This election season, Yellowknife became an unexpected hotbed of political discussion about civic engagement in government. We saw emotional remarks made at city council candidate forums, on social media, in the comments sections of online news articles, and among friends (who possibly turned into enemies).
At the centre of it all was IServeU, a new online direct democracy initiative that enables voters registered with the platform to guide how IServeU-endorsed city councillors vote on council motions—what can best be called an e-direct democracy.
While criticism was lobbed against IServeU regarding its funding sources, profitability, legality, accessibility, online security, and other possible shortcomings, those rather low-hanging fruit represent other, difficult-to-articulate, value-based concerns about how government should engage with residents, and about how people can and should have input into government decision-making.
Rather than debate the merits of IServeU, it is more productive to think about where to go from here, and how can we address people’s concerns about civic engagement so that ultimately Yellowknife’s city council—and other governments—can better incorporate a wider range of residents’ needs in a transparent and accountable way.
We can begin by addressing the question: “What is wrong with how Yellowknife residents and city government currently interact?”
The answer may be two-fold. First, there is a sense that input from an acceptably broad range of residents is inadequate and driven by limited avenues through which to meaningfully engage in City Council decision-making. Second, and a challenge not unique to Yellowknife’s City Council, there lacks a structure to guide decision-making that incorporates a range of stakeholders’ concerns and makes decisions in a transparent way with well-supported results. These two answers are, of course, linked: a process that effectively incorporates the concerns of a range of people may also address concerns about limited input.
Multiple forms of engagement
My intent is not to propose specific or ‘best’ forms of civic engagement, but rather to demonstrate how to improve any form of engagement. However, it is important to recognize that engagement exists on a continuum, and depends on the decision-making context and purpose. For example, is the decision-making process intended to reach a conclusion on a single option, or is it intended to arrive at a list of options? Will consensus be required? Which stakeholders will be making the final decision, and which ones will only be consulted or informed about progress? Answers to these questions help determine the level of detail needed and the resources (e.g., time, people) required.
Having few avenues for input—whether it’s through city council hearings or online forums—ultimately privileges one form of communication over others. Furthermore, people place different values on particular types of engagement and ways of communication; this point is not unfamiliar to anyone living and working in the Northwest Territories. Multiple forms of engagement help to ensure that a range of people can be involved in government decision-making. Moreover, this opens up avenues of engagement for residents who are unable to vote (e.g., new residents, non-citizens), but still have vested interests in where they live. Therefore, so-called civic technology like IServeU may be especially appealing to a certain demographic, and can be an effective way to engage otherwise uninterested voters. But this can—and should—work in parallel with other forms of civic input.
How to improve any type of civic engagement: Insights from decision science
Underlying any stakeholder engagement method is an assumption that people know what they want and can easily make the ‘best’ decision as long as they have the necessary information at hand. In this sense, people are thought to be ‘rational’; that is, fully informed about the context, with an ability to perform necessary calculations, to weigh conflicting values and make trade-offs, and to ultimately make decisions that maximize well-being.
But research from decision science—which encompasses a range of disciplines, including behavioural decision research, cognitive and social psychology, and behavioural economics—has shown that in most cases, people or groups of people struggle to make decisions that align with their goals and priorities. Instead, things like emotions, issue complexity, and past experiences affect our decision-making behaviour. This is especially true for decisions that have both short and long-term implications, involve hard-to-quantify values (e.g., traditional lands), and affect stakeholders with a range of potentially conflicting concerns.
To help us make difficult (and sometime not-so-difficult) decisions, we use a number of decision-making heuristics, or mental shortcuts. However, these shortcuts can also result in biases that hinder high-quality decision-making. The danger becomes decisions influenced not by a careful consideration of relevant information—including trade-offs across different priorities—but by heuristics that lead to a bias. Some of these heuristics and biases include anchoring, confirmation bias, representativeness, and groupthink (see the list of sources for more detail on these and others). These decision-making challenges are not unique to the “public”; even program managers, financial advisors, and elected officials are not immune.
Overcoming decision-making challenges
In terms of civic input and engagement, regardless of the method (whether it be online or in-person, for example), effective engagement requires structure to help us overcome our decision-making challenges. At the foundation of this structure is objectives-based decision-making, where we identify what we want to achieve and then work toward creating a way or ways to achieve it.
Let’s consider Yellowknife’s “50/50” lot (an unused parking lot owned by the City of Yellowknife). The initial step in a structured process is to clearly articulate the problem. In this case, a simple description might be that the City of Yellowknife owns a vacant lot and faces internal and external pressures to develop it.
