Technoculture
Understanding intelligence, whether we describe it as artificial or not, is an ongoing process.
Discussions about what defines intelligence and the technologies that we now refer to as Artificial Intelligence are not new and reach back into antiquity.
Personally, I don't love the term Artificial Intelligence for a few reasons. Technoculture recognizes that AI is a natural outcome of the process of technological evolution, which itself is a natural extension of the Biosphere. As technology is an inherently natural phenomenon, AI is in this sense not quite artificial. Because definitions of intelligence depend on a great deal of context and are everchanging, this word might limit our understanding of what AI actually is.
Understanding AI means understanding non-human intelligence, a vast endeavor in and of itself rooted in a post-humanist philosophical outlook that parallels the practices and philosophies of many indigenous cultures.
It will require us to examine the implications of defining intelligence and subsequently training AI around primarily Western, White, and cisheteronormative concepts of the mind. It requires us to decenter human thought as the pinnacle of consciousness and cognition and follow the thread of mind that might be present in all parts of nature.
In this section, we'll learn about the fundamental principles that underpin what we define as AI, some of the specific technologies that make it possible, the applications, and how our understanding of it all continues to evolve.
Currently (2025), most of the dialogue around AI advancements centers around what its implications are for certain careers & markets (namely media, entertainment, education) but is rapidly expanding to more fields, raising concerns about the broader labor markets. In addition to this, the major corporatized drivers of AI (Open AI, Grok, Chat GPT, etc) train and operate their models with extractive, biased data, powered by large-scale data centers that only accellerate the potential for misinformation and compound already worsening climate change effects due to their demand for water and energy.
AI in many ways represents a synthesis of all the ills of the current socioeconomic & geopolitical structure, from climate to wealth inequality, to embedded racial and gender bias. The significance of the potential existential risks are as great as the possible benefits are wide. The anticipation of this trajectory is what motivated me to start YOO. Alongside many other smaller teams building their own models, we too are aiming to develop AI in an equitable way. This includes relying on renewable energy soures, ensuring users consent to train on their data, and that citizens of our platforms own part of the value of the models. There is a wide spectrum of various kinds of AI companies that are aiming to do things better. You can find many of them in my AI toolkit channel on Are.na. In addition to these more pressing, present-day challenges, I have also worked to develop economic frameworks that could curb much of the economic fallout made possible by ever-advancing AI development. I personally think it reasonable to assume that any profession could adequately be absorbed by AI & robotics and it’s essential to create social safeguards, an economic safety net for this exact reason. AI only adds to the already known reality; we need a fundamentally new economic model. There are many other ethical conserns tht AI raises (can we really trust biased AI models to translate the language of whales?), many of which I am actively researching and/or outlining frameworks for. On the increasinly less speculative side, I have also developed a framework that could in principle ensure that actual sentient, intelligent AI can actually consent to the role, task or labor they may be asked to do, lest we recreate the conditions of enslavement for our nonhuman kin.
Artificial intelligence is currently defined as the intelligence of machines or software, as opposed to the intelligence of humans or animals. It is a field of study in computer science that develops and studies intelligent machines. Such machines may be called AIs.
The four functional types of AI are:
- Reactive Machines.
- Limited Memory.
- Theory of Mind.
- Self-aware.
Artificial general intelligence (AGI) is a hypothetical type of AI that can learn, understand, and perform tasks as well as humans. AGI is a theoretical goal that researchers are working towards.
How AGI differs from other AI
- Cognitive capabilities: AGI can match or exceed human cognitive abilities, while narrow AI is limited to specific tasks.
- Learning: AGI can learn new skills and solve complex problems in new situations.
- Knowledge: AGI has a vast knowledge of the world, including facts, relationships, and social norms.
AGI's potential benefits Increasing the abundance of resources, Turbocharging the global economy, and Discovering new scientific knowledge.
Robot
Origin
1920s: from Czech, from robota ‘forced labor’.
The term was coined in K. Čapek's play R.U.R. ‘Rossum's Universal Robots’ (1920).