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Ainslee Beer is a Master of Public Policy candidate at the University of Toronto School of Public Policy and Governance, and is a Junior Fellow at Massey College; Marc Desormeaux hold a Masters degree in Economics from the University of Toronto, and is a Junior Fellow at Massey College.
We live in the Age of Information. The question is: How much of it is good information? And while no doubt more data exist than ever before on how people act and make decisions, does it mean we've entered a new, sunny era of evidence-based policy making? The answer is: Not quite. And maybe even: Not at all.
And in that vagueness and muddle of contradictory numbers, the victim is trust, the public's trust in political decision-making, which is the essence not only of our democracy but of the cohesiveness of our Canadian society.
We will take as an example Keystone XL (KXL), the 1,897-kilometre-long pipeline that, if built, would carry crude oil from Hardisty, Alta., to Steele City, Nebraska. It provides a perfect illustration of the advantages and pitfalls of data in today's policy making process.
What people are looking for in data is to tell them is how to balance the project's economic benefits against the damages its operation and construction might cause to the environment. The economic impact of the pipeline is, to say the least, a matter of debate.
Keystone XL's economic benefits are usually expressed in the form of new jobs being created in the United States and Canada. However, the precise number of jobs projected varies greatly. TransCanada, the builder of the proposed pipeline, at one point claimed the project would create "20,000 new jobs," which they calculated using the estimated expenditures associated with the pipeline. Meanwhile the U.S. State Department has most recently estimated that while the project could support more than 42,000 direct and indirect jobs during construction, it would create only 35 permanent positions after completion.
How does the public judge?
Environmental analyses project similarly varied numbers. KXL's potential environmental impacts fall into two main categories: oil spills and increases in carbon emissions. While environmental organizations are certain the pipeline would wreak havoc in both areas, the U.S. State Department's Environmental Impact Statement has concluded the pipeline met all environmental standards.
Again, how does the public judge? This brings us back to complexity, decision-making and, above all, trust in decision-makers.
Our objective here is not to debate the exact number of jobs Keystone XL will or will not create, or to quantify environmental damages. It is to highlight the way data can be tailored to the message a particular group wants to propagate.
All of the data used as inputs were run through regularly used economic estimation models. However, many of the "jobs" may in fact be temporary construction positions that would only last a matter of months. The economic models may not account for the changes in oil prices that would likely result from the increased volume of oil being transported into the U.S.
With varying data available from an ever-increasing number of sources, politicians and interest groups of all stripes have the ability to choose the data that best suits them. And the data being used does not necessarily take the entire picture into consideration. It can be selectively chosen to further a political agenda.
So, what does this mean for the public? If Canadians are constantly being presented with contradictory information, all based on supposedly reliably measured data, how are individuals supposed to form concrete and informed opinions?
Of course, we cannot expect politicians and interest groups to align themselves entirely with the evidence; there will always be some discord between political communications and the scientific process. But to effectively design policy for the future, we need two things.
First, the data we use must tell the truth. Being able to quantify economic effects is invaluable for informed policy decisions, but any projection made is only as good as the data used. In the case of KXL, entering temporary positions as "jobs" – no matter how short in duration – may not reflect how much economic value is actually being created for workers.
Second, we need to be constantly recalibrating existing economic and environmental estimation tools and developing new ones. Many of the economic impact models used for the estimates above do not account for factors such as oil price changes. No economic model is perfect, but we do need constant re-tooling and rethinking of the ways in which we assess impacts as our economy evolves.
Big data and the proliferation of information bring with them both pros and cons. There may be more information than ever before, but there is also more noise to sift through and as such, more opportunity for the data to cloud the truth where it should be unveiling it. Effective evidence-based policymaking in the coming decades will require that governments not just use the mass of data available in the ways they always have, but also to develop new models and engage and inform the public in the process.
This article is part of a Globe and Mail series on the role of Canadian institutions in partnership with The Walter Gordon Symposium – a two-day public policy conference March 25-26 co-hosted by the University of Toronto's School of Public Policy and Governance and Massey College.
This year's symposium, titled Confronting Complexity: Better Ways Of Addressing Our Toughest Policy Problems, will explore how the media, private sector, governments, and supranational organizations factor into the policymaking process in our increasingly complex and changing society.