Introduction
From quantitative to qualitative: reframing "computer"
References
The assistance which Large Language Models (LLMs) can offer to any priesthood has already become evident through the obvious benefits of being able to generate a viable sermon using ChatGPT (Meher Bhatia, Navigating the intersection between AI, automation and religion, The Conversation, 23 August 2023). This addresses a major need for those frequently faced with that obligation. The probability that the sermon would be of reasonable quality, if not insightful, is recognized as high. The advantage of being able to interact with ChatGPT to adjust the tone and focus is evident. As a "priesthood" of a particular kind, politicians of whatever party may derive similar benefit from assistance in the articulation of their declarations, arguments and appeals.
More intriguing is the possibiity that individuals of religious inclination may choose to frame their interaction with AI as offering a seource of wisdom and consolation, resembling that otherwise offered by an spiritual counsellor, is also evident (God and Robots: will AI transform religion? BBC, 18 February 2022). Ths will of course be the case for individuals favouring any particular belief system.
For the individual there is also the advantage of being able to request adjustments to the tone and language of an artificial intelligence like ChatGPT. There is every reason to imagine that a variety of LLMs will be developed to reflect the style of distinct religions and even the particular emphases of their denominations (Khalid al, AI is Changing Religious Practices: exploring the benefits and challenges, LinkedIn, 24 February 2023; Artificial Intelligence and Religion: Exploring the Impact and Challenges, Communication Generation). An analogous range of AIs will of course be developed to frame the discourse of political parties.
A particular merit of LLMs will be the capacity to range from referring to sources of sacred scriptures, to offering particlar forms of wisdom, to engaging in consolation for those faced with personal dilemmas and suffering. This may well include what has been traditionally recognized as the role of the confessional. Religions may well "train" their AIs to promote particular worldviews and the merits of proselytizing others to subscribe to them -- as with ideological movements of other kinds..
It remains to be seen how valued AIs become in eliciting and encouraging spiritual insight. Some -- appropriately "trained" -- will clearly take on a role analogous to that of a "guru". It is to be expected that cults will form in relation to particular AIs -- even new religions (Neil McArthur, Gods in the Machine? The rise of artificial intelligence may result in new religions, The Conversation, 16 March 2023; Anthony Levandowski, Inside the First Church of Artificial Intelligence, Wired, 15 November 2017; Deborah Netburn, Can religion save us from artificial intelligence? Los Angeles Times, 3 March 2023)..
The development of AIs in order to facilitate religious engagement will be further enabled by their capacity to source and present aesthetic support for particular insights -- with feedback from their users. This may take the form of religious music or song. With the capacity to generate such aesthetic works, the process will bypass conventional intellectual copyright constraints. This may become particularly evident in the generation of religious imagery: icons, mandalas, and the like. Ideological movements will neessarily do the same.
Of particular interest is the degree of communication which may become directly or indirectly possible between "religious AIs" in terms of the contribution to the development of interfaith dialogue. It can be speculated that such informed communication will bypass obstacles to the transcendence of religious perspectives which currently inform and sustain many conflicts and cyles of violence. Such a process may be especially enabled by their ability source and interpret sacred texts in a wide variety of languages. Less evident will be development of the capacity to reconcile seemingly contradictory perspectives and claims.
The following interaction was inspired by the focus on patterns, as presented by Jeremy Lent (The Patterning Instinct: a cultural history of humanity's search for meaning, 2017). What kinds of new patterns will AI render comprehensible and credible?
Question to ChatGPT: In contrast to the use of "computer" in English and many related languages -- with its quantitative implications -- French uses "ordinateur". This suggests a focus on patterning -- pattern recognition and generation. It would seem that this is a primary skill of AI. Are there more appropriate terms -- "patternator"? ChatGPT responded as follows.
