Category Archives: metaphors

Are We Racists?

BMAI friends. The following ramble is my first cut at making sense of the grave role racial (and other) bias is playing in the world today. This was prompted by comments I see daily from my family and friends on social media. Thinking about the great lack of self- and group-awareness many of the commenters display, I turned my scope inward. How do my own innate, evolved biases slant me to take my group’s and my own privileges for granted and make invalid assumptions about those I perceive (subconsciously or explicitly) to be ‘the other’? I put this forward to start a discussion and hope you will contribute your own insights and references. Feel free to post comments or even insert questions, comments, or new text directly into my text. Of course, you can create your own new posts as well. Thanks.

Two Levels of Racism
1. Population Group Level
Racism is an expression of group dynamics. Consider two levels of racism. First, there’s systemic racism where conditions in a population generally favor one race over others. One race (or maybe a few races) has greater access to material and cultural influence in the population. This does not occur accidentally, but through the ongoing efforts of the dominant group to achieve and expand its controlling influence.
2. Individual and Local-Group Level
That’s where the second level of racism comes in. How a person perceives any group’s efforts to attain equal access and influence depends on whether the person is in the dominant group or the aspiring group. There are many ways individuals and their affinity groups perceive and act within the racially unequal system to maintain or change the racial inequalities. The group in power perceives efforts in its favor as good, appropriate, justified, patriotic, necessary, ethical, moral, and even (when there’s a shared group supernatural narrative) ordained, holy, etc. When a member of an out-group appears to support (or at least not outwardly oppose) the in-group’s dominance, members of the in-group view that as a proof that they are rightfully on top.
The group in power perceives any questioning of its dominance in the larger population as suspicious, dishonest, lazy (attempts to gain more access than is deserved), subversive, unpatriotic (or even treasonous), or (through the lens of dogma) evil, anti-God, etc. Obviously, racism (and other efforts to maintain inequality) is at work when these perceptions are acted out by legislators, law enforcers, prosecutors, juries, judges, presidents and their staff members, the private sector, and individual members of the favored group.
Members of a group with less influence perceive their questioning of the dominant group’s power in opposite terms from how the dominant group sees their struggle. Members of lower-access groups experience their quest for equality on all fronts as expressions of their inherent right–even necessity–to pursue “life, liberty, and happiness.” They see the efforts of dominant groups to control and exclude them as unjustified oppression by people who abuse the power provided them within a biased system that clearly needs to be changed.
On the first (population) level, racism is an aspect of the in-group/out-group dynamics that are present in all of us. Our ‘hard-wired’ programming is to subconsciously favor those we perceive to be more like us (in outward appearance, views, and culture) and subconsciously feel some degree of aversion and suspicion (and often fear) of those whose appearances, views, and culture vary from ours. Groups (through the actions of their members and leaders) use their power to slant social and economic systems to favor their own power and influence and to decrease the influence of those they perceive as not members of their group(s). When this natural bias results in one racial group having greater access to resources (education, healthcare, emergency services, and other public services; jobs; legislative influence; judicial equality; media visibility; etc.), systemic or structural racism is in place.
A takeaway of all this is that we are all racists, in the sense that the human brain has evolved complex social navigation functions that include strong biases in favor of one’s perceived in-group and disfavoring members of all other groups. To the extent we are hard-wired to perceive people who (as a category) look superficially different from us as somehow less safe or worthy of inclusion and power-sharing, we are innately racist. When we make the effort to become aware of, challenge, and ensure our racial biases do not influence our words and actions, we are moving toward a less bigoted way of being.

The Metaphorical Brain

Lakoff’s last article was published in this open access Ebook edited by Seana Coulson and Vicky T. Lai, published by Frontiers Media SA in Frontiers in Human Neuroscience (March, 2016). The blurb:

