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Ethical and Social Issues in Big Data Practice

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Authors: Rachel Finn, Anna Donovan and Kush Wadhwa
(Trilateral Research & Consulting, LLP)
Presented at BYTE WP2 Workshop Lyon, 11 Sept 2014

Published in: Technology
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Ethical and Social Issues in Big Data Practice

  1. 1. BYTE: Big data roadmap and cross-disciplinary community for addressing societal externalities Ethical and social issues in big data practice Rachel Finn, Anna Donovan and Kush Wadhwa Trilateral Research & Consulting, LLP BYTE WP2 Workshop Lyon, 11 Sept 2014
  2. 2. WP2: Elements of societal impact Task Description T2.1 Economic issues in big data T2.2 Legal issues in big data T2.3 Social and ethical issues in big data* T2.4 Political issues in big data T2.5 Public perceptions relevant to big data* T2.6 Open access to data T2.7 Validation workshop Task 2.3  D2.1 Task 2.5  D2.2 For information related to open access and big data (T2.6), please see D2.3 @BYTE_EU www.byte-project.eu
  3. 3. Objectives To understand what potential social and ethical externalities exist relative to big data processing To offer informed conjecture as to what members of the public might expect in a big data environment @BYTE_EU www.byte-project.eu
  4. 4. Methodology Both based on desk research / literature review ◦ Review of social and ethical issues focused on academic journal articles, research reports, media materials, etc. ◦ Review of public perceptions and aspirations focused on public opinion surveys ◦ E.g., Special Eurobarometer 359: Attitudes on Data Protection and Electronic Identity in the European Union 2012 ◦ Big Data: Public views on the Collection, Sharing and Use of Personal Data by Government and Companies 2014 ◦ Unisys Security Index: UK 2014 @BYTE_EU www.byte-project.eu
  5. 5. Practices examined • Transparency • Profiling and tracking • Re-use / secondary use • Data access @BYTE_EU www.byte-project.eu
  6. 6. Transparency Potential positive impacts ◦ Increased support for processing of data ◦ Information Commissioner’s Office (UK) – “Companies are asking… ‘should we do this with the data’?” ◦ Transparency may lead to greater trust, and more willingness to provide data Potential negative impacts ◦ Data sabatoge – “once actors realise that an institution is collecting data and looking for patterns, they can attempt to sabotage this by providing false information” ◦ A “chilling effect” – individuals restrain themselves from particular behaviours because they suspect that their activities are being monitored Unisys 2014 survey: 75% of British people will not shop or bank with people they cannot trust to safeguard their personal information @BYTE_EU www.byte-project.eu
  7. 7. Profiling / tracking Potential positive impacts ◦ Trend identification ◦ Personalisation ◦ Efficiency Potential negative impacts ◦ Discrimination ◦ Objectification ◦ Exploitation ◦ Privacy infringement Eurobarometer Flash 225: What is personal data? Information about tastes and opinions (27%), nationality (26%), hobbies, sports and places visited (25%), and websites visited (25%). @BYTE_EU www.byte-project.eu
  8. 8. Re-use / secondary use Potential positive impacts ◦ Use of “data exhaust” for innovation or to capture efficiencies ◦ Limits the need for costly duplication of recourses Potential negative impacts ◦ The “data gap” ◦ Extending “discriminatory” practices Eurobarometer 359: 34% of respondents were concerned that their information is being used without their knowledge and 23% were concerned about their information being used in different contexts from the ones that were disclosed to them @BYTE_EU www.byte-project.eu
  9. 9. Data access Potential positive impacts ◦ Opening access to data can enable the linking of data sets to generate new insights ◦ Differential access may be appropriate in some circumstances Potential negative impacts ◦ Creation of a “digital hierarchy” ◦ Gender, race and class bias in those creating the digital models ◦ Potential privacy infringements when data sets are opened, linked and mined. Ipsos Mori 2014: 90% support the use of people’s data to help develop treatment for cancer, 75% support data being used to improve the scheduling of transport services, and 70% support data use to prevent crimes @BYTE_EU www.byte-project.eu
  10. 10. QUESTIONS Any questions? Key contacts: ◦ Rachel Finn, rachel.finn@trilateralresearch.com ◦ Anna Donovan, anna.donovan@trilateralresearch.com Thank you @BYTE_EU www.byte-project.eu

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