Big Data ethics

By Andrej J. Zwitter. Big Data & Society, 2014

483 citations recorded by the source corpus.

The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and their knock-on effects. We are moving towards changes in how ethics has to be perceived: away from individual decisions with specific and knowable outcomes, towards actions by many unaware that they may have taken actions with unintended consequences for anyone. Responses will require a rethinking of ethical choices, the lack thereof and how this will guide scientists, governments, and corporate agencies in handling Big Data. This essay elaborates on the ways Big Data impacts on ethical conceptions.

Subfields: Artificial Intelligence, Safety Research, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/224103631809ed02119273b4674f97611dead836

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Citations in the corpus

Can Small and Synthetic Benchmarks Drive Modeling Innovation? A Retrospective Study of Question Answering Modeling Approaches (2021, background): “…is difﬁcult and inaccessible for the many groups without access to real users interacting with a real system, and privacy concerns can also limit the ethical collection and distribution of such benchmarks (Richards and King, 2014; Metcalf and Crawford, 2016; Paullada et al., 2020, inter alia ).”
Fairness in Machine Learning: A Survey (2020, background): “intrinsic biases in the sample will manifest themselves in any model built on the data [42, 33], inappropriate uses of data leading to (un)conscious bias(es) [41, 42], data veracity and quality [297], data relativity and context shifts [42, 233, 114], and subjectivity filters [41].”
Transformational shifts through digital servitization (2020, unknown): “In some cases, the firm knew more about its customers' fleets than they knew themselves (c.f., Zwitter, 2014).”
Where are human subjects in Big Data research? The emerging ethics divide (2016, background): “Together, these shifts are hard to quantify and ameliorate (Zwitter, 2014), frustrating the familiar ethical practices outside of biomedical research.”
Social Injustice in Surveillance Capitalism (2017, background): “This shapes “who we are before we make up our own minds” (Richards and King 2014: 396) and creates or further entrenches our sociocultural hierarchies (Tene and Polonetsky 2012).”
Ten simple rules for responsible big data research (2017, background): “In particular, data ungoverned by substantive consent practices, whether social media or the residual DNA we continually leave behind us, may seem public but can cause unintentional breaches of privacy and other harms [9,10].”
Data and its (dis)contents: A survey of dataset development and use in machine learning research (2020, background): “Data management and distribution Secure storage and appropriate dissemination of humanderived data is a key component of data ethics.(102) To have a culture of care for the subjects of the datasets we make use of requires us to prioritize the well-being of the subjects in the dataset throughout coll”
Digitization capability and the digitalization of business models in business-to-business firms: Past, present, and future (2020, background): “…more data exist today than have done so before in history (Smolan & Erwitt, 2012) – and approximately 5 billion gigabytes were generated from the beginning of recorded history until 2003, whereas 5 billion gigabytes of data were claimed to be generated every 10 seconds in 2015 (Zwitter, 2014).”