Readings #2

Intelligence on Tap, by Lars Erik Holmquist

In this article, Holmquist clearly explains how artificial intelligence works while referencing how an AI beat the world’s best Go player. He explained how the AI learned from playing the game against others and ultimately himself, learning different tactics and such. I find that AI are able to learn from interacting with others the most interesting aspect of this subject. I remember in Freshman year, I researched and wrote an essay about the AI named Tay. Tay was an AI given an account Twitter and she was able to learn from interacting with other Twitter. What started off as an innocent and fun idea, turned sour really fast as Tay was turned into an AI that started tweeting racist and horrible slurs against others… all because she learned from the “trolls” of the internet. It is incredibly exciting to able to begin looking at AI as a design material and see what sort of advancements and new products/objects/systems can be developed, however it doesn’t hurt to be wary of how society can influence a machine that is trying to pick up some human behaviors.

UX Design Innovation

As I read through UX Design Innovation, I could completely relate to the research done with surveying UX designers, as some stated they felt that machine learning was near “black magic.” I personally have never done much digging about how machine learning could be utilized further as a design tool, or would require designers. Any research I have done as been on my free time and I never took the information I learned further than what was stated in any articles or videos. However, after reading this paper, there’s a lot more potential and need for designers to step in and design along side engineers machine learning objects. But there is much needed compromise on both parties to try and communicate findings and how even prototyping would function on this topic.

Machine Learning Culture

I have never really thought about it, but I have experienced machines learning culture in relation to art quite a few times in the past few years. Being from northern Virginia, I have always made numerous trips to Washington D.C. to explore the city and the museums it has to offer. As I read through the Body Tracking and Provocative Art Installations portion of this paper, I realized that I have constantly experienced machine learning in the D.C. museums I explored in these past years, and never made the connection. I can think of two museums that would display collections that would contain some form or aspects of machine learning: ARTechouse and the Hirshhorn. Both museums brings in modern and contemporary collections from all over the place,  and although I cannot specifically remember a display (I’m sure it’ll come to me soon enough), it’s amazing I have never thought about how machine learning is even integrated into museums I love exploring.

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