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What if New York City Mayor Andrew Yang Is … a Good Idea?

Slate

Andrew Yang will not forestall the robot apocalypse from the Oval Office, but he may get to do it from New York City Hall. In the 2020 Democratic presidential primary, the former entrepreneur's quirky campaign found a surprisingly robust audience, attracted by Yang's warnings about automation and his promise to mail every American a "freedom dividend" (or, at least, by his math jokes and laid-back, open collar). In the end, the Yang Gang only got their guy as far as the New Hampshire primary. But thanks in part to the name recognition and national network of donors he accrued during that race, Yang is actually leading the polls this year's contest to be the Democratic candidate for New York City mayor. On Friday, Henry Grabar and Jordan Weissmann, two of Slate's native New Yorkers, convened to debate whether this is a good thing. Their debate has been edited and condensed for clarity.


Over a Decade of Social Opinion Mining

arXiv.org Artificial Intelligence

Social media popularity and importance is on the increase, due to people using it for various types of social interaction across multiple channels. This social interaction by online users includes submission of feedback, opinions and recommendations about various individuals, entities, topics, and events. This systematic review focuses on the evolving research area of Social Opinion Mining, tasked with the identification of multiple opinion dimensions, such as subjectivity, sentiment polarity, emotion, affect, sarcasm and irony, from user-generated content represented across multiple social media platforms and in various media formats, like text, image, video and audio. Therefore, through Social Opinion Mining, natural language can be understood in terms of the different opinion dimensions, as expressed by humans. This contributes towards the evolution of Artificial Intelligence, which in turn helps the advancement of several real-world use cases, such as customer service and decision making. A thorough systematic review was carried out on Social Opinion Mining research which totals 485 studies and spans a period of twelve years between 2007 and 2018. The in-depth analysis focuses on the social media platforms, techniques, social datasets, language, modality, tools and technologies, natural language processing tasks and other aspects derived from the published studies. Such multi-source information fusion plays a fundamental role in mining of people's social opinions from social media platforms. These can be utilised in many application areas, ranging from marketing, advertising and sales for product/service management, and in multiple domains and industries, such as politics, technology, finance, healthcare, sports and government. Future research directions are presented, whereas further research and development has the potential of leaving a wider academic and societal impact.


Brad Parscale accuses 'D-level' 'talking heads' around Trump for forcing him out of 2020 campaign

FOX News

Former Trump campaign manager reacts to 2020 election results in exclusive interview on'The Story' Former Trump 2020 campaign manager Brad Parscale has accused "D-level" "talking heads" in the president's orbit of starting a whisper campaign that forced him out earlier this year. Speaking with Fox News' Martha MacCallum in an exclusive interview on "The Story" Tuesday night, Parscale alleged that "when the polling numbers were going down, they were in his ear and I was out working." Discussing a reported incident in which Trump berated Parscale for passing along a bad polling report, the former campaign manager said: "I didn't like lying to him -- I like telling the truth. Sometimes that comes with a lot of painful days, knowing that I might let him down or make him upset, but a lot of the D-level people that hung around him told him what he wanted to hear: They were'yes' men. I wasn't going to be'yes' man, but a'get it done' man." Parscale did not name anyone as being specifically responsible for his ouster in mid-July, when he was replaced by Bill Stepien.


Biden transition 'moving forward,' awaiting GSA confirmation of election results

FOX News

Here's what you need to know as you start your day ... Biden transition hangs in limbo, awaiting GSA certification for results to become official The Biden transition is hanging in limbo, awaiting the General Services Administration's certification, which will give President-elect Joe Biden and his team the power to make decisions about the future of the federal government-- but the incoming administration is "moving forward" anyway, urging the GSA to "move quickly" and "respect" the "will of the American people." A Biden-Harris transition spokesperson told Fox News that the transition "is moving forward with preparations so that President-elect Joe Biden and Vice President-elect Kamala Harris are ready to lead our country on Day One and meet the pressing challenges facing our nation." The GSA has not yet made an "ascertainment" decision -- the formal declaration set up by the 1963 Presidential Transition Act. Until that ascertainment is made, the Biden team can not formally begin the transition process. The GSA has defended its precedent, which they said was "established by the Clinton Administration in 2000."


