What's up with tax increment financing (TIF) in Canada

Tax increment financing, where governments borrow against future property tax revenue to front the cost of infrastructural improvement within designated areas or on designated properties, has dominated U.S. economic development and found footing in Canada. A brief survey of its prevalence in the latter revealed what seems to be a mix of enthusiasm and uncertainty, as expected with an instrument proven controversial for its risks/rewards.

I brought this up in my Introduction to Planning class in a discussion on decentralization and the city government's role in economic development as the global-local pivot. What the dilemma of TIFs really comes down to is uncertainty - about whether development would've occurred in their absence, whether projected growth would materialize into enough funds to pay off the money borrowed, whether the public benefits would be equitably distributed within the neighborhood and the whole city or even beyond, whether the foregone revenues from overlapping jurisdictions would have long-term repercussions, whether rent-seeking agenda would sneak into the complex design and lodge itself through their implementation... And whenever there is uncertainty, power dictates the narratives - the ones most cited by TIF supporters being 1) "there's no harm done" - brownfields that yield little revenue unless injected with a dose of investment and 2) "it's good for everyone" - that the investment, paid for by new revenues that would not have existed otherwise, results in better infrastructure for the city. These aren't exactly false, if assuming too much; what gets left out is how extreme TIF is and that there may be more balanced alternatives.

Perhaps it is this controversial U.S. legacy that explains the apparent hesitation in its adoption in Canada. Ontario passed its Tax Increment Financing Act in 2006, enabling municipalities to create TIF districts, apply for provincial grant that match the projected tax increments, and use the funds to support businesses within the designated districts that would otherwise be prohibited. How it works--as best as I can tell--is that a city identifies (presumably contiguous) parcels suitable for redevelopment, remediation, and/or public transit, submits a feasibility study--by itself, through a business subsidiary, or with neighboring cities if applicable, gets approved for a grant from the province, establishes the district, freezes property valuation in that district at a baseline, diverts all tax increments (increases above the baseline from the development in question) into a special fund, uses that fund and payouts from the province to foot the bills. It isn't clear how the grant is calculated--presumably in the amount equal to the projected tax increments given the maximum cap at that amount and lack of specification with regard to the recipient (province or city) of the educational property tax in question. Districts are limited in size and scope--the municipal tax increment in a given year cannot exeed 1% of all municipal property taxes. There is room for governor's discretion to approve ineligible projects that are deemed to have substantial public benefit that cannot occur but for the provincial TIF grant.

Manitoba soon followed suit in 2009 with its Community Revitalization and Tax Increment Financing Act that subsequently enabled the creation of the "Sports, Hospitality, and Entertainment District (SHED) in downtown Winnipeg through the 2002 City Charter section 222. The approach was top-down in that the province designates a property and meet with the affected municipal and school boards and very much growth-oriented in that only the probability of project success and public benefit is considered, not funding availability. There are assessment and levy provisions separately for the designated property and surrounding properties. Once a designation is made, assessed value is frozen; for any subsequent increases or "increments", in lieu of school taxes, property owners pay toward a "community revitalization levy," which is then remitted back to the province to go into a Community Revitalization Fund to be paid out to the property owner(s), occupant(s), the city, and/or entities making supported investments in the neighborhood--to offset any costs they bore for redevelopment, whether it's from increased valuation from making improvements--not unlike the "pay-as-you-go" arrangement in many U.S. TIFs--or decreased valuation from creating affordable housing units--not unlike Ontario's use of Tax Increment Equivalent Grant. (I got exhausted just typing that last sentence..)

In 2018, Manitoba introduced a new framework to make TIFs more transparent, accountable, and collaborative (see above) so they don't become a runaway public risk or burden. Reforms include more representative decision-making, delayed payouts, and more stringent evaluation criteria, including but-for tests, which seems to have gone into effect, according this policy adopted by the Winniopeg City Council in 2022. Within hours of the announcement, the Canadian Taxpayers Federation responded with its rejection and criticism against the new framework as part of its stance against TIFs in general, citing the failure of development projects that Manitoban taxpayers had to pay for. At this point in time, Winnipeg officials were already doubting whether their city was all set on TIFs, according this CBC News analysis, and "whether Winnipeg has already mortgaged too much of its future to pay for projects now" and possibly trading long-term sustainability and resilience for relatively short-term gains that make sense to pursue for election cycles.

