Collaborating Authors

Voting & Elections

Meta AI Makes Interesting Revelation about its CEO Mark Zuckerberg


Meta's new chatbot has made the day for many on social media after giving honest opinions about its own boss, Mark Zuckerberg. The company recently released a new chatbot called BlenderBot 3, and the internet took it on a test run. A lot of users, including the media, also asked Meta AI about its opinion on the company's founder, to which it gave some interesting answers. The system can chat with a human on almost every topic by searching the internet. Meta previously warned that the chatbot could be "rude" or "offensive" to some as it "learned" the human language from widely available public data.

It took just one weekend for Meta's new AI Chatbot to become racist


Just when you think life online can't get worse than it already is, Meta steps in to prove you wrong. The company's new BlenderBot 3 AI chatbot -- which was released in the U.S. just days ago on Friday, August 5 -- is already making a host of false statements based on interactions it had with real humans online. Some of the more egregious among those include claims Donald Trump won the 2020 U.S. presidential election and is currently president, anti-Semitic conspiracy theories, as well as comments calling out Facebook for all of its "fake news." This, despite being owned by the company formerly known as Facebook. Meta's BlenderBot 3 can search the internet to talk with humans about nearly anything, unlike past versions of the chatbot.

Topmost Three Dangers of Artificial Intelligence


"Mark my words; AI is far more dangerous than nukes" Elon Musk AI has a massive impact on our social thinking process. The impact is positive as well as negative. We use mobiles phones, robots, self-driving cars, etc., excessively. Majority of us come into contact with Artificial Intelligence in some capacity or the other virtually daily. AI has fast contracted into our lives.

Congratulations to the authors of the #IJCAI2022 distinguished papers


The IJCAI distinguished paper awards recognise some of the best papers presented at the conference each year. This year, three articles were named as distinguished papers. The winners were selected by the associate programme committee chairs, the programme and general chairs, and the president of EurAI. Abstract: The metric distortion framework posits that n voters and m candidates are jointly embedded in a metric space such that voters rank candidates that are closer to them higher. A voting rule's purpose is to pick a candidate with minimum total distance to the voters, given only the rankings, but not the actual distances.

How we used machine learning to cover the Australian election


During the last Australian election we ran an ambitious project that tracked campaign spending and political announcements by monitoring the Facebook pages of every major party politician and candidate. The project, dubbed the "pork-o-meter" (after the term pork-barreling), was hugely successful in being able to identify distinct patterns of spending based on vote margin, or incumbent party, with marginal electorates receiving billions of dollars more in campaign promises than other electorates. All up, we processed 34,061 Facebook posts, 2,452 media releases, and published eight stories (eg here, here and here) in addition to an interactive feature. We also used the same Facebook data to analyse photos posted during the campaign to break down the most common types of photo ops for each party, and how things have changed since the 2016 election. We were able to discover more than 1,600 election promises, amounting to tens of billions of dollars in potential spending.

Artificial intelligence


Deep learning[133] uses several layers of neurons between the network's inputs and outputs. The multiple layers can progressively extract higher-level features from the raw input. For example, in image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits or letters or faces.[134] Deep learning has drastically improved the performance of programs in many important subfields of artificial intelligence, including computer vision, speech recognition, image classification[135] and others. Deep learning often uses convolutional neural networks for many or all of its layers.

Can artificial intelligence and democracy co-exist?


Some people see artificial intelligence as a danger to democracy; others see it as a huge opportunity. Researchers and experts explain how algorithms and big data are deployed in Switzerland – and how they aren't. Voting in Switzerland takes place every three months. Fierce debates take place before the referendums, and the tone can be particularly aggressive online. Insults, pure hate and even murder threats are not unusual.

La veille de la cybersécurité


The novelty cheque has long been a mainstay of the political "photo op" but a Guardian Australia analysis of photos posted during the 2022 and 2019 election campaigns suggests giant cheques are on the way out, while hi-vis workwear and photos of dogs are on the rise. During our work building the automated systems behind the pork-o-meter, which tracks election campaign pork barrelling as it occurs, the Guardian's data team found ourselves asking an important question. Could we teach a robot to spot photos of novelty cheques? We were already using machine learning to flag text from politicians' Facebook posts as likely grant announcements and election promises, but having another model in place to find big cheques and certificates in photos might pick up things we'd missed in the text.

Politics, Machine Learning, and Zoom Conferences in a Pandemic: A Conversation with an Undergraduate Researcher


In every election, after the polls close and the votes are counted, there comes a time for reflection. Pundits appear on cable news to offer theories, columnists pen op-eds with warnings and advice for the winners and losers, and parties conduct postmortems. The 2020 U.S. presidential election in which Donald Trump lost to Joe Biden was no exception. For Caltech undergrad Sreemanti Dey, the election offered a chance to do her own sort of reflection. Dey, an undergrad majoring in computer science, has a particular interest in using computers to better understand politics.

ACM's 2022 General Election

Communications of the ACM

The ACM constitution provides that our Association hold a general election in the even-numbered years for the positions of President, Vice President, Secretary/Treasurer, and Members-at-Large. Biographical information and statements of the candidates appear on the following pages (candidates' names appear in random order). In addition to the election of ACM's officers--President, Vice President, Secretary/Treasurer--two Members-at-Large will be elected to serve on ACM Council. The 2022 candidates for ACM President, Yannis Ioannidis and Joseph A. Konstan, are working together to solicit and answer questions from the computing community! Please refer to the instructions posted at Please note the election email will be addressed from Please return your ballot in the enclosed envelope, which must be signed by you on the outside in the space provided. The signed ballot envelope may be inserted into a separate envelope for mailing if you prefer this method. All ballots must be received by no later than 16:00 UTC on 23 May 2022. Validation by the Elections Committee will take place at 14:00 UTC on 25 May 2022. Yannis Ioannidis is Professor of Informatics & Telecom at the U. of Athens, Greece (since 1997). Prior to that, he was a professor of Computer Sciences at the U. of Wisconsin-Madison (1986-1997).