What Comes After Minds? (REVIEW)

What comes after minds? by Marvin Minsky. From The New Humanists: Science at the Edge (2003). Edited by John Brockman. Barnes & Noble Books: New York.

Key quotes

• “No uniform scheme will lead to machines as resourceful as the human brain. Instead, I’m convinced that this will require many different ‘ways to think’ - along with bodies of knowledge about how and when to use them”.
• “Computer science has helped us envision a far wider range of ways to represent different types and forms of knowledge,…”
• “I see each emotional state as a distinctly different way to think”.

Summary

What I like best about this brief introduction to some of Marvin Minsky’s thinking is his reminder of the value of mind modeling. In the early days of cognitive science, back before neuroscience’s explosion onto the scene and the advances of computer modeling, we were left with modeling mental processes and testing theories based on that which could be observed. While this approach had its limitations, it did yield some rather adventurous thinking as to what might be happening inside our minds; a tradition of thinking about thinking that one can argue, as Minsky does, has dried up in recent years, thereby closing off research paths worthy of investigation.

This piece includes a reminder of Freud’s concept of a suite of collaborating and competing mental functions, which offers insights into what can be experienced as a host of multiple agents at play in the mind. This collection of cognitive action figures, including the Id, the ego, and the superego, could potentially establish a point of departure for AI programming. And, as I must say out loud to myself whenever referencing anything relating to Freudy, we can hold our shame and dissapointment in Freud’s re-writing of his patient’s abuse testimonials while at the same time considering his articultion of mental models. Acknowledging the value of the latter, does not dim the light of our judgement of the former.

Minsky spells out some of the cool things humans can do, that we, thus far, have not been able to inspire computers to do. This includes our facility with using multiple representations, our emotions, and shifts between vast collections of knowledge. His theories regarding emotional states caught my eye, and I will be following up on that research in my review of his book The Emotion Machine.

And finally, the author’s brief nod to computers perhaps one day upping us in the process of recording data was exciting. In general, I find myself taking away from this article a sense of “hey, were not as dumb as we look”, while at the same time re-committing to the program of exploring computing the possibilities of computing beyond our capabilities, particularly in regards to ideating the sub-strata of arenas of innovation addressing climate change and the reduction of suffering. If AI processing is skewed in favor of single functions, let’s ensure our labs focuss on the most useful single functions.