Ontario wasn't Canada's TIF pioneer: Alberta first created the Community Revitalization Levy through the Municipal Government Act in 2005 that was later suspended in 2014 pending a thorough review of its impact on the redistribution of educational property taxes and resumed in 2022 with a number of transparency and accountability reforms. So far there are six TIF districts throughout the province--the earliest to begin (in 2008) and last to conclude (in 2047) being the redevelopment of Calgary Rivers District through its business subsidiary, the Calgary Municipal Land Corporation. The approval process, public involvement, and fiscal impact for this and the Edmonton districts were called into question in a 2019 paper by researchers with the School of Public Policy at the University of Calgary. These districts, along with Toronto's SmartTrack proposal and Winnepeg's SHED, are definitely worth keeping an eye, as Canadian governments continue the TIF experiment.

Teaching cities and city planning

It is a great honor to be entrusted with the responsibility of teaching 300+ undergraduate students this semester across two courses/departments at the University of Calgary -- one for geography on the evolution of cities through our past and the other for planning on building better cities for our future. This post will be short as I am quite busy every day prepping and refining my course content and delivery, in addition to writing papers.

It's hard to believe that we are only two weeks in. So much has happened. From the first small self-contained cities of five thousand years ago to the massive mechanized cities and sprawling suburbs that are our reality today--we experienced through reading the vicissitudes in the delicate balance between peoples and resources as well as the dramatic rise and fall of urbanized empires, which are really the cumulative result of daily mismanagement that went unnoticed or neglected. (I often stress, nothing big just happens without a bunch of small things adding up.) We witnessed how external fixes to resource crises--that is, attempting to repair the balance through expansion and acquisition of new resources, often involving dispossession of the more defenseless--tend to be unsustainable. We explored better solutions by unpacking the sociospatial configuration of cities.

While it's great fun getting lost in the fascinating details of the past urban forms and functions--pockets of civilization in Mesopotamia, Mesoamerica, Indus Valley, Egypt, and Northern China, Greek city-states, Roman empire's defensive outposts, Medieval hubs, mercantilist trading centers, burgeoning steam-powered metropolis, factory towns, planned suburbs, we also must ground ourselves in the continuities and generalizable characteristics of urbanism as well as disruptions in the form of new institutions (such as the private ownership of the means of production that gave rise to cottage industries). We also keep track of the theories that people all over have come up with to explain and understand urban phenomena--thus linking documented experience with epistemology.

Over on the planning side, similarly, we familiarized ourselves with the many plans of Calgary and its surrounding region (it's nice to see some degree of intermunicipal coordination), teasing out its various elements--visions and goals down to strategies and actions--and matching them to theoretical justifications and experimental results. Inspired by how the City Reader opens with the study of cities, I opened with the education of planners through accredited professional degrees and why certain coursework is required, so that we understand the problems, objectives, stakes, and planners' roles and powers. We examine not only theories in planning that inform our policy recommendations and theories of planning that guide implementation but also theories about planning that illuminate the paths and obstacles ahead. We look at the broader geopolitical and socioeconomic configurations that circumscribe the purview and possibility space for local planners and identify less-understood or -researched areas in the Canadian context.

Words cannot adequately describe the fulfillment I get from teaching urban studies and city planning and my gratitude for the opportunity to do it. I am learning so much each and every day, and I hope my students are too, and are having fun at the same time.

AI in urban planning - and in planning education in particular

The American Planning Association (APA) in 2021 established the “AI in Planning” Foresight Community which, over ten months, surveyed and interrogated and analyzed and contemplated/deliberated upon the unfolding relationship between advances in artificial intelligence (AI) such as machine learning and the planning profession (this report tells you all you need to know for now - the technical details, big-picture developments, and ethical debates/dilemmas). This blog covers the core conversations and contributes my views on AI in planning education from the perspectives of both teacher and learner.

The AI project in planning seeks to harness the computer’s overwhelming power in gathering and processing data input, including that on its own performance, extracting patterns, and performing calculations through digital replication of the planning logic. The prevailing understanding and consensus appear to be that 1) the technology will out-consume and out-power any resistance in its redefining the field much in the same nature as, only even more comprehensively than, geographical information systems (GIS) a few decades ago, and 2) its responsible use requires that planners learn its inner workings and, when applicable or appropriate, utilize its capabilities to make decisions and model projections for human settlements and communicate its operations to the affected communities. The creation by APA of its team of experts reflects the recognition that if planners are unprepared, they could either miss out on all the answers and solutions or misuse its output. Right now, the outlook is that technological advancement, largely in the private sector, will vastly outpace its adaptation for policy and planning in the public sector and scrutiny of its capability to do so effectively by universities and nonprofits.

