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»Big data – small problems?«
Ethische Perspektiven auf Forschung unter Zuhilfenahme
onlinebasierter Kommunikationsspuren
N...
Aufschlag

1. Dimensionen von Forschungsethik und »hybride« Kontexte
von Onlineforschungsethik
2. »Big Data« als forschung...
Was ist (Forschungs-)Ethik?

Suche nach allgemeinen Prinzipien oder Beurteilungskriterien zur
Begründung des richtigen Han...
»Hybridität« der Kontexte von Onlineforschung

ForscherKontexte
Hybride Kontexte

Nutzer-Kontexte

• forschungsethische St...
Ethisch relevante Merkmale der Onlinekommunikation
 Web als »science laboratory« und »Spielwiese«, als » gigantisches, le...
»Big Data« als forschungsethische Herausforderung

»big data«-Analysen verstanden als Erfassung, Speicherung und
Verwertun...
Ebenen ethischer Entscheidungsfindung

Meta-Ethik
Ethische Theorie
Ethische Prinzipien
Ethische Regeln / Richtlinien
Allta...
Ethische Regeln und Grundsätze

Einige Grundsätze »guten« wissenschaftlichen Arbeitens (DFG)
 Nachvollziehbarkeit aller S...
Ethische Standards gegenüber Forschungsteilnehmern

 Freiwilligkeit der Teilnahme als Voraussetzung
 Prinzip der informi...
Context matters: Freiwilligkeit / Informed Consent
 Problem der Entgrenzung von Privatheit/Öffentlichkeit

 Kontext hat ...
Which context?
Problem des »frictionless sharing«

Heise | »big data« & Forschungsethik 11
Prinzip der Anonymisierung

 potenzielle De-Anonymisierung von Datensätzen (Narayanan/
Shmatikov 2008, Zimmer 2010), (Re-...
Anspruchsgruppen ethischer Entscheidungsfindung

Intermediäre

Heise | »big data« & Forschungsethik 13
Neue Akteurskonstellationen
Forscher/-innen
 Wer interagiert mit wem/was?

Intermediäre

 Intermediäre implementieren
ei...
Kommunikationsethische Prinzipien
Nicht-Interaktion mit Nutzer/-innen unterminiert basale
kommunikationsethische Prinzipie...
Basale forschungsethische Prinzipien
 Nonmalificence und Benefience: Nichtschädigung, Wohlergehen, Autonomie
und Selbstbe...
Alte Fragen, neue Relevanz

»The social sciences can … have a tremendous impact on society,
even to the point of revolutio...
Offenes Ende

 »big data«-Analysen berühren zentrale forschungsethische
Dimensionen
 Herausforderung der Abwägung von te...
Herzlichen Dank!
Nele Heise, M.A.
Hans-Bredow-Institut Hamburg
n.heise@hans-bredow-institut.de
@neleheise
www.neleheise.de
Literatur (1/2)
Barbera, Marco V., Epasto, Alessandro, Mei, Alessandro, Perta, Vasile C., & Stefa, Julinda (2013). Signals...
Literatur (2/2)
Heise, N., & Schmidt, J.-H. (im Erscheinen): Ethik der Onlineforschung. In: M. Welker, M. Taddicken, J.-H....
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»Big data – small problems?« - Ethische Perspektiven auf Forschung unter Zuhilfenahme onlinebasierter Kommunikationsspuren

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Mein Vortrag auf der diesjährigen CvK-Fachgruppentagung "Digital Methods" am 8. November in Wien

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»Big data – small problems?« - Ethische Perspektiven auf Forschung unter Zuhilfenahme onlinebasierter Kommunikationsspuren

