Category Archives: philosophy

‘every thing that lives is holy’: Blake’s radical relativism

Perhaps each species has a different “umwelt,” a unique enveloping environment that is experienced and influenced by the organism’s sensory organs and nervous system. In that case, reality is not one connected thing, but rather everything that you can I could possibly experience and describe, plus the many other universes that are “enacted” (Varela, Thompson & Rosch 1991) by other species–those known and unknown to us, existent and yet to be.

Reflecting on such radical unknowability may have spiritual implications, which have been explored in different ways by Dogen (1200-1253 CE), Ludwig Wittgenstein, and others. (See “thinking both sides of the limits of human cognition.”)

William Blake presents a relevant discussion in his Visions of the Daughters of Albion (1793). Oothoon–a female figure, described as “the soft soul of America”–invokes the radical diversity of animal experiences, “as different as their forms and as their joys.” She implies that the consciousness of the chicken, pigeon and bee are fundamentally different. She uses such examples to pose a question about our own consciousness:

Ask the blind worm the secrets of the grave, and why her spires
Love to curl round the bones of death; and ask the rav’nous snake
Where she gets poison; and the wing’d eagle why he loves the sun
And then tell me the thoughts of man, that have been hid of old.

Blake, Selected Poems, Penguin Classics (p. 63).

I am not sure whether she is inviting us to imagine the experience of eagles and worms, or whether she assumes this would be impossible. Later, she exclaims, “How can one joy absorb another? are not different joys / Holy, eternal, infinite! and each joy is a Love” (p. 65).

This is a plea for appreciating fundamental diversity. She uses it to ask the person she loves, Theotormon, to accept her for who she is.

Blake had been exploring arguments for empathy. In his poem The French Revolution (1791), the pro-republican Duke of Orleans says to his reactionary peers:

But go, merciless man! enter into the infinite labyrinth of another's brain
Ere thou measure the circle that he shall run. Go, thou cold recluse, into the fires
Of another's high flaming rich bosom, and return unconsum'd, and write laws.
If thou canst not do this, doubt thy theories, learn to consider all men as thy equals,
Thy brethren, and not as thy foot or thy hand, unless thou first fearest to hurt them.

Blake may not endorse Orleans’ belief that one can actually enter others’ brains. I am not sure whether he thinks such radical empathy is virtuous or impossible. Either premise could be the basis for appreciating everyone’s uniqueness.

Bromion is a (very bad) male character in the Daughters of Albion. He replies to Oothoon by acknowledging that there are many

... trees[,] beasts and birds unknown: 
Unknown, not unpercievd, spread in the infinite microscope, 
In places yet unvisited by the voyager and in worlds 
Over another kind of seas, and in atmospheres unknown (p. 64).

Bromion then poses a series of questions about whether there are different wars, sorrows, and joys for these creatures. I think his answer is No:

And is there not one law for both the lion and the ox? 
And is there not eternal fire, and eternal chains? 
To bind the phantoms of existence from eternal life? (p. 65)

Here Bromion explicitly contradicts an aphorism from Blake’s “Proverbs of Hell” (1790)– “One Law for the Lion & Ox is Oppression” (p. 58)–which makes me suspect that Blake is against Bromion’s view.

The third speaker in The Daughters of Albion is Theotormon. He asks Oothoon to share what she knows of the world, “so that [he] might traverse times & spaces far remote.” But he is not sure what this will do for him:

Where goest thou O thought! to what remote land is thy flight?
If thou returnest to the present moment of affliction
Wilt thou bring comforts on thy wings, and dews and honey and balm;
Or poison From the desart wilds, from the eyes of the envier?’ (p. 64).

Theotormon is worried that empathy might cause envy or other harms. But Oothoon is sure that any experience of a consciousness other than one’s own is beneficial. She concludes the poem: “Arise and drink your bliss, for every thing that lives is holy!’ (p. 68). Theotormon sits silently while the other daughters of Albion “echo back her sighs.”

people are not points in space

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This is the video of a lecture that I gave at the Institute H21 symposium in Prague last September. The symposium was entitled Democracy in the 21st Century: Challenges for an Open Society, and my talk was: “People Are Not Points in Space: Opinions and Discussions as Networks of Ideas.” I’m grateful for the opportunity to present and for the ideas of other participants and organizers.

