The capacity for highly complex, evidence-based, and strategically adaptive persuasion remains a formidable great challenge for artificial intelligence. Previous work, like IBM Project Debater, focused on generating persuasive speeches in simplified and shortened debate formats intended for relatively lay audiences. We introduce DeepDebater, a novel autonomous system capable of participating in and winning a full, unmodified, two-team competitive policy debate. Our system employs a hierarchical architecture of specialized multi-agent workflows, where teams of LLM-powered agents collaborate and critique one another to perform discrete argumentative tasks. Each workflow utilizes iterative retrieval, synthesis, and self-correction using a massive corpus of policy debate evidence (OpenDebateEvidence) and produces complete speech transcripts, cross-examinations, and rebuttals. We introduce a live, interactive end-to-end presentation pipeline that renders debates with AI speech and animation: transcripts are surface-realized and synthesized to audio with OpenAI TTS, and then displayed as talking-head portrait videos with EchoMimic V1. Beyond fully autonomous matches (AI vs AI), DeepDebater supports hybrid human-AI operation: human debaters can intervene at any stage, and humans can optionally serve as opponents against AI in any speech, allowing AI-human and AI-AI rounds. In preliminary evaluations against human-authored cases, DeepDebater produces qualitatively superior argumentative components and consistently wins simulated rounds as adjudicated by an independent autonomous judge. Expert human debate coaches also prefer the arguments, evidence, and cases constructed by DeepDebater. We open source all code, generated speech transcripts, audio and talking head video here: https://github.com/Hellisotherpeople/DeepDebater/tree/main

"Here we present Project Debater, an autonomous debating system that can engage in a competitive debate with humans," write the authors. In tests of Project Debater, the AI was given only 15 minutes to research topics and prepare for debates. Its successes offer a tantalizing glimpse of how an AI system could work with the web of arguments that humans interpret with such apparent ease," Chris Reed writes in a critique of the new project published in Nature magazine. "Given the wildfires of fake news, the polarization of public opinion and the ubiquity of lazy reasoning, that ease belies an urgent need for humans to be supported in creating, processing, navigating and sharing complex arguments -- support that AI might be able to supply." If this subject interests you, Scientific American has done a great podcast episode with the research's lead Noam Slonim which tackles amongst other things whether the AI actually understands the arguments it presents and what that means for the future of debating. "Here we present Project Debater, an autonomous debating system that can engage in a competitive debate with humans," write the authors. In tests of Project Debater, the AI was given only 15 minutes to research topics and prepare for debates. Its successes offer a tantalizing glimpse of how an AI system could work with the web of arguments that humans interpret with such apparent ease," Chris Reed writes in a critique of the new project published in Nature magazine.

Stand aside, Siri and Alexa. An IBM team led by artificial intelligence (A.I.) researcher Noam Slonim has devised a system that does not merely answer questions; it debates the questioners. In a contest against champion human debaters, Slonim's Project Debater, which speaks with a female voice, impressed the judges. She didn't win, but that could change. As her developers explain in a March Nature article, Project Debater's computational argumentation technology consists of four main modules.

Can a machine powered by artificial intelligence (AI) successfully persuade an audience in debate with a human? As this research develops, it's also a reminder of the urgent need for guidelines, if not regulations, on transparency in AI -- at the very least, so that people know whether they are interacting with a human or a machine. Project Debater is a machine-learning algorithm, meaning that it is trained on existing data. Among them is the language model called Generative Pretrained Transformer (GPT), devised by OpenAI, a company based in San Francisco, California. As AI systems become better at framing persuasive arguments, should it always be made clear whether one is engaging in discourse with a human or a machine?

In February, 2011, an Israeli computer scientist named Noam Slonim proposed building a machine that would be better than people at something that seems inextricably human: arguing about politics. Slonim, who had done his doctoral work on machine learning, works at an I.B.M. Research facility in Tel Aviv, and he had watched with pride a few days before as the company's natural-language-processing machine, Watson, won "Jeopardy!" Afterward, I.B.M. sent an e-mail to thousands of researchers across its global network of labs, soliciting ideas for a "grand challenge" to follow the "Jeopardy!" It occurred to Slonim that they might try to build a machine that could defeat a champion debater. He made a single-slide presentation, and then a somewhat more elaborate one, and then a more elaborate one still, and, after many rounds competing against many other I.B.M. researchers, Slonim won the chance to build his machine, which he called Project Debater.

Can a machine powered by artificial intelligence (AI) successfully persuade an audience in debate with a human? Researchers at IBM Research in Haifa, Israel, think so. They describe the results of an experiment in which a machine engaged in live debate with a person. Audiences rated the quality of the speeches they heard, and ranked the automated debater's performance as being very close to that of humans. Such an achievement is a striking demonstration of how far AI has come in mimicking human-level language use (N.

IBM has designed an artificial intelligence system that can debate with humans. The company published a paper in the journal called Nature, where one of the team members described the AI system and how well it performed against a human opponent. Chris Reed, a professor in the University of Dundee has published a News & Views article in the same journal throwing light on the history and development of artificial intelligence as a disruptive technology based around the types of logic used in human arguments and the system created by IBM. As Reed explains in his piece, debating is a skill that humans have been perfecting for thousands of years. It's usually a type of discussion in which a person or a group persuades others that their opinion on a subject is right.

Stay updated with the latest in Tech, Science, Culture, Entertainment, and more by following our Telegram channel here. There are plenty of real-world applications for artificial intelligence (A.I.), but who'd have thought that arguing with humans would be one of them? A new A.I. program developed by IBM is apparently getting really good at debating against humans that it'll probably be impossible for regular people to win arguments against it in the near future. The program is called Project Debater, and has been in development for the past several years. Its sole purpose is to argue against humans on an array of topics in a meaningful and constructive manner, meaning that it'll take sides in debates and look to make strong logical arguments for its chosen viewpoints.

In 2019 Harish Natarajan took part in a debate with a five-and-a-half-foot tall rectangular computer screen in front of a live audience of about 800 people. The computer was Project Debater, an artificial intelligence system designed by IBM. Natarajan is a globally recognized debate champion. And the topic at hand was whether or not preschool should be subsidized. Based on an audience vote, Project Debater lost the contest.

The study of arguments has an academic pedigree stretching back to the ancient Greeks, and spans disciplines from theoretical philosophy to computational engineering. Developing computer systems that can recognize arguments in natural human language is one of the most demanding challenges in the field of artificial intelligence (AI). Writing in Nature, Slonim et al.1 report an impressive development in this field: Project Debater, an AI system that can engage with humans in debating competitions. The findings showcase how far research in this area has come, and emphasize the importance of robust engineering that combines different components, each of which handles a particular task, in the development of technology that can recognize, generate and critique arguments in debates. Less than a decade ago, the analysis of human discourse to identify the ways in which evidence is adduced to support conclusions -- a process now known as argument mining2 -- was firmly beyond the capabilities of state-of-the-art AI. Since then, a combination of technical advances in AI and increasing maturity in the engineering of argument technology, coupled with intense commercial demand, has led to rapid expansion of the field.