If our reasoning were biased, then we’d notice it, right? Not quite. We are conscious of very few (if any) of the processes that influence our reasoning. So, some processes bias our reasoning in ways that we do not always endorse. This is sometimes referred to as implicit bias. In this post, I’ll talk about the theory behind our implicit biases and mention a couple surprising findings.
The literature on implicit bias is vast (and steadily growing). So there’s no way I can review it all here. To find even more research on implicit bias, see the next two posts, the links in this series, and the links in the comments.†Continue reading Implicit Bias | Part 2: What is implicit bias?
The research on bias is kind of scary. It not only suggests that we are biased;Â It suggests that we are unaware of many of our biases. Further, it suggests that trying to suppress our biases can easily backfire. So, despite our best efforts, we could be doing harm. And yeah: that might provoke a bit of anxiety. That’ll be the topic of this post.
In future posts, I’ll talk about the theory behind our biases [Part 2], how bias impacts the workplace [Part 3], a dozen debiasing strategies from the research [Part 4], and a few tips for giving (and receiving) feedback about our biases [Part 5].
Related post: The Bias Fallacy (what it is and how to avoid it).
University faculty might face a dilemma. On the one hand, productivity is required for faculty to keep their job, be promoted, and — for tenure track faculty — secure tenure. And one way to survive in the competitive academic market is to outshine the competition in terms of productivity. And one way to be more productive than the competition is to overwork yourself. After all, overworking is associated with greater productivity (Jacobs and Winslow 2004; see also Seals and Rodriguez 2006 and Thomas 1992). However, overworking is also associated with lower job dissatisfaction (ibid). So, overworking
Being in the hands of a master magician can leave you feeling a bit uneasy. When the magician finishes a trick, you face a jarring disjunction: either your view of the world is deeply mistaken or you’ve failed to understand what happened during the trick. But you’ve no idea what you failed to understand about the trick, so it seems as though the world is not what you think it is.
In this post, I want to argue that something similar can happen when one studies philosophy or science. To explain what I mean, let me offer some context. Continue reading Philosophy, Science, and Magic
Welcome to the 171st edition of the Philosophers’ Carnival. Thanks to all those who submitted, to everyone who is reading, and to Tristan Haze for his support. Here we go!
Projects
Conceptual Geneology For Analytic Philosophy. Catarina Dutilh Novaes offers a series of four posts in which she defends a “historicist conception of philosophical concepts.” There are helpful links to the literature and to the other posts in the series in this final post.
Degrees of Justification. Luis Rosa begins exploring the claim that degrees of justification will not be satisfactorily captured by probabilities.
Human Errors and My Errata. Anne Jaap Jacobson has written four posts over at The Brains Blog. The overall project: “My intention in planning these four posts was to close on a kind of contribution very developed in feminist thought.  The contribution has concerned how we account for human cognitive successes when we are actually rather error-prone creatures.  The very general approach is to give up a kind of Cartesian picture of the mind.  What is instead emphasized is the extent to which our knowledge depends on our social interactions.” Continue reading Philosophers’ Carnival #171
Michael Bishop outlines a network theory of well-being in which well-being is constituted by positive causal networks and their fragments (2012, 2015). ‘Positive’ refers to — among other things — experiences that have positive hedonic tones, the affirmation or fulfilment of one’s values, and success in achieving goals. So according to Bishop’s view, we flourish when certain positive causal networks are robust and self-reinforcing. For example, something good happens to us and that improves our motivation and mood, which then helps us achieve more, which improves our motivation and mood even more, and so on.
Bishop’s network account musters philosophical rigor by providing a systematic and coherent account of wellbeing that satisfies many common sense judgments about well-being. But lots of philosophical accounts can do that. So Bishop’s account does even more. It unifies and makes sense of a huge swath of the science. This provides some reason to think that Bishop’s account is superior to its competition.
So what’s this got to do with exercise and neuroscience?
1. Neuroscience
I am largely persuaded by Bishop’s arguments for the network account of well-being, so I will skip my criticism of the project. Rather, I will add to it. Specifically, I will show how well is makes sense of the neuroscience. While I will not be able to review all of neuroscience, I can accomplish a more modest goal. I can review one part of neuroscience: the effect of exercise on the brain.
2. Exercise
There is a wealth of evidence suggesting that regular physical activity and exercise forms an important part of one’s positive causal network of well-being by, among other things, increasing positive affect (Harte, Eifert, and Smith 1995), increasing confidence (Klem, Wing, McGuire, Seagle, and Hill 1997), reducing stress, relieving depression (Blumenthal et al 1999; Motl et al 2005) and preventing more than a dozen chronic diseases (Booth, Gordon, Carlson and Hamilton 2000; see also Biddle, Fox and Boutcher 2000 for a review of relationships between exercise and well-being). The mechanisms for all of these results are not entirely clear. But neuroscience is providing, in broad strokes at least, some clues about the mechanisms that can explain, in part, why exercise produces a series of positive effects in a well-being network (e.g., Meeusen 1995, Farooqui 2014).
The Positive Effects in the Brain
Let’s start with how exercise produces direct positive effects in the brain. Firstly, exercise and regular physical activity directly improve the brain’s synaptic structure by improving potentiating synaptic strength (Cotman, Berchtold, Christie 2007). Secondly, exercise and regular physical activity strengthen systems that underlie neural plasticity—e.g., neurogenesis, the growth of new neural tissue (ibid., Praag et al 2014). These changes in the brain cause “growth factor cascades” which improve overall “brain health and function” (ibid.; Kramer and Erickson 2007).
