Dan Harrell, "Our Problem with the Problem with Technology"

Graduate Institute Summer Lecture Series | "Our Problem with the Problem with Technology"
Speaker: Dan Harrell, St. John's College Tutor

[@wordswords2094]

Exceptional. I have an old St John's Catalog which I cherish. Indeed, it felt quite different. Thank you for acknowledging the changes, trying to sort out the implications, and adhering to the core. Classical literature and themes have always had a habit of holding great social weight at some times, while in other times (Dark Ages, conquering foes) they fall into disregard. However, they will always prevail because of their resonance with the human experience. Please stand firm through this possible Dark Age.

[@ladyoftheflowers9781]

An interesting lecture... As a graduated Johnnie who dabbles in tech, I would like to say that there are many ways Dan Harrell may have misunderstood the nature of technology. Indeed one can think of technology as concealment as Heidegger did, but now I would say the nature of technology has changed. I would say abstraction is far better than concealment. For example, I write a script in Python to do a task. This script is interpreted and machine language is passed to the computer. This code can work on any operating system since Python code is not compiled like C. Technology stands on the shoulder of giants to abstract processes so we can be more creative. While Frege and other authors did establish computability (and indeed a computer essentially functions on these ideas), I do think we should also focus on hardware. The development of the transistor and overall the field of VLSI has revolutionized technology. Anyone who has taken digital logic 101 will know that the hardware is performing logical operations using the principles of chemistry and physics. And thus the computer serves as a paradigm of true abstract thinking and logic. We do not study logic per se at the college, which perhaps may explain why Johnnies are not immediately fascinated by things like decoders, multiplexers, and registers. His comments on ChatGpt are also off, I think. ChatGpt does not think. A LLM uses an algorithm that works on simple principles (pretty much backpropagation), but no one understands how the large models work as a whole. In addition, generative AI has been shown to become more and more unoriginal as it is trained. There are many inherent problems with AI currently that it seems highly improbable that AI can actually think for us. It is ultimately our attribution of thinking that makes it so, i.e. the ghost in the machine. Right now technology could use Johnnies. Divergent and critical ways of thinking are necessary. AI has devolved into a bunch of people who do not think deeply about what they are doing. They think only about accuracy, loss, objective functions, and precision. They miss the forest for the trees. Moreover technology is deeply aesthetic. One need only read Manfred Clynes book on Sentics or Rosalind Picard's Affective Computing to see the beginnings of profound technological creation. Technology provides a new perspective in which one can immerse themself in the liberal arts. We can even illuminate our study of Faraday by building circuits on perfboard and observing the flow of electrons. Fascinating stuff! I myself was enchanted by the beauty of the full wave rectifier and how its simple principles allowed us to deliver and use electricity more effectively. I hope more Johnnies go into tech! Cheers!