Marco Rubio recently suggested that we need fewer philosophers and more welders because welders make more money. See below:
In case it’s not obvious why this is a foolish suggestion, I’ll explain.
THE MAIN PROBLEM
Here are a couple claims that are probably true:
There is a need for more welders.
Some welders make more money than some philosophers.
Notice, however, that neither of the following follow from those probably true claims:
A. We need fewer philosophers.
B. On average, welders make more than philosophers.
So, insofar as Marco Rubio thinks that A and/or B follows from 1 and 2, Rubio is just wrong. And many people have pointed out that B is just false.† So insofar as Rubio thinks B is true, he is just wrong.
SOLUTIONS?
What can we learn from this?
We need better fact-checking in politics (ideally, politicians would check the facts before they start talking at a public venue).
We need more philosophy (viz., a proper understanding and appreciation of good reasoning) — even in the highest ranks of US politics. Maybe we need argument-checking: “Fact-checking is not enough. We need argument-checking“.
TWO MOREÂ PROBLEMS
And for those who still want to point out that we need more welders: fine! Having more welders and having more philosophers is not mutually exclusive! We can have both!†â€
Finally, there is the implicit suggestion that we should choose careers based on how much money the career offers. Sigh… Look, I get that we need a certain amount of money to flourish. But — contra Rubio’s short argument — surely there are other (more important?) variables involved in a career choice.
†“Marco Rubio said wrongly that welders make more money than philosophers” (Politifact). “Marco Rubio says welders make more money than philosophers do. He’s wrong” (Slate). “Philosophy majors actually earn a lot more than welders” (Vox).
††Thanks to John Ballenger, James Endicott, Andrew Chapman, Cameron Buckner, and Andrew Cullison for making these points (and other points that I haven’t even mentioned). Finally, thanks to my Facebook friends for humoring my Facebook rants about this.
At this point it’s pretty clear why someone would be worried about bias. We’re biased (Part 1). Consciously suppressing our biases might not work (Part 2).  And our bias seems to tamper with significant, real-world decisions (Part 3). So now that we’re good and scared, let’s think about what we can do. Below are more than 10 debiasing strategies that fall into 3 categories: debiasing our stereotypes, debiasing our environment, and debiasing our decision procedures. Continue reading Implicit Bias | Part 4: Ten Debiasing Strategies
Think about decisions that people make every day. A committee decides who to hire. A supervisor rates an employee’s performance. A teacher grades a student’s assignment. A jury arrives at a verdict. A Supreme Court judge casts their vote. An emergency medical technician decides which victim to approach first. A police officer decides whether to shoot. These are instances in which workplace bias can have significant consequences.
I won’t be able to highlight every area of research on workplace bias. So I cannot delve into the findings that police officers’ sometimes show racial bias in decisions to shoot (Sim, Correll, and Sadler 2013, Experiment 2; see Correll et al 2007, Ma and Correll 2011 Study 2 for findings that indicate no racial bias). And I cannot go into detail about how all-white juries are significantly more likely than other juries to convict black defendants (Anwar, Bayer, Hjalmarsson 2012).
GENDERÂ BIAS AT WORK
Instead, I’ll focus on the instances of workplace bias to which most people can relate. If you’re like most people, then you need to work to live, right? So let’s talk about how bias can affect our chances of being hired. Continue reading Implicit Bias | Part 3: Workplace Bias
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).
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
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?
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