Since Donald Trump launched his chaotic trade war earlier this year, it has become a truism to say he has plunged the world economy into crisis. At last month's spring meetings of the World Bank and International Monetary Fund in Washington, where policymakers and finance ministers from all over congregated, the attenders were "shellshocked", the economist Eswar Prasad, a former senior IMF official who now teaches at Cornell, told me. "The sense is that the world has changed fundamentally in ways that cannot easily be put back together. Every country has to figure out its own place in this new world order and how to protect its own interests." Trump's assault on the old global order is real. But in taking its measure, it's necessary to look beyond the daily headlines and acknowledge that being in a state of crisis is nothing new to capitalism. It's also important to note that, as Karl Marx wrote in The Eighteenth Brumaire of Louis Napoleon: "Men make their own history, but they do not make it as they please."

Computational argumentation has become an essential tool in various fields, including artificial intelligence, law, and public policy. It is an emerging research field in natural language processing (NLP) that attracts increasing attention. Research on computational argumentation mainly involves two types of tasks: argument mining and argument generation. As large language models (LLMs) have demonstrated strong abilities in understanding context and generating natural language, it is worthwhile to evaluate the performance of LLMs on various computational argumentation tasks. This work aims to embark on an assessment of LLMs, such as ChatGPT, Flan models and LLaMA2 models, under zero-shot and few-shot settings within the realm of computational argumentation. We organize existing tasks into 6 main classes and standardise the format of 14 open-sourced datasets. In addition, we present a new benchmark dataset on counter speech generation, that aims to holistically evaluate the end-to-end performance of LLMs on argument mining and argument generation. Extensive experiments show that LLMs exhibit commendable performance across most of these datasets, demonstrating their capabilities in the field of argumentation. We also highlight the limitations in evaluating computational argumentation and provide suggestions for future research directions in this field.

And I am talking Season 3. Or Amazon's hit, The Handmaid's Tale? Do you just binge and veg out or are you like me, and see how easily we could, and are, slipping into these worlds? After watching shows like this I often find myself reflecting back on George Orwell's 1984. It proves more eerily prophetic with each passing year. This Season, I fear, the writers of Westworld are almost scripting our future lives. You may not have caught it, but it is all in there.

The central prediction I want to make and defend in this post is that continued rapid progress in machine learning will drive the emergence of a new kind of geopolitics; I have been calling it AI Nationalism. Machine learning is an omni-use technology that will come to touch all sectors and parts of society. The transformation of both the economy and the military by machine learning will create instability at the national and international level forcing governments to act. AI policy will become the single most important area of government policy. An accelerated arms race will emerge between key countries and we will see increased protectionist state action to support national champions, block takeovers by foreign firms and attract talent.

The human species is about to change dramatically. That's the argument Yuval Noah Harari makes in his new book, Homo Deus: A Brief History of Tomorrow. Harari is a history professor at Hebrew University in Israel. He tells NPR's Ari Shapiro that he expects we will soon engineer our bodies and minds in the same way we now design products. The three main ways of doing that, first of all, is to take our organic body and start tinkering with it with things like genetic engineering, speeding up natural selection and actually replacing it with intelligent design -- not the intelligent design of some God above the clouds, but our intelligent design.