22 Matching Annotations
  1. Jun 2018
    1. Each of the creators are university researcher/professors of engineering; Linda isEurasian/Latina and transgender, with a background in metallurgical engineering and materials scienceand engineering acquired in United States institutions; Nicola is a cis-gender woman, with abackground in environmental engineering and educational research, who moved to the U.S. fromAustralia after completing her doctoral studies. Ruth is a cis-gender woman, born and raised in theU.S., of Western-European ancestry, with an educational background in biology and educationalpsychology

      I quite like the idea of giving the point of view, but I am confused about what information is selected out. While gender and sexuality might be relevant in sorts of contexts, I am not really clear why these factors should be raised as relevant to the point of view raised in this type of discussion. There are many things which might influence points of view on this topic. It strikes me that more salient issues, in terms of pertinence to current discussion, might include such matters as whether anyone has a history, or family history or partner, of working either in neuroscience, or in the arts or humanities, or in therapy, or has been following recent trends in leadership/management and emotional intelligence.

  2. May 2018
    1. What questions am I left with? What would I like to know more about?

      There are a two questions that immediately spring to mind upon engaging with this article: First, I wonder, do engineers understand quite how deep the problem goes? Second, while I believe the solution to the problem is really quite simple, I am curious whether most Engineers would be willing to embrace it. I will now address each of these questions in turn.

      Do Engineers understand quite how deep the problem goes?

      There is now an overwhelming body of evidence which indicates that evolution engineered the brain to put analytic and empathic thinking into tension. Scientific and mechanical reasoning, along with calculation (math) and logic, are prototypical types of analytic thinking. When we engage in these types of thinking, we shut down the brain areas we need to understand the perspective of others (Anticevic et al., 2012; Jack et al., 2012) – an absolutely crucial component of ethical awareness and deliberation (Friedman & Jack, 2017; Jack, Dawson, & Norr, 2013).

      My main critique of this discussion article relates to the fact that the authors only touch on the surface of the large body of evidence which not only supports this view of the brain, but which also indicates that it impacts human behavior. First, the authors appear to have overlooked other work from my laboratory which is supportive of this view (e.g. a follow up study of the neural basis of dehumanizing (Jack et al., 2013)My laboratory has focused on this issue and its behavioral consequences for many years now. However, it would be very concerning if such claims about the function of the brain were wholly dependent on work from a single laboratory! Happily, this is not the case. The fact that attention demanding analytic tasks, such as mechanical reasoning, tend to deactivate brain regions essential for social, emotional and moral cognition might be fairly characterized as one of the most clearly established findings in cognitive neuroscience (Anticevic et al., 2012; Buckner, Andrews-Hanna, & Schacter, 2008; Shulman et al., 1997)]. This work is broken down in greater detail in many of my more recent articles. In addition, there are behavioral studies by researchers with no interest in the brain which clearly show that analytic thinking negatively impacts ethical thinking and behavior (Small, Loewenstein, & Slovic, 2007; Wang, Zhong, & Murnighan, 2014; Zhong, 2011)

      These studies provide powerful convergent evidence, since they were in no way motivated or informed by neuroscience – they are observations about patterns of human behavior made by behavioral economists and psychologists without reference to the underlying neural mechanism which explains why they occur. Since the authors do not appear to be aware of much of this literature, large parts of the article are quite tentative in tone. Nonetheless, in the section titled “Reflections on the implications for learning engineering”, the authors provide an excellent and incisive summary of exactly why our understanding of the brain should be a serious cause for concern for those who are concerned about educating ethical engineers.

      In this regard, it is worth mentioning how an emphasis on analytic thinking might increase one’s ability to ‘rationalize away’ the ethical consequences of one’s decision(s). The sorts of problem solving skills that engineers learn might then be applied to social and ethical dilemmas, which in turn removes the social and ethical significance.