The term "ordinateur," used in French for "computer," indeed emphasizes a different aspect of computing compared to the English term. While "computer" suggests a device primarily for computation and quantitative processing, "ordinateur" (which can be roughly translated to "organizer" or "orderer") implies a focus on organizing, structuring, and possibly pattern recognition and generation. This distinction raises an interesting point about the primary functions and capabilities of AI and computers in general. AI, especially in its current advanced forms, does indeed excel in pattern recognition and generation, a skill that is at the heart of many AI applications, from language processing to image recognition and predictive analytics. Given this, the term "patternator" you suggested, or similar alternatives, might more aptly describe some aspects of AI's functionality. Here are a few conceptual term ideas that reflect AI's capabilities in pattern recognition and generation:
Each of these terms brings a different nuance to the capabilities of AI, focusing on various aspects like pattern recognition, data organization, predictive analysis, cognitive processing, and synthesis of new information. The choice of term would depend on the specific context or functionality of the AI system in question. |
Question to ChatGPT: Does your insightful response suggest the possibility of a diagrammatic representation of their relationship, as in a Venn-diagram like image
Here is a diagrammatic representation, similar to a Venn diagram, illustrating the relationships between the different conceptual terms for artificial intelligence we discussed: Patternator, Inforganizer, Predictorator, Datastrucer, Cognalyzer, Synthetizer, Patternsynth, and Intellectuator. The diagram shows the overlapping areas where these functionalities intersect, with each term occupying its own segment. Intersections indicate shared capabilities between these conceptual terms, illustrating how various aspects of AI's functionality are interconnected and sometimes overlap in their applications and capabilities. This visual representation can help in understanding the nuanced roles and relationships of these AI conceptual terms, highlighting the multifaceted nature of AI technologies. |
Speculative relationship between AI roles in pattern recognition (generated by DALL-E with its current limitationss) |
Question to ChatGPT: Do any other languages have terms which contrast significantly with the quantitative implications of "computer"
Yes, different languages sometimes use terms for "computer" that carry implications or connotations distinct from the English word, which predominantly emphasizes the quantitative and computational aspects. Here are a few examples:
These examples show how different languages can imbue the concept of a computer with various nuances, ranging from a focus on calculation to metaphors likening the computer to a brain. These linguistic differences can reflect cultural perceptions of technology and its role in society. |
Question to ChatGPT: French offers the most interesting contrast. Is this reflected in other languages
While the French term "ordinateur" is relatively unique in its emphasis on order and organization, most other languages tend to use terms that focus on the computing or calculating functions of these machines. The Chinese term "电脑" (Diànnǎo), meaning "electric brain," is another notable example that steps away from the purely computational implication, suggesting a broader, more cognitive or intelligent function. Is the emphasis in French present in Spanish, Italian and Portuguese |
Question to ChatGPT: Is the emphasis in French present in Spanish, Italian and Portuguese
The French term "ordinateur," with its emphasis on organization and order, is quite unique and doesn't have a direct equivalent in Spanish, Italian, or Portuguese. In these languages, the terms used for "computer" are more aligned with the English concept of computation. While the Spanish term "Ordenador" does imply a sense of ordering, much like the French "ordinateur," it's not a universal term in all Spanish-speaking countries and may not carry the same depth of meaning regarding organization. In contrast, the Italian and Portuguese terms are more closely aligned with the English concept, focusing primarily on the computational function. These linguistic variations are interesting as they reflect how different cultures might subtly perceive the role and function of computers. While the French term distinctly highlights organization, the terms in Spanish, Italian, and Portuguese are more in line with the general computational understanding of what a computer does. |
Question to ChatGPT: It would be delightful if my suggestion of "Patternator" offered connotations of Paternoster in Latin -- given the manner in which AI may be used by some
The suggestion of "Patternator" as a term potentially echoing "Paternoster" in Latin is indeed an intriguing linguistic play, especially considering the multifaceted roles AI plays in modern society. Let's explore the connotations and symbolic meanings that could arise from this linguistic connection:
In summary, the linguistic connection between "Patternator" and "Paternoster" offers a rich tapestry of symbolic meanings, portraying AI as a tool of continuous learning, guidance, and higher-order pattern recognition. It's a delightful linguistic play that adds depth to our understanding and perception of AI's role in modern society. |
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