@BYTE_EU www.byte-project.eu BYTE: Horizontal analysis of societal externalities Hans Lammerant - VUB Big data roadmap and cross-disciplinary community for addressing societal externalities
@BYTE_EU www.byte-project.eu
BYTE: Horizontal analysis of societal externalities
Hans Lammerant - VUB
Big data roadmap and cross-disciplinary community for addressing societal externalities
@BYTE_EU www.byte-project.eu
ExternalitiesDefinition
• Positive externalities occur when a product, activity or decision by an actor causes positive effects or benefits realized by a third party resulting from a transaction in which they had no direct involvement.
• Negative externalities occur when a product, activity or decision by an actor causes costs (or harm) that is not entirely born by that actor but that affects a third party.
Problems
• Economical concept -> application in non-economical areas?
• Boundary internal - external
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Big Data AssessmentCase study Raw dataset or typical volume used
– order of magnitude
Total volume of data holdings –
order of magnitude
Environment PB not available
Energy TB PB
Crisis
informatics
GB (daily volume) not available
Smart city GB not available
Healthcare GB TB
Culture small GB
Maritime KB-GB not available
Table 1: Volume of data – order of magnitude
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Big Data AssessmentCase study Velocity of data acquisition
Environment high
Energy high
Crisis informatics high
Smart city high
Healthcare low
Culture low
Maritime low
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Big Data AssessmentVariety
- Challenge present in all case studies
Veracity
- Challenge present in several, but not all, case studies
- Term covers several issues: correctness, resolution or granularity, uncertainty aboutmeaningfullness
Conclusion
- Big Data as umbrella term captures variety of situations
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Technical challenges
Data Acquisition:
- switch to sensor-driven data acquisition
- access to other data sources
Data Analysis: only occasionally mentioned as a challenge
DataAcquisition
DataAnalysis
DataCuration
DataStorage
DataUsage
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Technical challenges
Data Curation
• Interoperability
• Veracity
• Privacy, data protection, data security
Data Storage: only occasionally mentioned as a challenge
DataAnalysis
DataAcquisition
DataCuration
DataStorage
DataUsage
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Technical challenges
Data Usage
• mindset, organisational cultures -> Adaptation challenges
Conclusion:
• Challenges mostly in data collection, data curation and data usage phase
• Often technical challenges are translation of societal externalities
DataAnalysis
DataAcquisition
DataCuration
DataStorage
DataUsage
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Economic ExternalitiesEconomic externalities +/- Crisis
Informatics
Culture Energy Environment Healthcare Smart city
Improved efficiency + + + + +
Innovation + + + + + + +
Changing business models +/- - +/- +/- +/- +/-
Employment +/- + + +/-
Dependency on public
funding- - - - - -
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Social and Ethical ExternalitiesSocial and ethical
externalities
+/- Crisis
Informatics
Culture Energy Environment Healthcare Smart city
Improved efficiency and
innovation+ +/- + + +/- +/- +
Improved awareness and
decision-making+ + + + +
Participation + + + + +
Equality - - - -
Discrimination - - - -
Trust - –/+ - - –/+ –/+
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Legal ExternalitiesLegal externalities +/- Crisis
Informatics
Culture Energy Environment Healthcare Smart city
Privacy - - - - - -
IPR - - - - -
Liability,
accountability- - - - - -
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Political ExternalitiesPolitical externalities +/- Crisis
Informatics
Culture Energy Environment Healthcare Smart city
private vs. public and
non-profit sector- - - - -
losing control to actors
abroad- - - - -
improved decision-
making and participation+ + + +
political abuse &
surveillance- - -
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ConclusionsEconomic externalities
• Positive impact: improvement efficiency and innovation
• Changing and new business models -> possibility of dependence on dominant players
• Public funding proves to be important in kick-starting a data economy
Social and ethical externalities
• Improved efficiency and innovation for social, non-profit objectives
• Risk for negative impact on privacy and equality and for new discriminatory practices
• Problems with trust
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ConclusionsLegal externalities
• Data protection and intellectual property rights prove to be a barrier to big data
• Both serve to protect other societal values, but are considered outdated and too restrictive
• Also other legal frameworks need updating or clarification
Political externalities
• Relation between public and non-profit versus private sector
• Fear to lose control to actors abroad
• Perspectives on these issues varied a lot
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Big data and externalitiesCausal explanation?
How does big data affects interactions between actors?
Big DataInteractions
between actorsExternalities
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Categorisation of externalities• Benefits: practices aiming at capturing and maximizing the benefits of big data
• Regulatory practices: practices aiming at maximizing an objective at a societal level by balancing interests, but which are now negatively affected by big data. They show up as negative externalities because their balancing of interests does not deliver the same positive results any more.
• Protective practices: practices aimed at preserving other values or interests, which now get negatively affected.
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Categorisation of externalitiesBenefits Negative effects on regulatory
practicesNegative effects on protective practices
Improved efficiency and innovation
IPR Equality
Improved awareness and decision-making
Losing control to actors abroad Anti-discrimination
Participation Private vs. public and non-profit sector
Privacy
Improved political decision-making and participation
Trust (includes fear of capture and competition issues)
Liability, accountability
Political abuse & surveillance
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Effect of big data on interactions• Larger amount of interactions between actors
• Higher visibility of actors
• Higher penetration of organisational boundaries → traditional gatekeeping gets disrupted
• Data becomes network good → positive network effects
• Shift in transactions from exchange of goods to delivery of services → shift from momentary transaction to regulating continuous data flows
• Changing role of internet: from market place where actors meet into digital environment in which value creating production processes take place
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Effect on regulatory and protective practices• Current regulatory and protective practices reflect old transaction model→ high transaction costs → become disfunctional and result in negative externalities (e.g. rights clearance in copyright, consent in data protection)
• Enlarged visibility and penetration of boundaries: privacy problems forindividuals and for organisations
• Positive network effects: anonymization becomes unreliable, propagation of discriminatory effects
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QUESTIONS
Any questions?