My main point was that academic research currently disparages the reasoning potential of ordinary people, and this skepticism discourages efforts to protect and enhance democratic institutions. I think the low estimate of people’s capacity is a bias that is reinforced by prevalent statistical methods, and I endorse an alternative methodology.

can AI help governments and corporations identify political opponents?

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In “Large Language Model Soft Ideologization via AI-Self-Consciousness,” Xiaotian Zhou, Qian Wang, Xiaofeng Wang, Haixu Tang, and Xiaozhong Liu use ChatGPT to identify the signature of “three distinct and influential ideologies: “’Trumplism’ (entwined with US politics), ‘BLM (Black Lives Matter)’ (a prominent social movement), and ‘China-US harmonious co-existence is of great significance’ (propaganda from the Chinese Communist Party).” They unpack each of these ideologies as a connected network of thousands of specific topics, each one having a positive or negative valence. For instance, someone who endorses the Chinese government’s line may mention US-China relationships and the Nixon-Mao summit as a pair of linked positive ideas.

The authors raise the concern that this method would be a cheap way to predict the ideological leanings of millions of individuals, whether or not they choose to express their core ideas. A government or company that wanted to keep an eye on potential opponents wouldn’t have to search social media for explicit references to their issues of concern. It could infer an oppositional stance from the pattern of topics that the individuals choose to mention.

I saw this article because the authors cite my piece, “Mapping ideologies as networks of ideas,” Journal of Political Ideologies (2022): 1-28. (Google Scholar notified me of the reference.) Along with many others, I am developing methods for analyzing people’s political views as belief-networks.

I have a benign motivation: I take seriously how people explicitly articulate and connect their own ideas and seek to reveal the highly heterogeneous ways that we reason. I am critical of methods that reduce people’s views to widely shared, unconscious psychological factors.

However, I can see that a similar method could be exploited to identify individuals as targets for surveillance and discrimination. Whereas I am interested in the whole of an individual’s stated belief-network, a powerful government or company might use the same data to infer whether a person would endorse an idea that it finds threatening, such as support for unions or affinity for a foreign country. If the individual chose to keep that particular idea private, the company or government could still infer it and take punitive action.

I’m pretty confident that my technical acumen is so limited that I will never contribute to effective monitoring. If I have anything to contribute, it’s in the domain of political theory. But this is something–yet another thing–to worry about.

a method for analyzing organizations

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I’m about to conduct a study in partnership with a civic association in the midwestern United States. It should yield insights that can inform this association’s plans and help me to develop a method and related theory. I have IRB approval to proceed, using instruments that are designed.

In the meantime, a colleague alerted me to an impressive new paper by Dalege, Galesic and Olsson (2023) that uses a very similar model. Fig. 1 in their paper resembles the image I’ve created with this post. These authors make an analogy to physics that allows them to write about spin, energy and temperature. I don’t have the necessary background to replicate their analysis but will contribute relevant empirical data from a real-world group and some additional interpretive concepts.

We will ask members of the association to what extent they agree with a list of relevant beliefs (derived from their own suggestions in an open-ended survey). We will ask them whether each belief that the individual endorses is a reason for their other beliefs. As a hypothetical example, you might think that the organization’s youth programming is important because you believe in investing in young people. That reflects a link between your two beliefs. We will also ask members to name their fellow members who most influence them.

In the hypothetical image with this post, the circles represent people: members of the group. A link between any two members indicates that one or both have identified the other as an influence. That is a social network graph.

The small shapes (stars, circles, etc.) represent the beliefs that individuals most strongly endorse. The arrows between pairs of beliefs indicate that one belief is a reason for another. This is a belief-network.

Reciprocal links are possible in both the social network and the belief networks.

Before analyzing the network data, I will also be able to derive some statistics that are not directly observed. For example, each node in both the social network and the belief networks has a certain amount of centrality, which can be measured in various standard ways. I can also run factor analysis on the responses about beliefs to see whether they reflect larger “constructs.” (Again, as a hypothetical example, it might turn out that several specific responses are consistent with an underlying concern for youth, and that construct could be measured for each member.)

I plan to test several hypotheses about this organization. These hypotheses are not meant to be generalizations. On the contrary, I expect that for any given organization, most of the hypotheses will turn out to be false. The purpose of testing them is to provide a description of the specific group that is useful for diagnosis and planning. Over time, it may also be possible to see which of these phenomena are most common under various circumstances.