  1. 1. »Big data – small problems?« Ethische Perspektiven auf Forschung unter Zuhilfenahme onlinebasierter Kommunikationsspuren Nele Heise, M.A. Hans-Bredow-Institut Hamburg Tagung „Digital Methods“ | IPK Uni Wien 8. November 2013
  2. 2. Aufschlag 1. Dimensionen von Forschungsethik und »hybride« Kontexte von Onlineforschungsethik 2. »Big Data« als forschungsethische Herausforderung 3. Offene Fragen Heise | »big data« & Forschungsethik 2
  3. 3. Was ist (Forschungs-)Ethik? Suche nach allgemeinen Prinzipien oder Beurteilungskriterien zur Begründung des richtigen Handelns (Fenner 2010) »Ethics are guidelines and principles that help us to up-hold our values – to decide which goals of research are most important and to reconcile values and goals that are in conflict. Ethical guides are not simply prohibitions; they also support our positive responsibilities.« Diener/Crandall (1978: 3) Zentrale Dimensionen von Forschungsethik Wertbasis, Verantwortung, ethische Entscheidungsfindung Heise | »big data« & Forschungsethik 3
  4. 4. »Hybridität« der Kontexte von Onlineforschung ForscherKontexte Hybride Kontexte Nutzer-Kontexte • forschungsethische Standards/Prinzipien • technische, methodologische Anforderungen • Forschungspraxis/-erfahrung/-schwerpunkte • • • • • technische & soziale Rahmungen der Medienpraktiken Eigenschaften der Onlinekommunikation AGBs, Rechte auf Anbieterseite individuelle ethische Argumentationsparadigmen Vertrauen & Verantwortung • Ethische Prinzipien der Online-Kommunikation • (in-)formelle »Spielregeln« (z. B. Netiquetten) • Mediennutzungskompetenzen Heise | »big data« & Forschungsethik 4
  5. 5. Ethisch relevante Merkmale der Onlinekommunikation  Web als »science laboratory« und »Spielwiese«, als » gigantisches, leicht zugängliches Archiv von Kommunikations- und Interaktionsvollzügen« (Fraas et al. 2012: 189): Reichhaltigkeit der Daten, einfacher Feldzugang, z. T. bessere Bedingungen für Umsetzung einzelner Methoden; Einblick in zuvor nicht zugängliche Bereiche, Lebenswelten, Aktivitäten  Ethische Entscheidungsfindung unterliegt z. T. erschwerten Bedingungen: o (räumliche/zeitliche) Entkontextualisierung; globale Reichweite o Datenvernetzung und -persistenz o Entkörperlichung, Grad sozialer Präsenz und Sichtbarkeit, Anonymität (Verifizierung, Authentifizierung) o Entgrenzung von Öffentlichkeit und Privatheit (Daten, »Räume«) o Rechtsunsicherheit Heise | »big data« & Forschungsethik 5
  6. 6. »Big Data« als forschungsethische Herausforderung »big data«-Analysen verstanden als Erfassung, Speicherung und Verwertung von »massive quantities of information produced by and about people, things, and their interactions« boyd/Crawford (2011: 1)  dies berührt viele Dimensionen von Forschungsethik: o Grundsätze »guten« wissenschaftlichen Arbeitens, o (kommunikations-)ethische Standards im Umgang mit Forschungsteilnehmern, o grundlegende forschungsethische Prinzipien Heise | »big data« & Forschungsethik 6
  7. 7. Ebenen ethischer Entscheidungsfindung Meta-Ethik Ethische Theorie Ethische Prinzipien Ethische Regeln / Richtlinien Alltagsmoral / „ordinary moral sense“ Kritisch-evaluative Ebene Unmittelbar-situative Ebene Fünf-Stufen-Modell ethischer Entscheidungsfindung nach Strohm Kitchener/Kitchener (2009) Heise | »big data« & Forschungsethik 7
