Leveraging the Data Explosion for the Public Interest

Dates

Contact us for details

Length of Course

3 hours

Delivery Method

Online

Cost

$425 CAD

Summary

Traditional data sources lag reality often by weeks or months and often don’t capture the complexity of our digitized and globalized economies and societies. Enter new digital, real-time, granular datasets that can be used to monitor, anticipate, and respond to events, whether as a by-product of our activities (“digital exhaust”) or deliberately collected for societal objectives. One example is the use of online restaurant bookings and online job postings during the pandemic to assess real-time economic activity.

This course explores the opportunities and challenges this phenomenon raises for policymakers.

The class will expose participants to the use of non-traditional datasets across a wide range of local and global applications and experiments undertaken in recent years – from those measuring economic activity to the spread of disease to the impacts of climate change to verifying official data from authoritarian regimes.

Participants will consider the potential such non-traditional datasets present to better measure, analyze, and advance the public interest in a more timely, targeted fashion, and as a complement to more traditional datasets. They will also confront some of the risks leaders will need to mitigate to fully leverage this potential.

Instructor

Danielle GoldfarbDanielle Goldfarb is an adviser and consultant on real-time data, the digital economy, and public policy. She is a senior fellow at the Centre for International Governance Innovation, a global fellow at the Woodrow Wilson Center’s Canada Institute, a distinguished fellow at the Asia Pacific Foundation of Canada and an adviser on public policy to Mila – Quebec Artificial Intelligence Institute.

One of Danielle’s current areas of research is on the potential of the data and artificial intelligence explosion to improve public interest outcomes, while also confronting the risks it presents. Danielle created and teaches a popular graduate seminar on this theme at the University of Toronto’s Munk School of Global Affairs. Her TEDx talk, “The Smartest Way to Predict the Future,” is about leveraging new technologies to address data bias, improving prediction. She runs a series for the Canadian Association for Business Economics and its Toronto counterpart on the "new tools of the economists' trade" on how economists are using machine learning and non-traditional datasets to complement traditional macroeconomic tools.

Danielle has also created leading-edge research programs and novel data approaches at the C.D. Howe Institute, the Conference Board of Canada and, most recently, at Canadian data tech company RIWI (Real-Time Interactive Worldwide Intelligence). These include the creation of high-frequency economic and geopolitical conflict data feeds. She has been an adviser to Statistics Canada, Global Affairs Canada  Canadian parliamentary committees, the deputy minister of trade and the Prime Minister’s Office.

Format

The masterclass format is a concise summary of 4-5 sessions delivered over a 3-hour period. Upon completion of the masterclass learning objectives, participants will receive a BEI certificate.

Proposed Agenda

TBD

To Register