is a huge amount of hype and fuss over Big Data.” Marr, Bernard (2015), “Big data: using smart big data, analytics and metrics to make better decisions and improve performance”, p. 9
It will be interesting to see if the way humans will use big data will further devide society. This quote seem to express that there might be 2 basic perceptions about big data: Excitement (positive) and fear (negative).
“If you torture the data long enough, it will confess.” Provost, Fawcett (2013), “Data Science for Business – What you need to know about data mining and data-analytic thinking.”, p. 113
Initial quote from Ronald Coase describing the practice of overfitting the data to a point where it is not generalizable anymore outside the training data.
„Big data does have certain ‚Big Brother‘ overtones that can make people nervous.“ Marr (2017), “Data strategy – How to profit from a world of big data, analytics and the internet of things”, p. 173
Well said. But in my opinion people complain on the one hand, but behave differently. They still use Facebook and Google and many even request more video surveillance. As if this would solve any essential problem society has.
„More data, it’s easy to believe, is better data.“ O’Neil (2016), “Weapons of math destruction”, p. 89
Maybe you notice O’Neil’s irony and sarcasm.
„…one client of mine wanted to recruit self-driven people that were able to use their own initiative. By analyzing different data sets from the type of people they wanted to recruit and those they wanted to avoid, the company found that candidates who filled out applications with browsers that were not pre-installed on their computers and instead had to be installed separately (such as Firefox or Chrome) tended to be better for that particular job.“ Marr (2017), “Data strategy – How to profit from a world of big data, analytics and the internet of things”, p. 27
How did they do that? Installing Firefox as proxy for “self-drivenness”? How do they get that data? Why is that Installing-behavior measuring “self-drivenness”? Maybe it is just measuring intelligence or IT-knowledge. To use a simple proxy like this for recruitment is highly problematic in my opinion. Lucky me I am using Firefox myself. 🙂
„Soon big data may be able to tell whether we’re falling in love.“ Mayer-Schönberger, Cukier (2013), “Big data – A revolution that will transform how we live, work and think.”, p. 192
I mean, really? Seriously? Is it also able to tell us how many kids we get and what they do in the future?
“…the biggest impact of big data will be that data-driven decisions are poised to augment or overrule human judgment.“ Mayer-Schönberger, Cukier (2013), “Big data – A revolution that will transform how we live, work and think.”, p. 141
This is one major claim and needs to be tested scientifically, which I hope to do throughout my research.
„Lest there be any doubt: big data saves lives.“ Mayer-Schönberger, Cukier (2013), “Big data – A revolution that will transform how we live, work and think.”, p. 61
Fantastic new world, isn’t it? 🙂
“In ‘Weapons of math destruction’, many poisonous assumptions are camouflaged by math and go largely untested and unquestioned.” O’Neil (2016), “Weapons of math destruction”, p. 7
In her intriguing book “Weapons of math destruction” from 2016, Cathy O’Neil describes practical problems of mathematical models embedded in today’s algorithms. It will be interesting to see if after a big bunch of positive Big Data literature in the past her book is the starting point of more critical Big Data research.
“When we talk about big data, we mean ‚big‘ less in absolute than in relative terms: relative to the comprehensive set of data.” Mayer-Schönberger, Cukier (2013), “Big data – A revolution that will transform how we live, work and think.”, p. 29
“Big” means that more or less all data of the population is available (N≈all), but does not mean that the population itself needs to be “big” in size e.g. in regards to memory space needed.
“There is a treasure hunt under way, driven by the insights to be extracted from data and the dormant value that can be unleashed by a shift from causation to correlation. But it’s not just one treasure. Every single dataset is likely to have some intrinsic, hidden, not yet unearthed value, and the race is on to discover and capture all of it.” Mayer-Schönberger, Cukier (2013), “Big data – A revolution that will transform how we live, work and think.”, p. 15
This quote expresses very nicely the almost religious belief in data analytics.
“In machine learning, the aim is to fit a model to the data.” Alpaydin (2016), “Machine Learning”, p. 58
This sentence represents the new big data idea that data itself can develop new models of the real world, which is a turn around of the classic scientific approach.