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Like many critical concepts around which social relations are dependent, artificial intelligence (AI) has assumed a symbolic significance. That is, AI has become a term that represents more than itself. It has become the way in which people refer to a cluster of meaning, approaches, and premises about technology and its relationship to social relations. AI has become its own idea; as well as the vessel for a host of sometimes incompatible premises about humans, human society, technology, and more broadly consciousness, and the principles and assumptions around which social collectives (and individuals) cede authority over decision making (big and little) to processes, algorithms, analytics, and computational thought processes based on inductive reasoning from unending streams of iterative behaviors. What started out as a desire to produce simulation--the simulacra of humanity to solve problems, has become a linked set of processes and applications that can (in an ironically dialectical way) drive human behavior through the logic of its own programming (considered here).
The idea of AI blends together distinct streams of technological development (eg deep learning, natural language process, robotics, computer vision, problem solving reasoning (expert) systems). The first learns from data (pattern finding and projection); the second connects data learning to solve problems; the third translates and applies language as a sort of applied semiotics; the third embeds machines with capacity to perform tasks automatically; and the last comes closest to attempting to mimic human reasoning and decision making in the context of traditional human individual or institutional tasks (one way of looking at it here). In the aggregate, where various levels of technological development are inserted into an increasing number of human actions and interactions, on can arrive at a point where the individual and the collective are effectively managed or curated at the micro and macro level by and through clusters of tech based programing. At its limit, it can invert the relationship between the humans for whose benefit it is adopted and the ecologies of programs and functions that produce the benefit.
Pix Credit clip from the Movie Brazil here |
The idea of AI also blends together a host of tasks to which it is directed. Many of them are a function of capacity--data based problem solving. Their differentiation is a function of the complexity of the problem to be solved and the autonomy of decision making. Te later can be infinitely divided around sub-programing or aggregated to produce a "final" or "end product" decision or action. They are based on data, analyzed against premises, assumptions and expectations at least initially programmed into the process by humans. The analytics can themselves become part of the problem solving ecology permitting the technology to modify its analytical functions on the basis of its its encounters with data within the ultimate action parameters that may be inserted. but also cap. But large enough data streams can assume a life of their own--and projected through time can themselves serve as the basis for evolving analytics that then change the parameters of analysis. In one sense it it a very high volume chartist approach but with expanded capabilities and functions (e.g., predicting the cost of transport).
None of this makes much sense without beginning to appreciate the extent to which dependency is already emerging within complex webs of differentiated big data tech. But even getting to data to answer that query, in contemporary society, requires or is made possible only by invoking the technology itself. Thus, for example, a Google" query on "AI applications" produces a suggestion that one use Google Cloud. Even the search itself is possible through the application of big data tech. Even a cursory search suggests the current breadth of use.
Some examples: (1) Sam Daley describes "56 Artificial Intelligence Examples Shaking Up Business Across Industries;" (2) Avijeet Biswal describes "18 Cutting-Edge Artificial Intelligence Applications in 2024" across a variety of sectors; (3) Passionate also notes 18 sectors in which various forms of AI may be encountered (here); (4) Forbes describes "Applications of Artificial Intelligence Across Various Industries" suggesting that, at least for the moment, "AI usage is particularly prominent in finance, digital spaces (like social media, e-commerce, and e-marketing) and even healthcare"; (5) Siddhesh Shinde for Emeritus explored the ecologies of big data tech in heathcare, e-commerce, robotics, education, finance, marketing, banking, social media, business, and sustainability (here); (6)
These programs focus on the automation of processes and interactions, compliance, and all forms of data based decision making. Its robotics and chatbots can project these functions beyond a computer, that is make them mobile and able to be projected from all sorts of other devices. One begins to see the ecologies, the networks, of automated action and decision making and interaction that together already provide a substantial connection between big data tech and its human users. It is now far more likely that these programs and applications in the aggregate will shape the terrains and interactions between tech and humans (individuals and collectives) from the bottom, than the current crop of top down efforts coming from traditional hierarchically superior human institutions. The flow of time makes less relevant any single instance of its memory recorded, for example, as law. It is therefore likely, as well, that legality must find of way of inserting itself back in time--to become automated in a sense.
Pix credit here |
Pix Credit Clip from the Movie Brazil here |
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