Detecting Social Media Manipulation in Low-Resource Languages

arXiv.org Artificial Intelligence

Social media have been deliberately used for malicious purposes, including political manipulation and disinformation. Most research focuses on high-resource languages. However, malicious actors share content across countries and languages, including low-resource ones. Here, we investigate whether and to what extent malicious actors can be detected in low-resource language settings. We discovered that a high number of accounts posting in Tagalog were suspended as part of Twitter's crackdown on interference operations after the 2016 US Presidential election. By combining text embedding and transfer learning, our framework can detect, with promising accuracy, malicious users posting in Tagalog without any prior knowledge or training on malicious content in that language. We first learn an embedding model for each language, namely a high-resource language (English) and a low-resource one (Tagalog), independently. Then, we learn a mapping between the two latent spaces to transfer the detection model. We demonstrate that the proposed approach significantly outperforms state-of-the-art models, including BERT, and yields marked advantages in settings with very limited training data-the norm when dealing with detecting malicious activity in online platforms.


Have Deepfakes influenced the 2020 Election?

#artificialintelligence

Media manipulation through images and videos has been around for decades. For example, in WWII Mousollini released a propaganda image of himself on a horse with his horse handler edited out. The goal was to make himself seem more impressive and powerful [1]. These types of tricks can have significant impacts given the scale of people that see images like these, especially in the internet era. DARPA has an entire program constructed just to develop methods for detecting manipulated media through their media forensics (MEDIFOR) [2].


2020 election: Artificial Intelligence has chosen a winner - Report Door

#artificialintelligence

Artificial intelligence has chosen a winner for the 2020 presidential election -- but there's a catch. Hernan Makse is a statistical physicist at City University of New York who runs the Complex Networks and Data Science Lab at the Levich Institute in Manhattan. His lab uses AI to predict the outcomes of international elections using social media traffic, focusing mainly on Twitter, a platform with over 48 million monthly active users in the US. "We usually start one year from the election, and then we use that data to train the machine and predict the outcome of the election at the national level," he said in a recent interview with The Independent, noting how AI can now also be used to predict local and state election outcomes after data is organized by geolocation. "Predicting elections is, of course, quite complicated."


AI Weekly: The election

#artificialintelligence

In the United States, there was nothing else this week except for the presidential election. More people voted in this election than in any other previous U.S. presidential election -- a total of 143,518,226 votes and counting. As we close out a long, stressful week, it appears all but a formality that Joe Biden and Kamala Harris will be the country's next President and Vice President. Meanwhile, Donald Trump rages on in a toothless effort to hang onto power. The results of the election were not the resounding referendum against white supremacy, misogyny, xenophobia, and bigotry that many had hoped for. But at least the fears about how technology could tip the scales of this election didn't apparently come to pass -- many were concerned about numerous threats from (or enabled by) technology, from deepfakes to bots to hacking.


Artificial Intelligence Shows Potential to Gauge Voter Sentiment

#artificialintelligence

The Morning Download delivers daily insights and news on business technology from the CIO Journal team. "I wouldn't fire the pollsters, but I would direct them to try to leverage machine learning, data mining and AI in their work more to get better projections," said Oren Etzioni, chief executive of the Allen Institute for AI, a nonprofit research center in Seattle. The size of this year's polling error is still unknown as the vote count continues. But polls generally predicted clear Democratic gains, not cliffhangers. No person or algorithm can predict human behavior accurately all the time, said Heidi Messer, chairman of New York-based Collective[i], which offers AI and predictive technologies for sales teams.


Artificial Intelligence Shows Potential to Gauge Voter Sentiment

WSJ.com: WSJD - Technology

The Morning Download delivers daily insights and news on business technology from the CIO Journal team. "I wouldn't fire the pollsters, but I would direct them to try to leverage machine learning, data mining and AI in their work more to get better projections," said Oren Etzioni, chief executive of the Allen Institute for AI, a nonprofit research center in Seattle. The size of this year's polling error is still unknown as the vote count continues. But polls generally predicted clear Democratic gains, not cliffhangers. No person or algorithm can predict human behavior accurately all the time, said Heidi Messer, chairman of New York-based Collective[i], which offers AI and predictive technologies for sales teams.