By making clear the problem at hand, we can then move on to identifying objectives, or the things that matter to stakeholders, and reflect what they want to achieve. Identifying objectives should be an iterative, participatory, stakeholder-driven process so that objectives depict relevant concerns. Working toward common goals can help build a base of support, rather than polarizing or dividing people, and can help mitigate criticism once a decision is implemented. A series of structured engagement sessions with stakeholders might reveal a number of “big picture” objectives and smaller sub-objectives for the 50/50 lot, such as:
- Community: maximize opportunities for a public gathering place, for family activities, improve opportunities for youth, ensure year-round access, and ensure a safe space.
- Economy: increase employment, improve business development, minimize the cost to the government and taxpayers.
- Environment: minimize the environmental footprint.
- Culture: improve opportunities for arts, ensure space for events.
Note that these are not specific projects or activities, but instead address the purpose of the 50/50 lot development.
After a set of objectives has been identified, stakeholders can then create performance measurements for each objective as a way to tell if the objective has been achieved. For example, the objectives around Community (e.g., maximize opportunities for a public gathering place) might use simple low-medium-high measures as a first attempt; these can become increasingly complex moving forward, while the Economy sub-objective “increase employment” might use an estimate of the number of jobs created by a particular option (and may require input from economists).
The next step, then, is to develop ways or options to achieve the objectives. While typical engagement processes might ask the public (or specific stakeholders) for ideas via community meetings, hearings, workshops, open houses, or surveys, this type of brainstorming tends to be disconnected from any larger goals or objectives, is susceptible to decision-making heuristics and biases, and is therefore potentially inefficient and ineffective. Instead, options should be built with an eye toward achieving the objectives. For the 50/50 lot there might be a variety of options for a multi-use space (e.g., with different amounts of indoor space, of parking, with or without a library, with or without mall access, etc.). Existing options or plans may also be on the table for consideration (e.g., a parking lot, a library, or commercial space with housing).
Next, using the performance measures created earlier, we can estimate the performance of different options in terms of how well each one meets the objectives. In some cases this may require expert input, whereas in others an approximation is acceptable. While a winning option—one that best meets all the objectives—may emerge from this step, most often choosing the best option will involve confronting trade-offs. We can think of this as finding an acceptable balance across multiple objectives. To ultimately choose an option, it may be easy to eliminate options that are clear losers (those that do poorly on all of the sub-objectives), and to eliminate any sub-objectives that are met equally by all options. The objectives can be weighted, but there must be agreement about the weighted values. Beyond this, there are more complex methods to assess trade-offs across different objectives.
Once an option is chosen, it of course needs to not only be implemented, but also monitored, evaluated, and adapted as necessary. This can help test key assumptions (e.g., about the performance of certain options) and address uncertainties.
The process outlined here is based on structured decision-making, which has been used by NASA, Industry Canada, BC Hydro, United States Fish and Wildlife Service, Michigan State University, and in a variety of multi-stakeholder decision-making processes in Canada, the U.S., Vietnam, Tanzania, and elsewhere.
Improving existing decision-making processes
Most decision-making processes stop short of assessing how well different options perform. Instead, elected officials or the public might be asked to simply vote ‘yes’ or ‘no’ on a single option, or to rank or rate options without an idea of how well they meet different objectives. This means that people have to rely on gut instinct or best guesses, which can be influenced by how information is presented (including things as minute as the order of options, even if it’s random, or the colours used), or by how options are framed (a simple example of this is 90 per cent fat free vs. 10 per cent fat yogurt). We see the results of decision-making without guidance nearly everyday: in stalled decisions, plans, or projects with little support (and a lot of criticism), and initiatives that quickly—and often very publicly—fail.
Structures can be built into different types of engagement and decision-making processes to help us overcome our decision-making limitations. For example, and as Yellowknife City Councillor Rebecca Alty mentioned during a candidates’ forum, a matrix can help both councillors and the public evaluate potential options based on how well they meet the objectives. A more complex, computer-based version would enable people to manipulate different aspects of a plan or project (like building size and location), and then show how the objectives are affected (for example, the number of jobs created, revenue generated, greenhouse gas emissions) under different conditions.
I realize this all might seem rather clinical, calculated, and overly simplistic. In reality, transitions between these steps in a decision-making process require iteration, deliberation, recognition of financial and time constraints, and will necessarily involve—and potentially threaten—people’s values. I also realize it comes across as though people blindly plod through life, unable to make good decisions. Clearly, we’re able to get by fine most of the time. But complex decisions require more consideration than deciding which movie to watch.
Many issues put before government are simple and straightforward, but many are not, if only because they involve a variety of stakeholders with a variety of values and concerns. Breaking down the process into stages helps make decisions more approachable, and—importantly—less susceptible to decision-making biases. Incorporating deliberation from stakeholders provides opportunities for learning, the exchange of ideas, experiences and values, and buy-in and support for the final decision.
