Where is my data when it’s in a cloud?

I recently stumbled upon a cool Atlantic piece from a couple of year’s ago by Rebecca Rosen – Clouds: The Most Useful Metaphor of All Time? I was looking for metaphors used to talk about the internet, and of course the cloud is a ubiquitous one. I also find it a confusing one. I own that Kindle book, so why isn’t it on my iPad? or I wrote that note on my phone, so how’d it get in my email drafts? How is it that my cloud is “full?” Although I haven’t invested much time in learning about the internet cloud, Rosen’s Atlantic piece suggested that my confusions are more logical than I gave myself credit for. Clouds are used (both graphically and linguistically) for concepts that are vague and fuzzy:

What is it about clouds that has such sticking power? Clouds get traction as a metaphor because they are shape-shifters, literally. As a result they can stand in for many varied cultural tropes. Want something to represent the one thing marring your otherwise perfect situation? Done. Want to evoke the nostalgic feeling of childhood games of the imagination? Done. Maybe you want to draw a picture of heaven? You’re in luck. Clouds as metaphors pepper our language: every cloud has a silver lining, I’m on cloud nine, his head is in the clouds, there are dark clouds on the horizon. Clouds are the lazy man’s metaphor, a one-image-fits-all solution for your metaphor needs.

cloud1
But what does this mean!? https://blog.mysms.com/why-use-cloud-services.html

The point of clouds is that they’re vague. And in fact, how much do we really know about them, despite the fact that we see them almost every day? We do often talk about things we don’t understand in terms of other things we don’t understand. For example, to talk about love (a hard-to-understand idea), we often draw on terms from chemistry (an even harder-to-understand one). And even though we don’t really understand the metaphorical domain (chemistry), we feel like we understand the source (love) a little better thanks to our metaphorical use. So it is with clouds. For someone being introduced to the idea of the Internet’s cloud, they might initially get the gist pretty quickly – just as a cloud floats around in the sky, my data is floating around somewhere (or at the least, it’s not solely on my device). But then once you start using your cloud – accumulating books, songs, and documents – your understanding might become foggier. Because how do you get something back when it’s in a cloud? Wait for the rain? Jump on a plane? I’m still trying to figure this one out.

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Facebook and the Chinese Room

Image: http://www.technologyreview.com/news/519411/facebook-launches-advanced-ai-effort-to-find-meaning-in-your-posts/
Image: http://www.technologyreview.com/news/519411/facebook-launches-advanced-ai-effort-to-find-meaning-in-your-posts/

A recent assignment had me revisit Searle’s thought experiment referred to as “the Chinese room” and the debate of whether machines can understand as humans do. He puts forward this scenario: He doesn’t know any Chinese, but is sitting in a room with  reference books that allow him to produce coherent written responses to any message he’s given in Chinese. Thus, the person outside the room receiving his responses will believe that the person understands Chinese, when in reality, there is no understanding going on. Searle uses this as an analogy for computer programs- even if a computer program can produce logical or correct or sophisticated outputs, it doesn’t truly understand what it’s computing. Computers simulate intelligence but simulation is not sufficient for true consciousness or to be considered a “mind”.

Searle first wrote about the Chinese Room in 1980, but when I just recently read about the deep learning, the most current advance in artificial intelligence, I couldn’t help think that the Chinese Room is still quite pertinent. The process of deep learning is accomplished by a network in which connections among concepts. The smallest concepts form one layer, and above them are slightly larger ones, and so on, so that to retrieve information, the network doesn’t have to search a massive pool of data, but instead has to find the right associations between data (a much less onerous computational task). The name “Deep Learning” alone is telling to me because typically only humans, or agents with human cognitive capacities, can truly learn. If it helps make my Facebook newsfeed more interesting (i.e., excludes status updates from those random people from elementary school I’ve just never gotten around to unfriending), that’s great. But have technological innovations like this one brought us closer to a feeling that true artificial understanding is achievable (or already achieved?)

Tribute to Turing

Ever since I learned about Alan Turing in my introductory cog sci class, I knew he was someone pretty important in the field. Come to find out, he’s important in a lot of fields. He’s considered the father of AI and computer science thanks to his formalization of the concepts of algorithms and computation with the Turing machine, and is known for his belief that computers could be programed to “think.”

He was also very helpful to Britain during WWII by helping crack codes and German ciphers, but he was prosecuted in 1952 for homosexual acts, which were illegal at the time. He ended up committing suicide (most likely because of these accusations) by ingesting cyanide. Just this week, he was formally pardoned by the British government.

In reference to his fear that because of his homosexuality, his beliefs would not be taken seriously, Turing wrote to a friend:

Turing believes machines think

Turing lies with men

Therefore machines cannot think.

Turing has had a pretty huge impact on the world- for example, the computer as we know it would not exist without him. Although his life ended tragically and prematurely, it’s exciting to see that an effort is being made today, over 50 years after he died, to bring about a little bit of the justice he deserves.

Image: http://www.cs.utah.edu/~draperg/cartoons/2005/turing.html
Image: http://www.cs.utah.edu/~draperg/cartoons/2005/turing.html