From af70440681dada72fa271d8cbc4bfc44548a8a96 Mon Sep 17 00:00:00 2001 From: Conrom007 <81521947+Conrom007@users.noreply.github.com> Date: Thu, 27 Jul 2023 14:21:13 +0300 Subject: [PATCH] Update README.md --- README.md | 22 +++++++++++----------- 1 file changed, 11 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index a456d5a..205037f 100644 --- a/README.md +++ b/README.md @@ -3,15 +3,15 @@

Public Sentiment and Stances on AI: Insights from Comments on Recent Developments

-Reading that this helpful new gadget, called ChatGPT, that just yesterday wrote an entire essay for your homework, might become as threatening as a nuclear war can be both unsettling and peculiar. Recently, industry leaders involved in AI development warned the public of how dangerous the unregulated development of AI systems can turn out to be. Artificial Intelligence systems are still a brave new frontier with most communities still uncertain of their limits and capabilities. Nonetheless, foreboding news easily turn into a magnet for internet denizens to flock around and voice their opinion.
+Reading that this helpful new gadget, called ChatGPT, that just yesterday wrote an entire essay for your homework, might become as threatening as a nuclear war can be both unsettling and peculiar. Recently, industry leaders involved in AI development warned the public of how dangerous the unregulated development of AI systems can turn out to be. Artificial Intelligence systems are still a brave new frontier with most communities still uncertain of their limits and capabilities. Nonetheless, foreboding news easily turn into a magnet for internet denizens to flock around and voice their opinion.

One such avenue was the corresponding article by the New York Times, informing the public of the unnerving one-sentence statement signed by more than 350 individuals actively involved in AI research and commercialization. More than 1400 comments were promptly posted under the article. As the advent of the next level of AI systems was sudden in recent years, the average view is still not firmly established. A lack of consensus appears to be the main take-away after a few glances in the first few comments, not very much unlike how experts are recently divided. As such, it was of interest to try and analyze the public’s tendencies around the matter.
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Sentiment Analysis

-In sentiment analysis, sentiment refers to the underlying emotion expressed in a piece of text. Through the analysis we aim to determine whether a given text expresses a positive, negative, or neutral sentiment, with the ultimate goal of reaching insights regarding public opinion. The process often uses various techniques varying from looking for specific keywords, to linguistic patterns or contextual information. Presently, however, the model we deployed relies on neural network architecture in order to learn from documents and classify sentiment.

+In sentiment analysis, sentiment refers to the underlying emotion expressed in a piece of text. Through the analysis we aim to determine whether a given text expresses a positive, negative, or neutral sentiment, with the ultimate goal of reaching insights regarding public opinion. The process often uses various techniques varying from looking for specific keywords, to linguistic patterns or contextual information. Presently, however, the model we deployed relies on neural network architecture in order to learn from documents and classify sentiment.

Our first step was to gauge the public sentiment based on the comments. The model used, developed here in UNIC’s AI Lab, is the perfect candidate for that task. The model is capable of reading textual documents and deciphering whether the sentiment hidden behind the words is positive, negative or neutral. We deployed the model on the comments and one can say the results are surely intriguing. As you can see in the following figure the public appears to be mostly split between positive and negative sentiments regarding the article’s content. While some are happy about what they read, others view the news in a negative light.


@@ -24,7 +24,7 @@ An interesting first insight, although what would be even more interesting is fi -Still, there was a feeling that we can learn more about those topics. We ended up diving deeper into what’s hidden in those clusters and uncover the most influential words that made the topics what they are.

+Still, there was a feeling that we can learn more about those topics. We ended up diving deeper into what’s hidden in those clusters and uncover the most influential words that made the topics what they are.