Quotessence
Home / Topics / Big Data Quotes

Big Data Quotes

Browse 21 quotes about Big Data.

Big Data Quotes

“In the era where artificial intelligence and algorithms make more decisions in our lives and in organizations, the time has come for people to tap into their intuition as an adjunct to today’s technical capabilities. Our inner wisdom can embed empirical data with humanity.”

WisdomHumanityIntuitionDataDecisionsArtificial IntelligenceAlgorithmsMachine LearningEraBig Data
Book:small wins BIG SUCCESS: A handbook for exemplary success in post Covid19 Outbreak Era
Create image

“From a mathematical point of view, however, trust is hard to quantify. That's a challenge for people building models. Sadly, it's far easier to keep counting arrests, to build models that assume we're birds of a feather and treat us as such. Innocent people surrounded by criminals get treated badly, and criminals surrounded by law-abiding public get a pass. And because of the strong correlation between poverty and reported crime, the poor continue to get caught up in the digital dragnets. The rest of us barely have to think about them.”

CrimeInjusticeInequalityFairnessBig DataFeedback Loop
Book:Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
Create image

“And yet Rebecca felt that it was hard to tell whether the secret algorithms of Big Data did not so much reveal you to yourself as they tried to dictate to you what you were to be. To accept that the machines knew you better than you knew yourself involved a kind of silent assent: you liked the things Big Data told you you were likely to like, and you loved the people it said you were likely to love. To believe entirely in the data entailed a slight diminishment of the self, small but crucial and, perhaps, irreversible.”

IdentityInformation AgeDexter PalmerVersion ControlBig Data
Book:Version Control
Create image

“Jack's marketing books had been a part of her life for so long that she had ceased to register their presence, simply moving them from the couch to the coffee table, from the bed to the nightstand. How to Sell Everything to Anybody. Eight Great Habits of CEOs. They all seemed to involve numbers, as if you could simply count yourself to riches, like following sheep to sleep.”

NumbersBooksMarketingAnalyticsBig Data
Book:Joy For Beginners
Create image

“Will those insights be tested,or simply used to justify the status quo and reinforce prejudices? When I consider the sloppy and self-serving ways that companies use data, I'm often reminded of phrenology, a pseudoscience that was briefly the rage in the nineteenth century. Phrenologists would run their fingers over the patient's skull, probing for bumps and indentations. Each one, they thought, was linked to personality traits that existed in twenty-seven regions of the brain. Usually the conclusion of the phrenologist jibed with the observations he made. If the patient was morbidly anxious or suffering from alcoholism, the skull probe would usually find bumps and dips that correlated with that observation - which, in turn, bolstered faith in the science of phrenology. Phrenology was a model that relied on pseudoscientific nonsense to make authoritative pronouncements, and for decades it went untested. Big Data can fall into the same trap. Models like the ones that red-lighted Kyle Behm and black-balled foreign medical students and St. George's can lock people out, even when the "science" inside them is little more than a bundle of untested assumptions.”

ScienceFairnessPseudosciencePhrenologyBig DataFeedback Loop
Book:Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
Create image

“Pull approaches differ significantly from push approaches in terms of how they organize and manage resources. Push approaches are typified by "programs" - tightly scripted specifications of activities designed to be invoked by known parties in pre-determined contexts. Of course, we don't mean that all push approaches are software programs - we are using this as a broader metaphor to describe one way of organizing activities and resources. Think of thick process manuals in most enterprises or standardized curricula in most primary and secondary educational institutions, not to mention the programming of network television, and you will see that institutions heavily rely on programs of many types to deliver resources in pre-determined contexts. Pull approaches, in contrast, tend to be implemented on "platforms" designed to flexibly accommodate diverse providers and consumers of resources. These platforms are much more open-ended and designed to evolve based on the learning and changing needs of the participants. Once again, we do not mean to use platforms in the literal sense of a tangible foundation, but in a broader, metaphorical sense to describe frameworks for orchestrating a set of resources that can be configured quickly and easily to serve a broad range of needs. Think of Expedia's travel service or the emergency ward of a hospital and you will see the contrast with the hard-wired push programs.”

EconomyInnovationPlatformsAdoptionFlexibilityPushPullBig DataWeb 2 0AdaptionCrowdsourcingModularityAggregatorInformation Ecoomy
Author:John Hagel III
Create image