This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688127

Legal and Ethical issues in Social Capital Analysis

Dr. David Barnard-Wills, david.barnard-wills@trilateralresearch.com

Senior Research Analyst

Trilateral Research

www.trilateralresearch.com

@trilateral_UK, @dbarnardwills

Developing Careers through Social Networks and Transversal Competencies

Overview

The general politics & sociology of social capital

Issues arising from the social capital analysis

Issues arising from the results of the analysis

The question of external social media data

Recommendations

2Funded by the EU (Horizon 2020 Programme) | © DEVELOP – Developing Careers through Social Networks and Transversal Competencies

The politics & sociology of social capital

Social capital is complex

A metaphor

Not necessarily a property of any given individual (but of a network/culture/context).

Workplace social capital is already riddled with political/ethical issues before we do any analysis

. For example:

organizational mechanisms can channel women and racial/ethnic minority men into less

prestigious tracks with resulting intra-organizational job segregation (Collins 1997; DiPrete and

Soule 1988).

Differential access to training can resulting in the "de-skilling" of individuals in these groups

(Knoke & Ishio 1998; Mueller, Parcel, and Tanaka 1989; Nkomo and Cox 1990), resulting in

truncated opportunities for mobility.

Informal processes can exclude these groups from key networks and from mentoring relationships

(Baldi and McBrier 1997; Kanter 1977), relegating them as outsiders to organisational culture.

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The politics & sociology of social capital

Men and women, and people of different ethnicities:

Experience work networks, both social and professional in different ways,

Tend to have different work networks

Face different challenges in building and using those networks,

and gain differential benefits from the networks

The idea that there is a “best/perfect/ideal/required” social network or social capital

for a particular job role is therefore likely to be discriminatory.

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Then some issues arise from the analysis...

Accuracy and validity

Do social networks capture social capital?

What types of capital are excluded from the analysis?

How comprehensive is our initial data set, and is discrimination already “baked in”? (e.g all senior

staff are male and have “male” social networks)

Privacy and data protection concerns

SNA is re-use of data provided for another purpose

SNA includes the analysis of data that may not be transparent to the users (this being the point)

Therefore consent for the analysis should be separate from consent to use the social network

Particularly if its a business-critical network, - no opportunity not to use.

Consent is individual, network is not

How to communicate the SNA to participants?

Gaming social networks for social capital, & unwanted changes to behaviour

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Then some issues arise from the results of the analysis...

Harm to standing

Management decisions (jobs/personnel changes ) on the basis of social network analysis

E.g. From this social network graph, it looks like you are a bottleneck

Psychological harm

Negative reflections

Further privacy risks

How are analysis results accessible? (to user, to manager? To HR?)

Risk of Re-identification, -e.g. through location in a network, and commonly known demographics

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Non-workplace social networks?

Should the DEVELOP tool draw upon non-workplace (personal) social networks to

inform social capital analysis?

Motivation – “personal social networks have more information about individuals’

social capital. Which might be relevant to their career development. Some might be

highly relevant (e.g. LinkedIn connections with peers in industry).

PIA report D4.2 argues no.

Employment contracts and policies + proprietary work social networks provided for work purposes

simplifies many data protection concerns.

People use social networks in vastly multiple ways, likely highly non-comparable.

Users would have to trust employers with access to social media accounts.

Increases risk of workplace surveillance.

complexityIncreases risk of users not understanding privacy risks.

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SuggestionsAnalytical strategies should expect differences in social network/capital

opportunities to counter-act gender and ethnicity-based "channeling" and

use more-organisationally relevant characteristics to: guide career choice;

monitor access to training and ensure that it is egalitarian;

expand access to mentorship

Consent process –

Borgatti and Molina propose to expand the standard consent form (which binds researcher and

respondent) to include the organization’s management as well, committing them not to use the

resulting data to evaluate individual performance.

Provide clarity on the how SN data will be collected and analysed (visualisation?)

Interpreting and communicating the output

Social capital analysis is a tool for the user to reflect upon their career, development NOT a

management metric.

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ResourcesStephen Borgatti & Jose-Luis Molina,, Towards ethical guidelines for network research in

organisations, http://www.analytictech.com/borgatti/papers/ethics2.pdf

Solon Barocas & Andrew Selbst, Big Data’s disparate impact. California Law Review, 2016

Pauline T. Kim, Data driven discrimination at work, William and Mary Law Review, 2017.

Cynthia Dwork & Deirdre K. Mulligan, It’s not Privacy, and iIts Not Fair, 2013.

https://www.stanfordlawreview.org/online/privacy-and-big-data-its-not-privacy-and-its-not-

fair/

O'Neil, C. (2016) Weapons of Math Destruction: How big data increases inequality and

threatens democracy. St Ives: Allen Lane.

Frank Pasquale (2015) Black Box Society: The secret algorithms that control money and

information. Harvard University Press.

Gandy. O. (2009) Coming to Terms with Chance: Engaging Rational Discrimination and

Cumulative Disadvantage. Oxford: Routledge

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