Now consider how exercise has indirect positive effects in the brain by producing ancillary positive circumstances. Generally speaking, “exercise reduces peripheral risk factors for cognitive decline” by preventing—among other things—neurodegeneration, neurotrophic resistance, hypertension, and insulin resistance (ibid.; see also Mattson 2014). By preventing these threats to neural and cognitive health, exercise is, indirectly, promoting brain health and function.
Positive Causal Networks
It requires no stretch of the imagination to see how these positive effects will reinforce positive causal networks and thereby increase well-being. Even so, I will do you a favor by trying to demonstrate a connection between exercise, the brain, and the larger network of well-being.
We have already seen how exercise results in, among other things, increased plasticity. And increased plasticity results in improved learning (Geinisman 2000; Rampon and Tsien 2000). Also, the increased plasticity that results in improved learning can produce other positive outcomes: increased motivation, increased opportunities for personal relationships in learning environments, etc. (Zelazo and Carlson 2012, 358). Further, increased motivation and social capital can — coming full circle — result in further motivation (Wing and Jeffery 1999).
That right there is what we call a self-reinforcing positive causal network or positive feedback loop. And that, according to Bishop, is how we increase well-being (see figure 1).
Figure 1. Positive Causal Well-being Network. Exercise promotes outcomes in the brain that promote other positive outcomes outside the brain. Similarly, exercise reduces negatives outcomes that would reduce certain positive outcomes. This is adapted from causal network models found in Cotman, Berchtold, and Christie 2007.This causal model shows how the neuroscience we just discussed implies a causal network. The nodes and causal connections in this model show how well-being is a matter of positive causal networks.
3. What about Ill-being?
Obviously, I’ve only mentioned the neuroscience of well-being. But if we want to promote well-being, then we also have to decrease ill-being, right? Right. And once again, the network theory of well-being will fit nicely with the research on ill-being. For example, the research on emotion regulation (see Livingston et al 2015) implies some causal networks that can inhibit ill-being. The same can be said of the research about using deep brain stimulation in treatment-resistance depression (Bewernick et al 2010; Lozano et al 2008; Mayberg et al 2005; Neuner et al 2010).
4. A Concern: Fitness
You might object by positing that Bishop’s theory of well-being will not fit neuroscience as well as it fits positive psychology. This objection can be dismissed in a few ways. Here are two ways.
First, we can safely accept that Bishop’s network theory of well-being will not fit neuroscience as well as it fits positive psychology. After all, Bishop’s network theory was designed to fit positive psychology, not neuroscience. It’s hardly a fault for a theory to not do what is was not intended to do.
Second, neuroscience is a larger domain than positive psychology. So of course it is harder for a theory to fit it. Allow me to explain. As the domain of discourse increases in scope, it becomes increasingly difficult for us to find a theory that fits all of it. So, because neuroscience is a larger domain than positive psychology, the challenge of providing a theory that fits neuroscience is always more difficult than providing a theory that fits positive psychology. So the fitness objection doesn’t necessarily reflect badly on Bishop’s theory. It might only reflect a difference between positive psychology and neuroscience.
Conclusion
Let me summarize. I mentioned a few cases in which Bishop’s theory of well-being can unifies and makes sense of neuroscience. Then I proposed a few more cases in which Bishop’s theory might do the same. And then I addressed a skeptical worry about the project I propose. So Bishop’s theory of well-being can accomplish even more than Bishop intended.
This is a revised version of an old post about a problem with appealing to intuitions. Many of the original premises were overcomplicated and controversial — and, looking back, I am not even sure that the argument is valid…wow, that’s embarrassing. In this post, I try to make the argument less complicated and less controversial. The new argument yields a new conclusion, I think.
P1. The truth-value of a non-contingent premise is not contingent on anything. [Tautology]
P2. Our intuitions and our ability to imagine (i.e., “conceivability“) are contingent on cognitive capacities [assumption].
P3. Our cognitive capacities are contingent on our physical properties [assumption].
‘Bottom-up’ and ‘top-down’ are staple concepts in cognitive science. These terms refer to more than one set of concepts, depending on the context. In this post, I want to talk about one version of ‘bottom-up’ and try to pin down what is at the “bottom” of cognition.
First, I should single out the meaning of ‘bottom-up’ that I have in mind. It is the one in which ‘bottom’ refers to the deterministic hardware and pre-conscious processes from which “higher level” processes like meaning, affect, and perhaps conscious awareness emerge. Continue reading Where Does “Bottom-up” Bottom Out?
Randy O’Reilly gave a talk at CU Boulder yesterday entitled “Goal-driven Cognition in the Brain:….” It was an excellent look at how goals have emerged in cognitive science and psychology and how goal-based models have improved upon previous behaviorist models. He also told a story about how goal-driven cognitive models can be grounded in neurobiology.1 There are two reasons I mention this talk. First, Randy’s talk convinced me that “goals” have a valuable place in the ontology of mental states. Second, his talk helped me realize an example that shows how goals and desires are dissociable. In this post, I will talk about this second item. Continue reading Goals & Desires
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