  8. 8. Ethische Regeln und Grundsätze Einige Grundsätze »guten« wissenschaftlichen Arbeitens (DFG)  Nachvollziehbarkeit aller Schritte: Wissen, Darstellungsformen  Veröffentlichung der Ergebnisse: Formen, Open Data  Anwendung bestmöglicher Standards, v. a. im Umgang mit Untersuchungsteilnehmern Prämisse: Einige »big data«-Analysen ≠ Inhaltsanalysen  Daten als Handlungsakte (social data), nicht Artefakte Heise | »big data« & Forschungsethik 8
  9. 9. Ethische Standards gegenüber Forschungsteilnehmern  Freiwilligkeit der Teilnahme als Voraussetzung  Prinzip der informierten Einwilligung (»informed consent«)  Schutz der Teilnehmer: Anonymität, Privatheit  Nicht-Schädigung (Vermeidung möglicher Risiken)  Rechtlicher Kontext: Persönlichkeitsrechte, Datenschutz, Recht auf Informationelle Selbstbestimmung Heise | »big data« & Forschungsethik 9
  10. 10. Context matters: Freiwilligkeit / Informed Consent  Problem der Entgrenzung von Privatheit/Öffentlichkeit  Kontext hat Einfluss auf die produzierten Daten und die Erwartungen der Nutzer/-innen o »imagined audience« (Publikumsvorstellungen) o Beurteilungs- und Medienkompetenz der Nutzer/-innen  Erfassung von (explizit/implizit produzierten) Inhalten als Verletzung der »kontextuellen Integrität« (Nissenbaum 2004), also sozialer Normen (ggf. sogar AGB/Zugangsbeschränkungen)  Aggregation, Zusammenführung, Weiterverarbeitung von Inhalten als (potenzielle) Verletzung von Privatheit (boyd 2010)  Recht auf Informationelle Selbstbestimmung? Heise | »big data« & Forschungsethik 10
  11. 11. Which context? Problem des »frictionless sharing« Heise | »big data« & Forschungsethik 11
  12. 12. Prinzip der Anonymisierung  potenzielle De-Anonymisierung von Datensätzen (Narayanan/ Shmatikov 2008, Zimmer 2010), (Re-)Kombination von Datensätzen  Frage: Was sind persönliche oder sensible Informationen? Heise | »big data« & Forschungsethik 12
  13. 13. Anspruchsgruppen ethischer Entscheidungsfindung Intermediäre Heise | »big data« & Forschungsethik 13
  14. 14. Neue Akteurskonstellationen Forscher/-innen  Wer interagiert mit wem/was? Intermediäre  Intermediäre implementieren eigene Werte und steuern Möglichkeitshorizont  Neue Abhängigkeiten (Forschungsfreiheit?) Nutzer/-innen  AGBs ersetzen/überlagern informed consent ? Heise | »big data« & Forschungsethik 14
  15. 15. Kommunikationsethische Prinzipien Nicht-Interaktion mit Nutzer/-innen unterminiert basale kommunikationsethische Prinzipien (Wolff 2007)  Reziprozität: Wechselseitigkeit der Kommunikation o u. a. Folgen für informed consent  Personalität: Anerkennung des Personseins des Anderen, Verbot der Verdinglichung /Objektivierung/Instrumentalisierung o Wahrnehmung von Nutzer/-innen (als „einrollende Datensätze) o Datenaggregation/-interpretation »dehumanizes those being judged … and thus threats those profiled objects as collections of facts, rather than as persons« (McFarland 2012) Heise | »big data« & Forschungsethik 15
