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4. Workshop Responsible Data Science - Discussion on Confidentiality in data science by Ronald Leenes


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Discussion on Confidentiality in data science: “Data science that ensures confidentiality – How to answer questions without revealing secrets?” (session leader prof.dr. Ronald Leenes)

To future-proof responsible data science methods, foundational research is needed, and, given the complementarity of TU/e and TiU in JADS, there are great opportunities to collaborate on this theme. This was reflected by the JADS Workshop on Responsible Data Science

Published in: Data & Analytics
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4. Workshop Responsible Data Science - Discussion on Confidentiality in data science by Ronald Leenes

  1. 1. JADS-ws on Responsible Data Science confidentiality prof.dr. Ronald Leenes Understanding Society
  2. 2. data determinism identity theft data protection
  3. 3. in a moral community people do the right things for the right reasons (not because it is the law)* *but a stick might help
  4. 4. “confidentiality”
  5. 5. 95/46/ECData protection Directive
  6. 6. GDPRCOM(2012) 11 final 25-01-2012 General Data Protection Regulation
  7. 7. onfidentialitypersonal data fairness autonomy transparency & accountability purpose limitation data minimisation security
  8. 8. the GDPR introduces/reinforces some serious challenges for data scientists claim purpose limitation data minimisation transparency accountability privacy by design
  9. 9. data security will become an even more challenging topic claim cybercrime data breach notification secure & process
  10. 10. anonymization is dead/dying and Data Science slams the last nails in the coffin claim reidentification profiles applied all data are personal data* *right, Nadya
  11. 11. 1. (how) can we reconcile Data Science with ‘GDPR’? 2. can data security be reconciled with processing? 3. do we have to stop worrying and learn to love processing personal data? questions
  12. 12. time