Political discourse datasets are important for gaining political insights, analyzing communication strategies or social science phenomena. Although numerous political discourse corpora exist, comprehensive, high-quality, annotated datasets are scarce. This is largely due to the substantial manual effort, multidisciplinarity, and expertise required for the nuanced annotation of rhetorical strategies and ideological contexts. In this paper, we present AgoraSpeech, a meticulously curated, high-quality dataset of 171 political speeches from six parties during the Greek national elections in 2023. The dataset includes annotations (per paragraph) for six natural language processing (NLP) tasks: text classification, topic identification, sentiment analysis, named entity recognition, polarization and populism detection. A two-step annotation was employed, starting with ChatGPT-generated annotations and followed by exhaustive human-in-the-loop validation. The dataset was initially used in a case study to provide insights during the pre-election period. However, it has general applicability by serving as a rich source of information for political and social scientists, journalists, or data scientists, while it can be used for benchmarking and fine-tuning NLP and large language models (LLMs).

"The hand mill gives you society with the feudal lord; the steam mill society with the industrial capitalist," Karl Marx once said. We have seen over and over again throughout history how technological inventions determine the dominant mode of production and with it the type of political authority present in a society. So what will artificial intelligence give us? Who will capitalise on this new technology, which is not only becoming a dominant productive force in our societies (just like the hand mill and the steam mill once were) but, as we keep reading in the news, also appears to be "fast escaping our control"? Could AI take on a life of its own, like so many seem to believe it will, and single-handedly decide the course of our history? Or will it end up as yet another technological invention that serves a particular agenda and benefits a certain subset of humans?

In a sparsely decorated corner office of the Danish Public Benefits Administration sits one of Denmark's most quietly influential people. Annika Jacobsen is the head of the agency's data mining unit, which, over the past eight years, has conducted a vast experiment in automated bureaucracy. Blunt, and with a habit of completing others' sentences, Jacobsen is clear about her mission: "I'm here to catch cheaters." Denmark's Public Benefits Administration employs hundreds of people who oversee one of the world's most well-funded welfare states. The country spends 26 percent of its GDP on benefits--more than Sweden, the United States, and the United Kingdom.

This article appears in the November/December 2021 issue of The American Prospect magazine. The term "artificial intelligence" is widely recognized by researchers as less a technically precise descriptor than an aspirational project that comprises a growing collection of data-centric technologies. The recent AI trend kicked off around 2010, when a combination of increased computing power and massive troves of web data reanimated interest in decades-old techniques. It wasn't the algorithms that were new as much as the concentrated resources and the surveillance business models capable of collecting, storing, and processing previously unfathomable amounts of data. In other words, so-called "advances" in AI celebrated over the last decade are primarily the product of significantly concentrated data and computing resources that reside in the hands of a few large tech corporations like Amazon, Facebook, and Google.

This article appears in the November/December 2021 issue of The American Prospect magazine. The term "artificial intelligence" is widely recognized by researchers as less a technically precise descriptor than an aspirational project that comprises a growing collection of data-centric technologies. The recent AI trend kicked off around 2010, when a combination of increased computing power and massive troves of web data reanimated interest in decades-old techniques. It wasn't the algorithms that were new as much as the concentrated resources and the surveillance business models capable of collecting, storing, and processing previously unfathomable amounts of data. In other words, so-called "advances" in AI celebrated over the last decade are primarily the product of significantly concentrated data and computing resources that reside in the hands of a few large tech corporations like Amazon, Facebook, and Google.

Human history has an unfortunate record of discrimination and biases against each other that follow us from ancient times. A conscious effort towards developing inclusive and equal social systems is a necessity. In the increasingly automated world, where computers interact with humans, Artificial Intelligence gives us another shot at making the world a fairer place with equal opportunities. However, machines are built by people. We are obliged to put conscious effort into making sure the AI solutions won't carry over our mistakes.

THE idea that we are living in a historic, even apocalyptic, age exerts a powerful pull on the human mind. Eschatology – the theology of end times – is a religious concept, but crops up in many other systems of thought. Marxism and neo-liberalism were both driven by an "end-of-history" narrative. Scientific thinking isn't immune either: the technological singularity has been called eschatology for geeks, and the study of existential risk even has its own centre at the University of Cambridge. You don't have to believe in the four horsemen to see the apocalypse coming.

Professor Stephen Hawking is one of the world's most well-known scientists and has had his life story told in books, documentaries, and Oscar-winning dramas. But conspiracy theorists claim we hardly know anything about the award-winning physicist, who celebrated his 76th birthday on Monday. For there are certain corners of the internet where people are convinced that the real Professor Hawking died decades ago and that in the intervening years the political and scientific elite have installed a lookalike to act in his place. Some of those who believe he has been supplanted think Professor Hawking, Director of Research at the Centre for Theoretical Cosmology within the University of Cambridge, died in 1985 - three years before the publication of his best-selling book A Brief History of Time. The idea might seem outlandish, but conspiracy theorists have outlined six signs that they claim clearly support their idea, ranging from the way he looks to the complexity of his theories.

According to scientists and legal experts, responding to the bank's warning this November, there is now an urgent need for the development of intelligent algorithms to be put on the political agenda. Top of the agenda as far as Lightfoot is concerned is the economic impact if AI cuts large amounts of jobs and the incomes from people, how will they make a living and what will they do, a concern that Professor Toby Walsh, an expert in AI at Australia's University of New South Wales and a prominent campaigner against the use of AI in military weapons, says is justified and one that needs to be urgently considered. Though Professor Walsh and fellow AI expert Murray Shanahan, Professor of Cognitive Robotics at London's Imperial College were wary of calls for regulation of the sector, which they said, would inhibit research. According to Professor Walsh scientists working in AI have already started to exercise a degree of self-control over the exploitation of the discoveries being made in AI the areas that need to be focussed on are the ramifications of the technology.

The idea of cyborgs running the world may seem like science fiction but may be becoming reality sooner than you think. No, there will not be an epic world war of us versus them. Instead, the shift from human to automation is slowly creeping into our society. Automation is already running assembly lines and even surgeries. From ATM's, pay-at-the-pump, self check-out, self-serve kiosks, order and pay at the table in restaurants, and all of the banking, shopping, record sharing, reading, socialization that takes place online, computers are already taking the place of humans.