SIV851 Special module on e-Governance
Digital infrastructure, identity, online data and privacy
- First meeting: September 8, 5pm at SIT001 (please note the change from Sep 7 announced earlier).
- Please email email@example.com with SIV851 in the Subject if you are interested in attending.
- All the students interested in attending the course are requested to email a one page pdf indicating:
- the reason for your interest in the course
- any prior reading that you may have done on the topic and
- your views on the issues to be covered in the course.
- Final assignment here: Nov 14. Submissions
Classes and assignments
- To understand the policy and technology issues in digitisation and digital data requirements in governance - with special emphasis on demographic data, health, education, welfare and tax.
- To understand the issues in building the data infrastructure: digital identity, issues in privacy, threats to civil liberty, data integrity, data security, facilitating analytics, risks of analytics.
- Data infrastructure issues.
- Digital identity: local vs global ids, US SSN, Indian PAN and Aadhaar - features, similarities and differences. Possible power imbalance between the state and citizens.
- Privacy concerns: Chomsky, Glenn Greenwald and Snowden; LSE identity project report; various concerns with Aadhaar in Indian civil society; UIDAI reports; deliberations on privacy in the Supreme court.
- Big-data and inequality, risks and benefits of commercial usage of governance data: arguments of Cathy O'Neil and others.
- Analysis of vulnerabilities vs requirements.
- Privacy protection techniques: elements of cryptography; differential privacy and k-anonymity; database, network and system security issues.
- Identify key technology problems that need to be solved to ensure privacy compliance?
- Identify some key recommendations for an effective data privacy law?
- Open questions?
The module will have reading and discussions for 12 to 15 hours. In addition, each participant will be required to scribe and present a topic. Evaluations will be based on peer and instructor review of class participation, quality of reports and presentations.
We will invite experts from the domains of policy, law and computer scientists specialising in big data analytics for ``targetting'' for special sessions. We will also try to bring out a consolidated report at the end of the course.
Subhashis Banerjee / Dept. Computer Science and Engineering / IIT Delhi /
Hauz Khas/ New Delhi 110016