  16. 16. Basale forschungsethische Prinzipien  Nonmalificence und Benefience: Nichtschädigung, Wohlergehen, Autonomie und Selbstbestimmung, »Respect for persons« o Informationelle Selbstbestimmung, Entscheidungen der Nutzer/-innen o Interpretation/Darstellung von Befunden und deren (mögliche) Folgen; »predictive analyses« (Wen 2012)  Justice: Gerechtigkeit i.S.v. Gleichbehandlung aller o Wer/was ist (nicht) repräsentiert?: »What happens if you live in the shadow of big data sets?« (Crawford 2013) o Wie umgehen mit inhärenten »biases« von Daten? o Kontrolle und Zugang zu Daten und Tools  Fidelity (Vertrauen) o Transparenz, Offenlegung und Kommunikation von Forschung Heise | »big data« & Forschungsethik 16
  17. 17. Alte Fragen, neue Relevanz »The social sciences can … have a tremendous impact on society, even to the point of revolutionizing our conceptions of human nature, society, and culture.« Diener/Crandall (1978: 195) »Incentives sind die wahren Wertewandler unserer Gesellschaft« Schirrmacher (2013) Fragen nach der Richtigkeit, Verantwortung und Folgen von Forschung Heise | »big data« & Forschungsethik 17
  18. 18. Offenes Ende  »big data«-Analysen berühren zentrale forschungsethische Dimensionen  Herausforderung der Abwägung von technischer Machbarkeit und ethischer Vertretbarkeit einer »data-driven science«  Spannungsfeld zwischen Aufrechterhaltung/Aufgabe forschungsethischer Prinzipien und Verunmöglichung von Forschung  Problembewusstsein, Sensibilisierung, Verständigung Heise | »big data« & Forschungsethik 18
  19. 19. Herzlichen Dank! Nele Heise, M.A. Hans-Bredow-Institut Hamburg n.heise@hans-bredow-institut.de @neleheise www.neleheise.de
  20. 20. Literatur (1/2) Barbera, Marco V., Epasto, Alessandro, Mei, Alessandro, Perta, Vasile C., & Stefa, Julinda (2013). Signals from the Crowd: Uncovering Social Relationships. http://conferences.sigcomm.org/imc/2013/papers/imc148-barberaSP106.pdf . Zugegriffen am 7. November 2013. Baym, Nancy (2013): Data not seen: The uses and shortcomings of social media metrics. First Monday. Number 10. doi: http://dx.doi.org/10.5210%2Ffm.v18i10.4873. Zugegriffen am 7. November 2013. boyd, danah (2010). “Privacy and Publicity in the Context of Big Data.” Vortrag auf der WWW. Raleigh, North Carolina, am 29. April 2010). http://www.danah.org/papers/talks/2010/WWW2010.html Zugegriffen am 8. November 2013. boyd, d., & Crawford, K. (2011). Six Provocations for Big Data. http://softwarestudies.com/cultural_analytics/Six_Provocations_for_Big_Data.pdf. Zugegriffen: 9. Juni 2013. Burgess, J., & Bruns, A. (2012). Twitter Archives and the Challenges of ‘Big Social Data’ for Media and Communication Research. M/C Journal, 15(5). http://journal.media-culture.org.au/index.php/mcjournal/article/viewArticle/561/0. Zugegriffen: 10. Juni 2013. Capurro, Rafael; Pingel, Christoph: (2002): Ethical issues of online communication research. In: Ethics and Information Technology, Nr. 4(2002). S. 189194. Crawford, K. (2013). The Hidden Biases of Big Data. http://blogs.hbr.org/cs/2013/04/the_hidden_biases_in_big_data.html. Zugegriffen: 10. Juni 2013. Deutsche Forschungsgemeinschaft (1998). Vorschläge zur Sicherung guter wissenschaftlicher Praxis: Empfehlungen der Kommission „Selbstkontrolle in der Wissenschaft“. Weinheim: Wiley-VCH. Diener, E., & Crandall, R. (1978). Ethics in Social and Behavioral Research. Chicago: University of Chicago Press. Dzeyk, W. (2001). Ethische Dimensionen der Online-Forschung. Kölner Psychologische Studien, 6(1), 1–30. http://kups.ub.unikoeln.de/2424/1/ethdimon.pdf (03.11.2013). Eynon, R., Schroeder, R., & Fry, J. (2009). New Techniques in Online Research. Challenges for Research Ethics. 