      The authors do an excellent job of discussing why an engineering education is likely to reinforce students into predominately relying upon analytic thinking in preference to empathic thinking. They do this using the model shown in Figure 4, which illustrates how doing/behavior (i.e. practice at particular types of task) enables changes in structure (neural network function), and also vice-versa: changes in structure enable changes in doing/behavior. This creates a cycle of reinforcement. As the authors nicely put it: “the ‘doing’ that activates the Physical Stance [i.e. an engineering education] gives rise to the Physical stance as a preferred, low activation cognitive pathway….condition[ing] people to unconsciously apply mechanical reasoning to situations where social or moral reasoning would be a better fit for the purpose.” I believe the authors are exactly on point with this model. In my laboratory we have extended our neuroscience work by also measuring individual tendencies to think analytically and empathically with simple behavioral tests and self-report questionnaires. One way in which we measure analytic thinking is using the Intuitive Physics Test developed by Simon Baron-Cohen and colleagues, which can be easily found online for those who are interested and which is a good measure of everyday aptitude for mechanical thinking (Baron-Cohen, Wheelwright, Spong, Scahill, & Lawson, 2001)

      In these purely behavioral tests, we consistently find evidence for a small trade-off between these two ways of thinking (Friedman & Jack, 2017). That is, individuals who score higher on analytic thinking tend to score very slightly lower on empathic thinking. Some of these findings are reported incidentally in (Jack, Friedman, Boyatzis, & Taylor, 2016). We are currently preparing a manuscript which collates a much larger set of studies and focuses solely on this issue. The small trade-off between empathic and analytic thinking becomes accentuated for cases where it is less clear which way of thinking is best suited to the matter of hand. For instance, we have now performed a number of studies of religious belief. Supernatural claims, such as that God or a universal spirit exists, seem clearly incorrect from a purely mechanical way of thinking. However, we posited that they would seem correct from an empathic way of thinking. Correspondingly, we found that analytic thinking ability is associated with decreased religious belief, whereas empathic thinking is associated with increased religious belief (Jack et al., 2016). Other unpublished work in progress shows an even more robust association between these two ways of thinking and how much individuals care about dehumanized outgroups. Unsurprisingly, people higher in empathy care more about dehumanized outgroups than people lower in empathy. More remarkably, people who score higher on the Intuitive Physics Test care less about dehumanized outgroups than people who score lower on that measure of analytic thinking. I am comfortable informally reporting this finding since we have now replicated it. We aim to extend it with a further study before publication. The important point which emerges from this work is that individuals who have strongly reinforced one way of thinking without seeking to balance that out with another way of thinking show a clear tendency to default to (or prefer) one cognitive strategy over another when faced with any situation which is even remotely ambiguous. In other words, those whose training has focused predominantly on analytic thinking, such as engineers, will tend to overlook the more human perspective. This observation was made anecdotally long before cognitive neuroscience emerged as a discipline, or psychology developed the instruments to assess it quantitatively. The famous Oxford philosopher, P.F. Strawson, wrote in his groundbreaking article on the philosophy of free will “But what is above all interesting is the tension there is, in us, …between our humanity and our intelligence” (Strawson 1962, p.10).

      In the next part of their section titled “Reflections on the implications for learning engineering,” the authors make another insightful and important point. They observe that as we overdevelop one way of thinking, we may distort our whole picture of the world to fit with that way of thinking. They make this point by reference to Lakoff’s notion of frames, which is certainly a useful tool for thinking about how we think. However, I would suggest the basic point is perhaps more simply and more powerfully made by the well-known aphorism they aptly mention: “If one only has a hammer, everything looks like a nail.”

      The distortion of the world to fit with a purely scientific or analytic way of thinking is something I find I am obliged to wrestle with frequently. One label for this phenomenon is ‘scientism’. Since I teach at university dominated by the hard sciences and Engineering, such scientistic attitudes are quite common. They are also quite common in neuroscience and in some branches of psychology. An amusing example of this is a recent book by the very analytically smart psychologist Paul Bloom, who has written many warmly received popular science books. However, he recently published a book titled “Against Empathy” to resounding condemnation from virtually all intellectually informed readers, in particular other psychologists, philosophers, sociologists and anthropologists. In essence, Paul Bloom’s lack of connection to empathy motivated him to form a completely distorted picture of it, and motivated him to write a book which attacks empathy in ridiculous and contrived ways, such that it is barely coherent from an analytic (either scientific or logical) point of view. Such poor judgment is remarkable for such a smart and accomplished individual, both as a scientist and as a popular science author.

