When it seems the entire world is doubling down on Artificial Intelligence (AI), we’re doubling down on Artificial Collective Intelligence (ACI). We’re not simply being obstinate, we actually think we’re onto something that matters. Before you write us off, bear with me while I explain our thinking. Still unsure? Run the little experiment at the end. Sorry ahead of time for any forthcoming heartache.
It’s just adding one word at a time. As Stephen Wolfram so perfectly summarises in his wildly intelligent (but wildly complex) article about how ChatGPT works, it’s simply adding one word at a time - albeit, rather intelligently. We’ll save you the trouble of reading the piece, but said with a bit more detail, think of it in three simple elements:
Simplified this way, it’s quite easy to see how AI technology, like ChatGPT, can appear helpful, but perhaps cause more issues in the long run if not given guidance and not sense-checked. This is also why a lot of AI-generated text can read and sound very “flat”.
So, while ChatGPT, a form of AI, on its own, doesn’t solve everything, let alone fully replace jobs, it (and Large Language Models in general) can accelerate certain graduate-level tasks while producing a high-quality output. Examples might include:
These tasks, normally given to humans, would certainly take far longer to complete. AI systems get them done quickly and efficiently, and at a quality-level worth recognizing. But the humans aren’t out of a job just yet.
Okay, before we go deeper, let’s make sure we’re on the same page with terms.
We at AGM think LLM is promising but flawed on its own and AGI, while also interesting, is years and years away (and will probably still require humans). This leads us to:
ACI, or Augmented Collective Intelligence, refers to the integration of artificial intelligence with human intelligence to enhance the collective intelligence of a group of individuals or a network. It involves the use of Al to support human decision-making, collaboration, and knowledge management, among other tasks. ACI systems are designed to augment human intelligence and work in partnership with people.
Simply put: we’re supercharging our humans.
Putting LLM-based tools in the hands of an intelligent human supercharges them: quantity of work and quality of work improves.
The deployment of LLM and AI to our teams globally not only democratises certain cognitive tasks but also accelerates our ability to iterate. Go with us on this one:
Cool, no problem. You already have Apple’s LLM at your fingertips (and you don’t use it).
Point is: you might use AI to assist, edit or expand, but you don’t use it on its own.
We won’t either. Environment, experience and expertise still matter.
In the weeks ahead, we’ll be moving past the philosophical to breakdown how we’re deploying ACI across our services and solutions globally. It’s pretty cool - namely because our humans are still involved and getting supercharged by the minute.
Have a pressing question? Get in touch here.