horizontal analysis of 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


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


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


Big Data AssessmentCase study Velocity of data acquisition

Environment high

Energy high

Crisis informatics high

Smart city high

Healthcare low

Culture low

Maritime low


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


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



Data Curation

• Interoperability

• Veracity

• Privacy, data protection, data security

Data Storage: only occasionally mentioned as a challenge

DataAnalysis

DataAcquisition

DataCuration

DataStorage

DataUsage



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


Economic ExternalitiesEconomic externalities +/- Crisis

Informatics

Culture Energy Environment Healthcare Smart city

Improved efficiency + + + + +

Innovation + + + + + + +

Changing business models +/- - +/- +/- +/- +/-

Employment +/- + + +/-

Dependency on public

funding- - - - - -


Social and Ethical ExternalitiesSocial and ethical

externalities

+/- Crisis

Informatics


Improved efficiency and

innovation+ +/- + + +/- +/- +

Improved awareness and

decision-making+ + + + +

Participation + + + + +

Equality - - - -

Discrimination - - - -

Trust - –/+ - - –/+ –/+


Legal ExternalitiesLegal externalities +/- Crisis

Informatics


Privacy - - - - - -

IPR - - - - -

Liability,

accountability- - - - - -


Political ExternalitiesPolitical externalities +/- Crisis

Informatics


private vs. public and

non-profit sector- - - - -

losing control to actors

abroad- - - - -

improved decision-

making and participation+ + + +

political abuse &

surveillance- - -


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


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


Big data and externalitiesCausal explanation?

How does big data affects interactions between actors?

Big DataInteractions

between actorsExternalities


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.


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


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


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


QUESTIONS

Any questions?

horizontal analysis of societal externalities

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