      Since the discussion article highlights the tension between mechanistic reasoning and ethics, it is important to note that ethics itself can be split into perspectives that are predominantly analytic (utilitarianism), versus more empathic perspectives that focus more on humanity. This is in itself a topic of some study in cognitive neuroscience. My own published view is that competent ethical thinking requires us to balance analytic and empathic perspectives on a situation (Friedman, Jack, Rochford, & Boyatzis, 2015; Friedman & Jack, 2017; Rochford, Jack, Boyatzis, & French, 2016). In general, the error that is most often made in current society is to tend towards emphasizing an analytic approach and excluding an empathic approach. That a purely analytic way of thinking ethically is problematic is illustrated by the fact it motivates actions without regard for human rights, including acts which would be categorized under current law as unjustified killing. Many of the recent ethical scandals that have plagued major corporations appear to have stemmed from an overemphasis on an analytic way seeing issues. An analytic, performance oriented way of thinking, especially in organizations, can have more subtle ethical consequences, such that those individuals are less likely to engage in helpful behaviors that bolster the social atmosphere at that organization (Bergeron, 2007; Bergeron, Shipp, Rosen, & Furst, 2011).

      While a solution may be straightforward, would most engineers be willing to embrace such a solution?

      There is one way in which the problem may not be quite so bad as the authors fear. They suggest that a focus on mechanical reasoning may actively weaken our social and ethical thinking skills. This is one way of reading what the neuroscience tells us, however I would suggest another way of understanding it. The fact that social, emotional and moral cognition areas are suppressed during mechanical reasoning need not mean they are being weakened. Another way of looking at this suppression is that it is protective – it gets those brain areas out of the way. In any case, there is no reason to suppose the suppression actively weakens the function of those brain areas. It merely fails to develop them. This is a problem which, I suggest, can be overcome by two strategies: (1) training to ensure the empathic, as opposed to the analytic brain network, is deployed during social and ethical decision making and (2) training to develop the empathic brain network. Neither of these strategies need impugn the intention to predominantly train engineering students in mechanical reasoning. They merely require engineering schools to embrace and positively require a modest number of courses which can help stem one side of their students brains’ from withering away. Training of the empathic network may be accomplished by classes on empathic listening, social skills for leadership, art appreciation, history, literature, as well as philosophy classes on happiness and ethics. Such classes are likely to greatly help students to possess more balanced brains and live more balanced lives. As a result they are likely to improve student performance, rather than detract from their engineering skills. My concern, however, is that many professional engineers are likely to be so unfamiliar with these forms of understanding, that they will find it hard to endorse including them in the curriculum. Indeed, some engineering faculty may be so unfamiliar with the value of these types of thinking that they find them threatening, and so react by being dismissive and actively fighting their introduction in the curriculum. In other words, they might be ‘blind’ to the value of such social, ethical and moral insights because they lack they the cognitive ability to perceive them, let alone appreciate them. Hence, while there may be many enlightened Engineering faculty, such as those who have written this discussion piece, I suspect a different voice will triumph in faculty meetings. If psychology has taught us anything, it is that human decision making is rarely guided by passion for the truth as much as by other emotions, especially emotions associated with a sense of threat to self. Hence, while it may be that no reasonable person could deny the brain has been engineered by evolution such that it needs to be educated in different modalities, I rather doubt this truth will guide engineering faculty.

      I'd like to acknowledge Jared Friedman for thoughtful input to the reflections that I offer here.

      Anticevic, A., Cole, M. W., Murray, J. D., Corlett, P. R., Wang, X. J., & Krystal, J. H. (2012). The role of default network deactivation in cognition and disease. Trends Cogn Sci, 16(12), 584-592. doi:10.1016/j.tics.2012.10.008 S1364-6613(12)00244-6 [pii]

      Baron-Cohen, S., Wheelwright, S., Spong, A., Scahill, V., & Lawson, J. (2001). Are intuitive physics and intuitive psychology independent? A test with children with Asperger Syndrome. Journal of Developmental and Learning Disorders, 5(1), 47-78.

