Much of decision-making psychology (and by extension behavioural economics) explores the processes by which people solve a problem or achieve a goal. Usually the papers in this field contrast the rational, expected-utility way to solve these problems with the approaches people actually use in practice.
An important question they rarely address is “Why that goal?” How is it that people choose the particular problem they want to solve, the objective to work towards? In the psychology lab, the answer is easy: the person in a white coat gives it to them. In real life, that doesn’t happen.
Answering this question is essential to developing a comprehensive theory to replace or challenge classical economics. Standard microeconomic theory has a clear, simple answer to this: we always have the same goal, maximising utility. Any other objective (finding the best job, working out how much money to save, picking what to eat, choosing a romantic partner, deciding whether to rob a convenience store – to pick at random from the typical subjects of economics papers) is a means to an end. According to the classical theorist, we choose between these different goals based on which we think will bring the highest marginal utility. Independent goals which don’t conflict with each other are pursued more-or-less simultaneously: I seek a promotion at work during the day while trying to find the ideal spouse at night, choose the best mutual fund at lunchtime and weigh up the risk and reward of the convenience store holdup before bed.
Psychologists, while rightly challenging the claim that I can simultaneously optimise across all these different life goals, don’t propose an alternative way to choose between them. My conscious problem-solving mind can only focus properly on one objective at a time, but which one?
The fast-and-frugal heuristics school gives an argument that simple heuristics are the best way to solve apparently complex problems like catching a baseball, allocating investment money or walking through a crowd, but doesn’t tell me why I want to catch the baseball or invest money in the first place. The heuristics and biases approach tells me that I am anchored on a particular rate of return for my investments but not whether I will spend this afternoon trying to beat that rate or watching football.
You could easily ignore this question and assert that sooner or later I’ll get round to dealing with most of the important problems in life, and that the real work of psychology should be focused on how I’ll tackle them. But there are plenty of counterexamples. Many people never get around to thinking about investments or savings, or not until it’s too late to do anything meaningful about them. Our success in achieving health objectives is strongly influenced by what we spend our time thinking about – unconscious eating and conscious exercise are in conflict. Status quo bias in the labour market and in consumption patterns is responsible for lots of apparently suboptimal behaviour and there’s a strong argument that the cause is a (possibly rational) lack of attention to the goal.
Here is a candidate theory of how we select our goals.
I draw inspiration from a Glöckner and Betsch paper, Modeling option and strategy choices with connectionist networks. Although this paper is within the narrow paradigm I’m critiquing – how do people solve a problem that is exogenously given to them – it contains a model we can borrow to address the broader problem. They propose that the mind answers questions by collecting data and using it to populate a network of nodes representing a model of the problem it is working on. It tests how self-consistent this model is, and if it is highly consistent it is more likely to consider the problem solved. If it is not consistent (e.g. two different answers to the question can still be true within the mental model) the mind seeks out more information to try to increase consistency. As they say:
“One of the basic ideas of Gestalt psychology (e.g., Köhler, 1947) is that the cognitive system tends automatically to minimize inconsistency between given piece of information in order to make sense of the world and to form consistent mental representations”
The unconscious (automatic) mind determines that there are two or more inconsistent ideas simultaneously held, and prompts the conscious (deliberative) systems to gather more information with which to populate the model, in order to try to resolve the conflict between them. This process continues until the mental model reaches a certain level of consistency – in effect, when it stops changing and reaches a stable representation. This representation is taken as the answer to the question.
In a very different context, John Yorke writes:
“The facts change to fit the shape, hoping to capture a greater truth than the randomness of reality can provide.”
I propose that the mind relies on a similar connectionist, associative network to choose which goals to focus on.
This network represents the actions that the decision maker could take, the consequences of those actions, and the reward that would accompany those outcomes. In any situation a person could take thousands of potential actions with tens of thousands of consequences, and it is unlikely the mind (even the highly parallel automatic system) can simultaneously evaluate all of them. Instead, a small subset of those potential actions and outcomes will be activated by sensory stimuli or familiarity: nodes representing regular, repeated actions are likely to remain active much of the time; nodes representing outcomes such as the satisfaction of hunger may be activated by biological need, and other less frequent actions or consequences may be activated by seeing or hearing messages which remind us of them.
Activation automatically spreads from node to node in this network. The network’s connections link actions to their consequences – the action of eating food links to satisfaction of hunger; saving money is linked to a higher bank balance, which in turn links to an emotional payoff from feeling secure; smoking a cigarette links to the quieting of cravings and a feeling of relief. Thus, when an action is activated a consequence will become active; and vice versa, when an outcome is activated the actions which could lead to it will also become active. If only one action-node is activated, the decision maker will take that action. If only one outcome-node is active, the decision maker will choose to pursue that outcome. At this point a goal has been set, and the well-studied processes of decision making will take over.
If nodes representing more than one potential action or outcome have been activated, the automatic system needs to keep working, until it can resolve which one to pursue. This work includes the further spreading of activation to other nodes in the network (the food-eating node could activate nodes that represent spending money and gaining weight, the hunger-satisfaction node could activate alternative actions that lead to the same outcome) which in turn may connect back to some of the same nodes, increasing their activation further. The network might “test out” particular outcomes by activating nodes that represent their second-order consequences. The activation is diluted by this point; the earlier nodes were strongly activated; these ones are weaker.
At this point a similar kind of consistency-testing to that proposed by Glöckner and Betsch comes into play. The activated, imagined actions and outcomes are tested against sensory input and knowledge about the outside world. Are these outcomes plausible? Can I actually take these actions? Are they consistent with what I believe about how the world works? If so, the activation, and the relationship between actions and outcomes, is reinforced. If not, the activation is reduced and the network keeps looking for a consistent, stable, combination of action and outcome.
Eventually, that stable set of active nodes will emerge; or perhaps two or three combinations will continue to compete for attention and plausibility. If so, again following the template of Glöckner and Betsch, the deliberative system comes into play and selects between them. The deliberative mind applies symbolic, logical or linguistic forms of reasoning and decision making instead of the connectionist, activation-driven process of the automatic mind. These symbolic processes (and the biases that can affect them) are the stuff of most decision theory, and I defer to the accumulated body of science to tell us how they work. My claim here is only about the automatic process that selects the options between which we deliberate.
The outcome emerging from this process becomes the goal we consciously seek. It will be paired with an initial action, though that action alone may not be enough to achieve the goal, in which case a planning process of some kind has to take place – again, thoroughly explored by existing decision theory.
This model tells us something about why certain goals or actions might be preferred to others. If an action is particularly salient or easy to imagine, we are more likely to focus on the outcomes that follow naturally from it. If an outcome is particularly consistent with our mental model of the world, we are more likely to take the actions that will cause that outcome. The availability heuristic, effects related to salience and attention, and confirmation bias are all natural outcomes of this emergent-goal process. For now it is a theoretical model, but it is not too hard to imagine empirical tests for it.
Of course, the outcome you choose should not only be consistent with your view of the world, but also be a rewarding one. I agree with both the classical economist and the behaviourist that reward drives us to choose outcomes, and therefore the actions that lead to them. But we clearly do not apply probabilistic, utilitarian calculations to estimate and respond to that anticipated reward, and simple behavioural conditioning is not enough to explain the rich, complex actions and plans we make. In the next post in this series I will suggest a more plausible way to think about reward, how it motivates us to act, and what this means for how we experience life.