What is AI? Part 2, with Lucy Suchman | AI Now Salons

In our second of a two-part grounding conversation on “What is AI?”, Lucy Suchman draws connections between military logics, our own conception of intelligence, and how we map that onto AI as we know it.
How we conceptualize “intelligence” in neural networks and machine learning is crucial for how we understand this technology. AI does relatively well at identifying statistical patterns in closed-world data. But real, open-world environments are notoriously difficult for the field of robotics and machine learning writ large, and as such “engineering” the world these machines inhabit and draw data from becomes almost as important for their proper functioning as the algorithms underlying them. Ultimately, we need to understand the limitations of AI systems, their risks, and acknowledge the aspects of the world that resist automation.
Biography
Lucy Suchman, Professor Emerita at Lancaster University and an expert in AI and human-computer interaction, delves with us into what lies beneath AI as we know it today- its history as a subfield of computer science, its functioning as a technology that extracts meaning from vast datasets, and ultimately, as a term that defies precise definition, sometimes to the benefit of the corporations behind its current form.

[@ScottGaul]

Wow. When I clicked through to your channel I had no idea I was going to be absorbed by a highly intelligent conversation about AI and military power. As a guy I can now breathe a sigh of relief - I have hope! I now see how highly intelligent women will likely be able to save the world. 🙂A deep bow of gratitude for your efforts.

[@toad3877]

Learned so much from this too - and a note that women and men alike engaging in thoughtful, compassionate discussion like this is what saves the world! We are a cooperative species after all

[@ScottGaul]

@@toad3877 Well said.

[@erikljungberg1056]

AI is not trained in a closed world. In fact, there could never be a part of the world that is closed off from the rest of everything else. This is a counter-intuitive point that our conventional mental models have a hard time holding. When you are interacting with Chat-GPT, you are in a sense interacting with an externalized part of the collective human experience. There is continuity between words written many hundred years ago and the magnetic zeros and ones in OpenAI's training data. Meaning is non-local and does not obey the rules of Newtonian space. Two things can be connected without sharing the same time or space. Meaning can work like that, though we don't really understand what meaning is, and how it can exist in the universe.