The current disconnects hampering the effective use of AI by planners across all domains as identified by the academic experts through a combination of meta studies and case studies can be pinpointed at these particular loci of “dissonance”:

1) between any of a planner’s desire/will (what problem am I trying to solve), comfort/capacity (how well can I use the tool at hand), and awareness/comprehension (how appropriate is the tool to the purpose, and what is its limitation): until planners can unequivocally define exactly the procedures, goals, and core values motivating all decisions and choices in their scope of practice, AI will always remain an unstable concoction of uncertainty and powerful potential for mishap/mischief.

2)  between private sector priorities, which shape the technology’s development and deployment, and public sector imperatives, which form the bottom line of re-distributive justice and co-existential compact.

3) between the respective timescales of innovation, financing/entrepreneurship institutional building and capital/labor routing, and knowledge production on its methodological possibilities and ethical implications across the various spaces or sectors – academic, nonprofit, governmental, corporate, tribal etc.

4) between the respective cognitive spaces of planners and their communities – be they settlements, workspaces, classrooms, or legislatives.

In essence, moving forward requires bridging the perception-understanding gaps around any social spaces where AI is relevant or a potentially advisable/preferable direction and taking assessment of what we know and don’t know about what we will and won’t do.

I’ve delighted in reading the cases of AI’s pilot for solving long-standing problems over humane and just resource allocation. I await large-scale, replicable studies of its effectiveness as a governance tool in all spheres of social existence. And we are all part of a nascent experiment with a hitherto unknown set of circumstances – namely, an epistemological transformation superimposed on various inherited structural dysfunctions…

- one of which being deficiencies in our teaching and instruction of the fundamentals of math and computing and philosophy and reasoning. That our entire education system in the country and parts beyond requires an overhaul is besides the point, but the only limit to perfecting planning educational programs’ purpose for preparing AI-knowledgeable prospective planners is lack of political will to overcome/disrupt institutional rigidity or inertia. What I’m trying to say, we have the individual and institutional capacity in our existing systems for producing things – knowledge included – to implement the leading recommendations, just that outdated thinking needs to move out of the way.

As a new teacher of urban planning, I have been fiercely outspoken against the use of AI in any kind of instructional settings where learning – as in gaining true comprehension – is the primary goal. A machine designed by humans for computing – in the broadest possible sense of the term – human-generated data (even nature measurements are only meaningful to the extent humans deem it worthwhile to measure) can confirm the established conceptions or replicate/augment human actions/calculations or justify chosen recourses or predict forthcoming occurrences based on known likelihoods - that it can do so is meaningless or irrelevant for gaining deeper awareness of our worldly and outer-worldly relations.

In other words, it has no place in the learning process other than summarizing a ridiculous amount of data that no known biological organism can consciously do according to the metrics we have agreed on. For this reason, I find entertaining any notion of incorporating AI in the classroom of planning education utterly risky as human minds, young and old, are far too impressionable, and for good evolutionary reason, to be trusted with ex-poste knowledge reconstruction. (Besides, making predictions based on statistical/probabilistic models and then retracing the logic in the models makes learning like chasing one's tail, only much less fun). My advice for students at all stages of life is: don’t let AI deprive you of the opportunity to make the connection yourself; you can always ask it afterwards.

The implication from that last statement is that there’s no theoretical gap between a thinking thing made up of metallic or organic matter or whatever combination of substances. That our machines will produce ever closer approximations and eventually replicate human intuition and ingenuity and imagination is not a question but an inevitability. Good news is that we are always moving toward convergence or some sort of new equilibrium following any kind of disruptive cognitive/technological advances; the challenge is minimizing the damage on the way -- that our experimentation with various AI projects don’t cause unnecessary harm or suffering. Students who mistake AI for an aid to learning beyond simple fact-finding and pattern-summarizing simply have not noticed the delight of true learning. The goal for us educators in the classroom is to recall, reproduce, and reinforce those fleeting joyful moments of epiphany and revelation – like that one when you first discovered negative numbers as a child, of learning through love and human connection, and thereby put AI in its rightful place of serving simply as an efficient, aided self-correcting gyroscopic calculator, to be used only by those properly trained.

Googling “AI planning.org” will return all the current AI endeavors in urban planning – the first few results being  the newest publications on the current state of knowledge and application and deliberation, each providing links and citations to useful resources.