Data Science with Ethics

Making Data Science Work: Session 4


The COVID modeling of Imperial College’s epidemiologist, Neil Ferguson, which was the basis for the lockdown of Britain was found to be totally unreliable and ‘buggy mess’ - unreadable, non-reproducible, and sensitive to assumptions and initial conditions. But the impact was huge and could not be undone.
Data scientists are helping organizations determine optimal routes, risk, identity, education level etc. The number, depth, and scope of the decisions is increasing, and so is the impact. This leads to several questions:

  • How should data scientists think about their responsibility?
  • Do values have a role? Where should they draw the line?
  • What can experiences in other domains tell us about the journey ahead?
  • How should organizations evolve to carry the burden of decision making?
  • What kinds of systems and processes enable more responsible Machine Learning?

Panelists We have a couple of fantastic panelists to help us think through these questions:
Ashwin Kumar, Director of ML, Fidelity Investments
Suchana Seth, Fellow, Berkman Klein Center, Harvard University

Registration Register to participate via Zoom. Zoom link will be shared one day before the event. Or, watch the livestream on this page.
Registered participants can also leave comments and questions for the hosts and speakers, which will be taken up during the session.

Previous session: The previous session was held on 17 June. Summary of the session is available on

About the hosts: Venkata Pingali and Indrayudh Ghoshal of Scribble Data will host the meetup. Scribble Data is a Bangalore/Toronto startup, active in the data community. Scribble implements MLOps for Data using their feature store, Enrich. This enables data science teams to train models faster, and with confidence in the underlying data.

About the organizers: The Fifth Elephant is a platform for practitioners working with data (anywhere from ingestion, to its application in data science for different use cases) to showcase their work and to collaborate.

For further inquiries, contact 7676332020 or write to


Scribble Data