      Bergeron, D. M. (2007). The potential paradox of organizational citizenship behavior: Good citizens at what cost? Academy of Management Review, 32(4), 1078-1095. Bergeron, D. M., Shipp, A. J., Rosen, B., & Furst, S. A. (2011). Organizational citizenship behavior and career outcomes the cost of being a good citizen. Journal of Management, 0149206311407508.

      Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The Brain's Default Network: Anatomy, Function, and Relevance to Disease. Annals of the New York Academy of Sciences, 1124(1), 1-38. doi:10.1196/annals.1440.011 Cech, E. A. (2014). Culture of disengagement in engineering education? Science, Technology, & Human Values, 39(1), 42-72.

      Friedman, J., Jack, A. I., Rochford, K., & Boyatzis, R. (2015). Antagonistic Neural Networks Underlying Organizational Behavior. Organizational Neuroscience (Monographs in Leadership and Management, Volume 7) Emerald Group Publishing Limited, 7, 115-141.

      Friedman, J. P., & Jack, A. I. (2017). Mapping cognitive structure onto the landscape of philosophical debate: An empirical framework with relevance to problems of consciousness, free will and ethics. Review of Philosophy and Psychology.

      Jack, Dawson, A. J., Begany, K. L., Leckie, R. L., Barry, K. P., Ciccia, A. H., & Snyder, A. Z. (2012). fMRI reveals reciprocal inhibition between social and physical cognitive domains. Neuroimage, 66C, 385-401. doi:S1053-8119(12)01064-6 [pii] 10.1016/j.neuroimage.2012.10.061

      Jack, Dawson, A. J., & Norr, M. E. (2013). Seeing human: distinct and overlapping neural signatures associated with two forms of dehumanization. Neuroimage, 79, 313-328. Jack, A. I., Friedman, J. P., Boyatzis, R. E., & Taylor, S. N. (2016). Why do you believe in God? Relationships between religious belief, analytic thinking, mentalizing and moral concern. PloS one, 11(3), e0149989.

      Rochford, K. C., Jack, A. I., Boyatzis, R. E., & French, S. E. (2016). Ethical leadership as a balance between opposing neural networks. Journal of Business Ethics, 1-16.

      Shulman, G. L., Fiez, J. A., Corbetta, M., Buckner, R. L., Miezin, F. M., Raichle, M. E., & Petersen, S. E. (1997). Common Blood Flow Changes across Visual Tasks: II. Decreases in Cerebral Cortex. J Cogn Neurosci, 9(5), 648-663. doi:10.1162/jocn.1997.9.5.648

      Small, D. A., Loewenstein, G., & Slovic, P. (2007). Sympathy and callousness: The impact of deliberative thought on donations to identifiable and statistical victims. Organizational Behavior and Human Decision Processes, 102(2), 143-153. doi:10.1016/j.obhdp.2006.01.005

      Wang, L., Zhong, C.-B., & Murnighan, J. K. (2014). The social and ethical consequences of a calculative mindset. Organizational Behavior and Human Decision Processes, 125(1), 39-49.

      Zhong, C.-B. (2011). The ethical dangers of deliberative decision making. Administrative Science Quarterly, 56(1), 1-25.

    2. I will give some reflections which directly address the three suggested question from the reflector guidelines, which I will answer in two segments:

      1) What did I learn from engaging this work?

      Given my own background leading some of the neuroscience research discussed, the most significant point I learnt from engaging with this work is the deep sense of commitment demonstrated by (at least some) engineers to the ethical dimension of their profession. This was made vivid to me by three points: First, and foremost, by the effort and thought put into the creation of this discussion article by three university engineers. Second, by the quote from the creed of the NSPE which makes clear the professional commitment of engineers to "dedicate [their] professional knowledge and skill to the advancement and betterment of human welfare." Third, by the fascinating longitudinal study cited in the text (Cech, 2014), which provides compelling empirical evidence that an engineering education causes students to ethically disengage.

      I hugely applaud the growing awareness amongst Engineers of the importance of ethical sensitivity. It fits with a larger trend of increasing awareness of the importance of ‘soft’ or people skills to the practice of being an effective Engineer. This increased awareness is reflected in some recent news stories about well-known Tech giants (see links below). I also see it closer to home. My own University, Case Western Reserve University, has a very well-respected school of Engineering which has recently decided to train leadership skills in undergraduates as part of the required core curriculum.