Hypotheses to test

H1: The group is unified

H1a: The group is socially unified to the extent that its members belong to one network connected by interpersonal influences. The denser the ties within the connected network, the more the group displays social unity.

H1b: The group is epistemically epistemically unified to the extent that members endorse the same beliefs, and to the extent that these shared beliefs are central in their belief networks.

H2: The group is polarized.

H2a: The group is socially polarized if many members belong to two separate subgroups that are connected by interpersonal influences but are not connected to each other, as depicted by the red and blue clusters in my hypothetical image.

H2b: The group is epistemically polarized if many members endorse belief A, and many other members endorse B, but very few or no members endorse both A and B. If A and/or B also have high network centrality for the people who endorse them, that makes the epistemic polarization more serious. (Instead of examining specific beliefs, I could also look at constructs derived from factor analysis.)

H3: The group is fragmented

H3a: The group is socially fragmented if many members are connected by influence-links to zero or just one other member.

H3b: The group is epistemically fragmented if no specific beliefs are widely shared by the members.

H4: The group is homophilous if individuals who are connected by influence-ties are more likely to endorse the same beliefs, or have the same central beliefs, or reflect the same constructs, compared to those who are not connected. If the opposite is true–if socially connected people disagree more than the whole group does–then the group is heterophilous.

H5: There is a core and a periphery

H5a: There is a social core if some members are linked in a relatively large social network, while most other members are socially fragmented.

H5b: There is an epistemic core if many (but not all) members endorse a given belief, or a given belief is central for them, or they share the same constructs, while the rest of the organization does not endorse that belief.

H6: Certain members are bridges

H6a: A person is a social bridge if the whole group would be socially polarized without that person.

H6b: A person is an epistemic bridge if the whole group would be epistemically polarized without that person.

H7: Members tend to hold organized views: This is true if the mean density of individuals’ belief networks (the mean number of links/nodes) is high, indicating that people see a lot of logical connections among the things they believe.

Our survey respondents will answer demographic questions, so we will be able to tell whether polarized subgroups or core groups have similar demographic characteristics. Hypothetically, for example, a group could polarize epistemically or socially along gender lines. And we will ask general evaluative questions, such as whether an individual feels valued in the association, which will allow us to see whether phenomena like social- connectedness or agreement with others are related to satisfaction.

What to do with these results?

Although the practical implications of these results would depend on the organization’s goals and mission, I would generally expect polarization, fragmentation, the existence of cores, and homophily to be problematic. These variables may also intersect, so that an organizations that is socially polarized, epistemically polarized, homophilous, and reflects highly organized views is especially at risk of conflict. A group that is fragmented and reflects disorganized belief-networks at the individual level may face a different kind of risk, which I would informally label “entropy.”

Being unified can be advantageous, unless it reflects group-think or social exclusivity that will prevent the organization from growing.

Once an organization knows its specific challenges, it can use appropriate programming to make progress. For instance, if the group is socially fragmented, maybe it needs more social opportunities. If it is polarized, maybe a well-chosen discussion could help produce more bridges. If it displays entropy, maybe it needs a formal strategic plan.

I would generally anticipate that bridges are helpful and should be supported and encouraged. In our study, all the data will be anonymous, so our partner will not know the identity of any people who bridge gaps. But a different application of this method could reveal that information.

Although I am focused on this study now, I remain open to partnerships with other organizations so that I can continue this research agenda. Let me know if you lead an organization that would like to do a similar study a bit later on.

Reference: Dalege, J., Galesic, M., & Olsson, H. (2023, April 12). Networks of Beliefs: An Integrative Theory of Individual- and Social-Level Belief Dynamics. https://doi.org/10.31219/osf.io/368jz. See also: Analyzing Political Opinions and Discussions as Networks of Ideas; Mapping Ideologies as Networks of Ideas; seeking a religious congregation for a research study

the age of cybernetics

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A pivotal period in the development of our current world was the first decade after WWII. Much happened then, including the first great wave of decolonization and the solidification of democratic welfare states in Europe, but I’m especially interested in the intellectual and technological developments that bore the (now obsolete) label of “cybernetics.”

I’ve been influenced by reading Francisco Varela, Evan Thompson, and Eleanor Rosch, The Embodied Mind: Cognitive Science and Human Experience (first ed. 1991, revised ed., 2017), but I’d tell the story in a somewhat different way.

