I attended a panel discussion on Smarter Cities last night. It was an interesting mix of panelists from the university, although lacking representation of private companies and the public sector.
Topics included financial responsibility of developing smart and sustainable neighbourhoods, creative development design (to the sky and in the ground rather than spreading out), collaboration across sectors and municipalities, equitable development for all demographics and the idea of global villages (which was incredibly fascinating and I will need to talk about in a different post).
The quick talks were interesting but the discussion that followed was the event’s highlight. I’m going to focus on two topics: data-based planning and government limitations.
One conversation was around data driven cities. There was disagreement between data-first and people-first development. To my understanding, one opinion was that cities should not develop without hard evidence of potential success and that our planning policies should originate from as much data as we can gather. This correlated with idea that people need to be told what they want, where decision makers must look data and explain to the public what’s good and what isn’t. The opposing view (from the mathematician on the panel) was that city planning should be spearheaded by how people use them – which might often seem illogical and counter to what data suggests. Existing quantitative data is limited by big-picture social issues and often excludes disadvantaged demographics. It is also easy to get caught up with the facts for too much precision; people are attracted to chaos as much as they to order, and there needs to be space for some natural messy urbanism. However, planning based on subjective opinions alone is also frivolous, since human bias can steer development in structureless, confusing directions. In my eyes, the happy medium lies in human-driven and data-supported solutions. Cities need to be worked on bottom-up: instead of throwing data and technology at a city and hoping it works, data products need to be tailored to the city’s specific issues through extensive consultation.
Another recurring theme was the role of the government in building/managing these smart cities. The panel’s disappointment in the risk aversion and lack of innovation in all levels of the government was blatant. The moderator went so far as to say that most of the audience’s young people will not end up working for the government because of creative limitations. Unfortunately, public service workers were not on the panel, but an audience member challenged the panel by explaining he works for the provincial government and works on plenty of innovative and creative projects, regardless of how slow they move. Another (among the many) critique of the government was that it incentivizes competition rather than collaboration, and shuns failure. Instead of Toronto working with other cities, individual cities work separately and often in competition with each other to make the ranks of important lists. To worsen matters, the risk aversion is so strong that cities are afraid to innovate and fail. The finest example of this is Toronto’s notorious pilot projects. Everything must be an extensively studied pilot project before rolling out the ‘real thing’.
All in all, it was an interesting event that sparked substantial conversation. My only disappointment was that it ended too soon and that these conversations will be, as usual, continued with other people and likely not lead to much action.
(n) urban-dweller
(n) urban-dweller