      I applaud this trend and I want to emphasize how incredibly important it is that Engineering schools also train students to be able to think properly about ethics. Technology has, and will continue to, fundamentally change our lives. However – and often despite the best intentions – those changes are not always for the best. Technologies intended to be used for good often have unintended consequences, and/or can be intentionally exploited to ill effect. It is crucially important that ethical considerations are built into the process of designing and building new technologies. It is not a good solution for such ethical issues to be left entirely for other people to worry about. Ethics fundamentally boils down to how one comports oneself in an interpersonal world – and technology is increasingly becoming enmeshed in our interpersonal lives. The idea that ethics is ‘done’ in ivory towers, only amongst philosophers, is far from the truth. This is, of course, not to dismiss the theorizing that ethicists and philosophers engage in. Professional ethicists can and should play an important role in teams that develop and build new technologies. However, if ethical concerns are to be adequately heard and heeded, it is essential that the creators of new technology are themselves equipped to appreciate ethical concerns. This is fundamentally important if they are to be competent to engage in meaningful dialogue with others about the trade-offs involved in different design choices. Perhaps more importantly, it is essential that engineers understand ethical concerns, for otherwise they will never be truly motivated to create for ethical reasons.

      The surprising thing Google learned about it employees

      How to lead with empathy

    3. state of unfocused modes of thinking oftencalled “daydreaming” or “mind wandering” (Buckner, Andrews-Hannah, & Schacter, 2008)

      yes, but we ruled out this hypothesis and very few people would accept this description of it any more

    4. Figure 4. Identification of atlas representations of BOLD differences from Jack et al. 2013, overlaid withannotations to illustrate how the atlas images are related to one another.

      The labels that I would use are the following, starting with the top left image and going to the right: left hemisphere, lateral surface; left hemisphere, medial surface, left hemisphere, entire cortical surface cut and flattened. Second row of images, starting at the left-most and reading to the right: right hemisphere, lateral; right hemisphere, medial; right cortical surface.

    5. massaged

      They are highly processed, yes. Depends how the analysis is done quite how much. As I mentioned before, I like to look at the data in as raw a form as possible to make sure their aren't misleading assumptions. Not all brain imagers do this! The phrase 'massaged' is pejorative. That may be fair of some researchers, but certainly not all.

    6. test stimulus

      Actually in Jack et al 2013 we modelled it both with and without making such an assumption, referred to as "assumed BOLD response". The timecourses that are shown involve making no such assumption. I usually try to analyze also with fewer assumptions to make sure the assumptions are not distorting the picture of reality.

    7. inhibitory in its effect.

      absolutely correct, it can be inhibitory. However it appears dubious that is what is going on in practice when one sees increases in BOLD. The standard assumption that increases in BOLD reflect increased use of a brain area appears to hold well and I don't know of it ever being empirically challenged.

    8. neuron emitting the BOLD signal

      This isn't quite right. It is thought to index neural activity, and empirical tests indicate it does quite reliably, however the route is even more circuitous than you mention. The INCREASE in blood oxygen level obviously doesn't come from the metabolic demands directly - they would decrease oxygen! Rather is come from the fact the vascalature oversupplies oxygenated blood after it detects metabolic activity.

    9. Spunt, Meyer, & Lieberman,

      I believe it was first used in a seminal social neuroscience imaging study on a paper I was an author on, called "Imaging the Intentional Stance" published in 2002. The term means the same. It originally comes from the philosopher Dennett - see his book "the intentional stance"

    10. Spunt, Meyer, & Lieberman, 2015

      Note that the Jack et al study tests this hypothesis and finds it empirically inadequate. It is true it still has the name, but few cognitive neuroscientists who have kept up with the literature think the label is anything other than misleading.

    11. shows symmetric fMRI signals

      Actually the analytic network is slighly left dominant and the empathic network slightly right. This can be gleaned from the Jack et al 2013 study. The slight assymetry may explain why the closely related left-right brain idea took hold and has taken off so well despite the lack of good neuroscience support for clear lateralization.