The War itself saw the rapid development of entities that seemed analogous to human brains. Those included the first computers, radar, and mechanisms for directing artillery. They also included extremely complex organizations for manufacturing and deploying arms and materiel. Accompanying these pragmatic breakthroughs were successful new techniques for modeling complex processes mathematically, plus intellectual innovations such as artificial neurons (McCullouch & Pitts 1943), feedback (Rosenblueth, Wiener, and Bigelow 1943), game theory (von Neumann & Morgenstern, 1944), stored-program computers (Turing 1946), information theory (Shannon 1948), systems engineering (Bell Labs, 1940s), and related work in economic theory (e.g., Schumpeter 1942) and anthropology (Mead 1942).

Perhaps these developments were overshadowed by nuclear physics and the Bomb, but even the Manhattan Project was a massive application of systems engineering. Concepts, people, money, minerals, and energy were organized for a common task.

After the War, some of the contributors recognized that these developments were related. The Macy Conferences, held regularly from 1942-1960, drew a Who’s Who of scientists, clinicians, philosophers, and social scientists. The topics of the first post-War Macy Conference (March 1946) included “Self-regulating and teleological mechanisms,” “Simulated neural networks emulating the calculus of propositional logic,” “Anthropology and how computers might learn how to learn,” “Object perception’s feedback mechanisms,” and “Deriving ethics from science.” Participants demonstrated notably diverse intellectual interests and orientations. For example, both Margaret Mead (a qualitative and socially critical anthropologist) and Norbert Wiener (a mathematician) were influential.

Wiener (who had graduated from Tufts in 1909 at age 14) argued that the central issue could be labeled “cybernetics” (Wiener & Rosenblueth 1947). He and his colleagues derived this term from the ancient Greek word for the person who steers a boat. For Wiener, the basic question was how any person, another animal, a machine, or a society attempts to direct itself while receiving feedback.

According to Varela, Thompson, and Rosch, the ferment and diversity of the first wave of cybernetics was lost when a single model became temporarily dominant. This was the idea of the von Neumann machine:

Such a machine stores data that may symbolize something about the world. Human beings write elaborate and intentional instructions (software) for how those data will be changed (computation) in response to new input. There is an input device, such as a punchcard reader or keyboard, and an output mechanism, such as a screen or printer. You type something, the processor computes, and out comes a result.

One can imagine human beings, other animals, and large organizations working like von Neumann machines. For instance, we get input from vision, we store memories, we reason about what we experience, and we say and do things as a result. But there is no evident connection between this architecture and the design of the actual human brain. (Where in our head is all that complicated software stored?) Besides, computers designed in this way made disappointing progress on artificial intelligence between 1945 and 1970. The 1968 movie 2001: A Space Odyssey envisioned a computer with a human personality by the turn of our century, but real technology has lagged far behind that.

The term “cybernetics” had named a truly interdisciplinary field. After about 1956, the word faded as the intellectual community split into separate disciplines, including computer science.

This was also the period when behaviorism was dominant in psychology (presuming that all we do is to act in ways that independent observers can see–there is nothing meaningful “inside” us). It was perhaps the peak of what James C. Scott calls “high modernism” (the idea that a state can accurately see and reorganize the whole society). And it was the heyday of “pluralism” in political science (which assumes that each group that is part of a polity automatically pursues its own interests). All of these movements have a certain kinship with the von Neumann architecture.

An alternative was already considered in the era of cybernetics: emergence from networks. Instead of designing a complex system to follow instructions, one can connect numerous simple components into a network and give them simple rules for changing their connections in respond to feedback. The dramatic changes in our digital world since ca. 1980 have used this approach rather than any central design, and now the analogy of machine intelligence to neural networks is dominant. Emergent order can operate at several levels at once; for example, we can envision individuals whose brains are neural networks connecting via electronic networks (such as the Internet) to form social networks and culture.

I have sketched this history–briefly and unreliably, because it’s not my expertise–without intending value-judgments. I am not sure to what extent these developments have been beneficial or destructive. But it seems important to understand where we’ve come from to know where we should go from here.

Peter Levine

A Blog for Civic Renewal

Category Archives: philosophy

‘every thing that lives is holy’: Blake’s radical relativism

people are not points in space

can AI help governments and corporations identify political opponents?

a method for analyzing organizations

the age of cybernetics