Thirst for alternatives
The interest in IServeU reflects desires for alternative ways to interact with government. While IServeU presented Yellowknife residents with one possible option for civic input, we do not have to stop there. At minimum, an effective civic engagement method should allow for a range of stakeholders, have space for deliberation, learning and collaboration, focus on the objectives, and select options based on their projected performance. Enterprising individuals could even use the steps outlined here to identify the most effective engagement method, themselves!
Changing how government interacts with the public requires willingness from councillors, city administration, and residents. Yellowknife’s municipal election seemed to indicate that people are interested in exploring new ways of engagement. But also, councillors are listening: many have increasingly turned to social media to communicate with residents, in addition to regular constituent meetings. To share its budget information, the City of Yellowknife is using principles of “open government”, which aim to make government data more transparent and accessible with the intent of improving accountability. We can look toward some examples from other cities too: Austin, Minneapolis, New York and others have websites where residents can provide input, discuss issues, and ask questions about local government. Cities across the globe are beginning to use participatory budgeting, which involves stakeholders—including the public—in an objectives-based budgeting process, and where spending decisions are based on effectively meeting people’s priorities.
Decision-making is not easy. The mayor, city councillors, administration, and residents work hard to make Yellowknife a great place to live, and all want to interact in a meaningful way. At the core of this discussion are fundamental, value-based questions about the role of government, and how to balance being responsive to residents’ needs and concerns with making sound, informed decisions. A starting point would be to add elements of structure to existing paths of engagement to enable more productive and effective discussions.◉
Disclaimer: Author was involved with Councillor Shauna Morgan’s campaign for City Council. These views do not reflect those of her employer or any of her co-authors.
Photo credit: iStock.com/RyersonClark
Sources and further reading
Ariely, D. 2009. Predictably Irrational: The Hidden Forces That Shape Our Decisions.
Dryzek, J. S. 2000. Deliberative Democracy And Beyond: Liberals, Critics, Contestations.
Gregory, R., L. Failing, M. Harstone, G. Long, T. McDaniels & D. Ohlson. 2012. Structured Decision Making: A Practical Guide To Environmental Management Choices.
Hammond, J. S., R. L. Keeney & H. Raiffa. 2002. Smart Choices: A Practical Guide To Making Better Decisions.
Kahneman, D. 2011. Thinking Fast and Slow.
Kahneman, D., P. Slovic & A. Tversky. 1982. Judgment Under Uncertainty: Heuristics and Biases.
Michel-Kerjan, E. & P. Slovic. 2010. The Irrational Economist: Making Decisions In a Dangerous World.
Schwartz, B. 2004. The Paradox Of Choice: Why Less Is More.
Sunstein, C. R. & R. Hastie. 2014. Wiser: Getting Beyond Groupthink To Make Groups Smarter.
Thaler, R. H. & C. R. Sunstein. 2008. Nudge: Improving Decisions About Health, Wealth, And Happiness.
Arvai, J. L., R. Gregory & T. McDaniels. 2001. Testing a structured decision approach: Value-focused thinking for deliberative risk communication. Risk Analysis, 21, 1065-1076.
Arvai, J. & K. Post. 2012. Risk management in a developing country context: Improving decisions about point‐of‐use water treatment among the rural poor in Africa. Risk Analysis, 32, 67-80.
Bessette, D. L., V. Campbell‐Arvai & J. Arvai (2015) Expanding the Reach of Participatory Risk Management: Testing an Online Decision‐Aiding Framework for Informing Internally Consistent Choices. Risk Analysis. Online.
Hammond, J. S., R. L. Keeney & H. Raiffa. 1998. The hidden traps in decision making. Harvard Business Review, 76, 47-58.
Kassam, K. S. 2015. Emotion and decision making. Annu. Rev. Psychol, 66, 33.1-33.25.
Kahneman, D. & A. Tversky. 1979. Prospect theory: An analysis of decision under risk. Econometrica: Journal of the Econometric Society, 263-291.
Kenney, L., Bessette, D., & Arvai, J. 2015. Structuring decisions about energy in developing communities: An example from Canada’s north. Journal of Environmental Planning and Management, 58(5), 855-873.
Kenney, L., Arvai, J., Vardhan, M., & Catacutan, D. 2015. Bringing stakeholder values into climate risk management prrograms: Decision aiding for REDD in Vietnam. Society & Natural Resources, 28(3), 261-279.
Slovic, P., M. L. Finucane, E. Peters & D. G. MacGregor. 2007. The affect heuristic. European Journal of Operational Research, 177, 1333-1352.
Tversky, A. & D. Kahneman. 1973. Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5, 207-232.