21st Century Society, 4(2), 187–199. Fenner, D. (2010). Einführung in die Angewandte Ethik. Tübingen: Francke. Fraas, C., Meier, S., & Pentzold, C. (2012). Online-Kommunikation. Grundlagen, Praxisfelder und Methoden. Wien: Oldenbourg Verlag. Gillespie, T. (2010). The Politics of ‘Platforms’. New Media & Society, 12(3), 347–364. Heise, N. (2013). ‘Doing it for real’ – Authentizität als kommunikationsethische Voraussetzung onlinebasierter Forschung. In M. Emmer, A. Filipovic, J.H. Schmidt, & I. Stapf (Hrsg.), Echtheit, Wahrheit, Ehrlichkeit. Authentizität in der computervermittelten Kommunikation (S. 88–109). Weinheim: Juventa.
  21. 21. Literatur (2/2) Heise, N., & Schmidt, J.-H. (im Erscheinen): Ethik der Onlineforschung. In: M. Welker, M. Taddicken, J.-H. Schmidt, N. Jackob (Hrsg.): Handbuch Online-Forschung. Herbert von Halem Verlag (= Neue Schriften zur Online-Forschung; Bd. 12). Mahrt, M. & Scharkow, M. (2013). The Value of Big Data in Digital Media Research. Journal of Broadcasting & Electronic Media, 57(1), 20-33. doi: 10.1080/08838151.2012.761700 Manovich, L. (2012). Trending: The Promises and the Challenges of Big Social Data http://www.manovich.net/DOCS/Manovich_trending_paper.pdf. Zugegriffen: 9. Juni 2013. McFarland, M. (2012). Ethical Implications of Data Aggregation http://www.scu.edu/ethics/practicing/focusareas/technology/internet/privacy/dataaggregation.html. Zugegriffen: 10. Juni 2013. Naranyan, A., & Shmatikov, V. (2008). De-anonymizing Social Networks http://www.cs.utexas.edu/~shmat/shmat_oak09.pdf. Zugegriffen: 8. November 2013. Schirrmacher, F. (2013): Vorwort zum G-Nome Projekt. Veröffentlicht am 7. November 2013. http://gutjahr.biz/2013/11/g-nome/ . Zugegriffen: 7. November 2013. Schmidt, J.-H. (2009). Braucht das Web 2.0 eine eigene Forschungsethik? Zeitschrift für Kommunikationsökologie und Medienethik, 11(2), 40–44. Schmidt, J.-H. (2012). Persönliche Öffentlichkeiten und informationelle Selbstbestimmung im Social Web. In J.-H. Schmidt, & T. Weichert (Hrsg.), Datenschutz (S. 215-225). Bonn: Bundeszentrale für politische Bildung. Strohm Kitchener, K., & Kitchener, R. F. (2009). Social Research Ethics. Historical and Philosophical Issues. In D. Mertens, & P. E. Ginsberg (Hrsg.), The Handbook of Social Research Ethics (S. 5–22). Thousand Oaks: Sage Publications. Uprichard, E. (2013). Big Data, Little Questions? Discover Society, (01.10.2013). Retrieved from http://www.discoversociety.org/focus-big-data-littlequestions/ Vis, Farida (2013). A critical reflection on Big Data: Considering APIs, researchers and tools as data makers. First Monday. Number 10. doi: http://dx.doi.org/10.5210%2Ffm.v18i10.4878. Zugegriffen am 8. November 2013. Wen, H. (2012). The Ethics of Big Data. http://www.forbes.com/sites/oreillymedia/2012/06/21/the-ethics-of-big-data. Zugegriffen: 10. Juni 2013. Wolff, O. J. (2007). Kommunikationsethik des Internets: eine anthropologisch-theologische Grundlegung. Hamburg: Verlag Dr. Kovač. Zimmer, M. (2010). ‘But the data is already public’: on the ethics of research on Facebook. Ethics and Information Technology, 12(4), 313–326. Heise | Forschungsethik Seite 21 von 21

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