Metaphor has been an issue of intense research and debate for decades (see, for example [1]). Researchers in various disciplines, including linguistics, psychology, computer science, education, and philosophy have developed a variety of theories, and much progress has been made [2]. For one, metaphor is no longer considered a rhetorical flourish that is found mainly in literary texts. Rather, linguists have shown that metaphor is a pervasive phenomenon in everyday language, a major force in the development of new word meanings, and the source of at least some grammatical function words [3]. Indeed, one of the most influential theories of metaphor involves the suggestion that the frequency of metaphoric language results because cross-domain mappings are a major determinant in the organization of semantic memory, as cognitive and neural resources for dealing with concrete domains are recruited for the conceptualization of more abstract ones [4]. Researchers in cognitive neuroscience have explored whether particular kinds of brain damage are associated with metaphor production and comprehension deficits, and whether similar brain regions are recruited when healthy adults understand the literal and metaphorical meanings of the same words (see [5] for a review). Whereas early research on this topic focused on the issue of the role of hemispheric asymmetry in the comprehension and production of metaphors [6], in recent years cognitive neuroscientists have argued that metaphor is not a monolithic category, and that metaphor processing varies as a function of numerous factors, including the novelty or conventionality of a particular metaphoric expression, its part of speech, and the extent of contextual support for the metaphoric meaning (see, e.g., [7], [8], [9]). Moreover, recent developments in cognitive neuroscience point to a sensorimotor basis for many concrete concepts, and raise the issue of whether these mechanisms are ever recruited to process more abstract concepts [10]. This Frontiers Research Topic brings together contributions from researchers in cognitive neuroscience whose work involves the study of metaphor in language and thought in order to promote the development of the neuroscientific investigation of metaphor. Adopting an interdisciplinary perspective, it synthesizes current findings on the cognitive neuroscience of metaphor, provides a forum for voicing novel perspectives, and promotes avenues for new research on the metaphorical brain.

[1] Arbib, M. A. (1989). The metaphorical brain 2: Neural networks and beyond. John Wiley & Sons, Inc.
[2] Gibbs Jr, R. W. (Ed.). (2008). The Cambridge handbook of metaphor and thought. Cambridge University Press.
[3] Sweetser, Eve E. “Grammaticalization and semantic bleaching.” Annual Meeting of the Berkeley Linguistics Society. Vol. 14. 2011.
[4] Lakoff, G., & Johnson, M. (1999). Philosophy in the flesh: The embodied mind and its challenge to western thought.
[5] Coulson, S. (2008). Metaphor comprehension and the brain. The Cambridge handbook of metaphor and thought, 177-194.
[6] Winner, E., & Gardner, H. (1977). The comprehension of metaphor in brain-damaged patients. Brain, 100(4), 717-729.
[7] Coulson, S., & Van Petten, C. (2007). A special role for the right hemisphere in metaphor comprehension?: ERP evidence from hemifield presentation. Brain Research, 1146, 128-145.
[8] Lai, V. T., Curran, T., & Menn, L. (2009). Comprehending conventional and novel metaphors: An ERP study. Brain Research, 1284, 145-155.
[9] Schmidt, G. L., Kranjec, A., Cardillo, E. R., & Chatterjee, A. (2010). Beyond laterality: a critical assessment of research on the neural basis of metaphor. Journal of the International Neuropsychological Society, 16(01), 1-5.
[10] Desai, R. H., Binder, J. R., Conant, L. L., Mano, Q. R., & Seidenberg, M. S. (2011). The neural career of sensory-motor metaphors. Journal of Cognitive Neurosc., 23(9), 2376

Mapping the brain’s metaphor circuitry

By George Lakoff, Frontiers in Human Neureoscience, Hypothesis and Theory Article (link), 2014. Introduction: “An overview of the basics of metaphorical thought and language from the perspective of Neurocognition, the integrated interdisciplinary study of how conceptual thought and language work in the brain. The paper outlines a theory of metaphor circuitry and discusses how everyday reason makes use of embodied metaphor circuitry.” Also see the section on experimental results for the studies.

Embodied philosophy in a nutshell

In this 4-minute clip Lakoff summarizes how philosophy is changed by cognitive science. Particular philosophies get attached to a root metaphor (or blend) that entails certain premises and conclude that it is reality in toto without going further to understand that other metaphors entail different premises with equally logical conclusions. The embodied thesis helps us understand how our body-minds work to correct many of philosophy’s metaphysical assumptions while providing a postmetaphysical frame for an empirical, embodied and multifarious philosophy.

Who am I: the conscious and unconscious self

Frontiers in Human Neuroscience, 2017; 11: 126. Some excerpts:

“In this article we suggest the idea that the processing of self-referential stimuli in cortical midline structures (CMS) may represent an important part of the conscious self, which may be supplemented by an unconscious part of the self that has been called an ’embodied mind’ (Varela et al., 1991), which relies on other brain structures.”

