Searle introduced 1983 in his writings the aspect of intentionality as a fundamental bridge between the philosophy of language and mind. In essence, he postulated that mental states are always in some relation to the real world. In other words, if I think that a tree is (from my perspective) made out of hard wood, the thought refers to trees that are made of of material that is hard (seen from a human perspective) in the real world. Waow, right? While this sounds super obvious, this framework to think within, allows thoughts to be verifiyably false or true to begin with.

While intentionality has many more facetts, especially in the realm of AI, a thing that always bothered me from an epistemological stand point is that for this to hold true, the world has to be devisable into a binary yes and no. For example, my coffee can be 60° celsius hot or not. I can verify this information easily by measuring the temperature (yes/no). However, what if it is not universally 60° celsius everywhere, perhaps a bit cooler at the surface? Theoretically, you could argue that this also can be converted into a binary statement such as : Is the coffee everywhere 60° hot or not (yes/no). Yet, this is where Searle postulated that we sometimes confuse the intrinsic features of something with the ones we interpret into them.

If I were to put my coffee on a table, simply because it is flat, wooden, sturdy, you could argue, that I understood the intrinsic traits of a table. If I were not in my office, but rather a forest, searching for a place to put my coffee, the thought may arrise that I can put it on a treestump, afterall it is flat, made out off wood, and sturdy. Even better, knowing the intrinsic features so well, I could postulate that a treestump is a table and a table is a treestump. Fundamentally, I demonstrated that by confusing both the features I interpret as similarities, I ignored their differences.

This is why intentionality ‘feels’ wrong to discuss in the framework of a Von Neumann based architecure that is rooted in binary operations (the basis for the computers we all use and know) to me. Even if we were to fully understand the brain, a transferal of these processes through an interpreter layer, similar how programming languages are processed for assembly, doesn’t guarantee success. If this would be the case, I could simply take a working motorblock made out of metal and rebuild it with wood, expecting the same result. (In the light of other technologies (quantum- & neuromorphical computing), this interpreter layer would also remove all the benefits of them.) And these are only some of the devils in the details, where we’re not even scratching the surface that general relativity fails us completely beyond the molecular level (hello quantum mechanics, goodbye yes/no).

To circle back: To verify if my coffee is universally 60° celsius or not I already make the assumption that I can make binary statements about it, which could potentially be a feature I interpret into something, over a trait it intrinsically has by its own.

As scalability of AI plateaus, requiring more processing power to grow, the obvious bet would be quantum computing. The other candidate would be neuromorphical computing, which is the attempt to replace the Von Neumann architecture with what seems to be more closely related to our brain. One major development is the ability to replicate spiking. In essence, if I were to see a wolf in a forest, my brain immediately triggers a fight or flight reflex by forwarding signals directly to their respective areas required for such action. An AI, while still mimicking neuronal networks through their node system, has to filter this signal through many more layers of abstraction to have a chance to produce a result that is similar to mine (it is heuristic at the end of the day, hence I say chance). While capable of mind boggling feats, this still doesn’t remotely hold up a candle to the computing power of our brains. On the other hand, it wasn’t too long ago that microprocessors weighted tons, so who knows who’ll win this race and how.

Circling back to intentionality, we certainly find many barriers in understanding or discovering intentioanlity. Some might argue, that we as humans do not act with intentionality constantly; if we’re going to the grocery store, we do not intentionaly set one foot in front of the other or decide actively if we cross the street only when the pedestrian traffic light is green, we’re almost automated in such situations. However, cutting ourselves loose from the Von Neumann architecture and binary thinking seems to me to advance us one step further into potentially building an understanding of this matter.

For me, the most interesting aspect of these thoughts are the questions they raise:

• If intentionality is theoretically possible in all systems architectures, how does it differ from binary, neuromorphical and quantum computing? Are there many different kinds of intentionality?
• What if we were to combine aspects of both, such as the aspect of shortcuts in spiking with the power of quantum computing and how would that affect intentionality?
• Is the world of chances (such as in quantum computing) applicable to our brains thought process, such as in the spontaneus generation of ideas?
• Is intentionality scalable? In other words, is it a trait of a thing, a system or group?
• Can intentionality even be discovered in a binary capacity or are there gradients of intentionality?
• In the realm of comparability between entities holding intentionality, are there things, groups or systems that are incompatible with each other, because of their different intentionalities?
• Are there parallels between intentionality of a single entity and a system?
• Is intentionality subject to undergoing change, such as maturing or aging?
• If I were to loose all my senses, would I loose intentionality? Is a “brain in a jar”, without any stimuli capable of intentionality?
• Can intentionality be understood in a true/false context and does Searle ultimatively, potentially confuse intentionality as intrinsic instead of interpreted features?
• How can Infected Mushrooms release such a banger of an album out of nowhere.