“When we describe the self as structure and organization we understand it as a system. But the concept of the embodied self states that the self or cognition is not an activity of the mind alone, but is distributed across the entire situation including mind, body, environment (e.g., Beer, 1995), thereby pointing to an embodied and situated self.”

“Furthermore, we argue that through embodiment the self is also embedded in the environment. This means that our self is not isolated but intrinsically social. […] Hence, the self should not be understood as an entity located somewhere in the brain, isolated from both the body and the environment. In contrast, the self can be seen as a brain-based neurosocial structure and organization, always linked to the environment (or the social sphere) via embodiment and embeddedness.”

Memes are like cognitive frames

It occurred to me that memes are a lot like frames as Lakoff describes them. Lakoff has done extensive cognitive scientific work on schemas, metaphors and frames. Check out this lengthy article in Frontiers in Human Neuroscience, 2014; 8: 958, “Mapping the brain’s metaphor circuitry.” Even though they don’t relate this to the concept of memes, there are some striking similarities. E.g.: 

“Reddy had found that the abstract concepts of communication and ideas are understood via a conceptual metaphor: Ideas Are Objects; Language Is a Container for Idea-Objects; Communication Is Sending Idea-Objects in Language-Containers.”

Should AI agents’ voice interactions be more like our own? What effects should we anticipate?

An article at considers the pros and cons of making the voice interactions of AI assistants more humanlike.

The assumption that more human-like speech from AIs is naturally better may prove as incorrect as the belief that the desktop metaphor was the best way to make humans more proficient in using computers. When designing the interfaces between humans and machines, should we minimize the demands placed on users to learn more about the system they’re interacting with? That seems to have been Alan Kay’s assumption when he designed the first desktop interface back in 1970.

Problems arise when the interaction metaphor diverges too far from the reality of how the underlying system is organized and works. In a personal example, someone dear to me grew up helping her mother–an office manager for several businesses. Dear one was thoroughly familiar with physical desktops, paper documents and forms, file folders, and filing cabinets. As I explained how to create, save, and retrieve information on a 1990 Mac, she quickly overcame her initial fear. “Oh, it’s just like in the real world!” (Chalk one for Alan Kay? Not so fast.) I knew better than to tell her the truth at that point. Dear one’s Mac honeymoon crashed a few days later when, to her horror and confusion, she discovered a file cabinet inside a folder. A few years later, there was another metaphor collapse when she clicked on a string of underlined text in a document and was forcibly and instantly transported to a strange destination.

Having come to terms with computers through the command-line interface, I found the desktop metaphor annoying and unnecessary. Hyperlinking, however–that’s another matter altogether–an innovation that multiplied the value I found in computing.

On the other end of the complexity spectrum would be machine-level code. There would be no general computing today if we all had to speak to computers in their own fundamental language of ones and zeros. That hasn’t stopped some hard-core computer geeks from advocating extreme positions on appropriate interaction modes, as reflected in this quote from a 1984 edition of InfoWorld:

“There isn’t any software! Only different internal states of hardware. It’s all hardware! It’s a shame programmers don’t grok that better.”

Interaction designers operate on the metaphor end of the spectrum by necessity. The human brain organizes concepts by semantic association. But sometimes a different metaphor makes all the difference. And sometimes, to be truly proficient when interacting with automation systems, we have to invest the effort to understand less simplistic metaphors.

The article referenced in the beginning of this post mentions that humans are manually coding “speech synthesis markup tags” to cause synthesized voices of AI systems to sound more natural. (Note that this creates an appearance that the AI understands the user’s intent and emotional state, though this more natural intelligence is illusory.) Intuitively, this sounds appropriate. The down side, as the article points out, is that colloquial AI speech limits human-machine interactions to the sort of vagueness inherent in informal speech. It also trains humans to be less articulate. The result may be interactions that fail to clearly communicate what either party actually means.

I suspect a colloquial mode could be more effective in certain kinds of interactions: when attempting to deceive a human into thinking she’s speaking with another human; virtual talk therapy; when translating from one language to another in situations where idioms, inflections, pauses, tonality, and other linguistic nuances affect meaning and emotion; etc.

In conclusion, operating systems, applications, and AIs are not humans. To improve our effectiveness in using more complex automation systems, we will have to meet them farther along the complexity continuum–still far from machine code, but at points of complexity that require much more of us as users.