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Gianmarco De Francisci Morales

Principal Researcher, CENTAI

Gianmarco De Francisci Morales is a Principal Researcher at CENTAI, a private research institute that focuses on Artificial Intelligence and Complex Systems, where he leads the Social Algorithmics Team (SALT). Previously, he worked as a Senior Researcher at ISI Foundation in Turin, as a Scientist at Qatar Computing Research Institute in Doha, as a Visiting Scientist at Aalto University in Helsinki, as a Research Scientist at Yahoo Labs in Barcelona, and as a Research Associate at ISTI-CNR in Pisa. He received his Ph.D. in Computer Science and Engineering from the IMT Institute for Advanced Studies of Lucca in 2012. His research focuses on computational social science and data mining, with an emphasis on polarization and echo chambers on social media. He has been a member of the open source community of the Apache Software Foundation, has worked on the Hadoop ecosystem, and has been a committer for the Apache Pig project. He was one of the lead developers of Apache SAMOA, an open-source platform for mining big data streams. He commonly serves on the PC of several major conferences in the area of data mining, including WSDM, WWW, KDD, and ICWSM. He co-organized the workshop series on Social News on the Web (SNOW), co-located with the WWW conference. He has published more than 90 scientific articles and won best paper awards at WSDM, CHI, WebSci, and SocInfo.

Tracing AI's Transformation from 'WarGames' to the Social Media Era

Four decades ago, "WarGames" highlighted the dangers of AI controlling nuclear weapons. But how much safer are AI systems today compared to our past collective imagination? And which domains are appropriate for the application of AI, not only as a technology but also as an ideology?Modern AI can mimic human language, but struggles with reasoning, a surprising aspect from a historical point of view. This intriguing characteristic has reshaped the boundaries of AI applications, and sparked discussions on the implications of human-AI interaction. Central to the functioning of modern AI systems are generative models, fine-tuned via machine learning algorithms on extensive datasets harvested from the Web and social media. Interestingly, social media platforms are also one of the main users of AI models, as components in running their machinery. Their deployment spans several pivotal functions, encompassing content moderation, personalized content recommendation, and targeted advertising. The interplay between AI and social media is a convoluted cycle, one that gains complexity as it intertwines with the intricacies of politics, ideological polarization, and digital radicalization. The dynamics at play within this ecosystem have profound implications for the dissemination of information, the formation of opinions, and the broader societal fabric.Exploring the fusion of AI and social media requires a nuanced understanding of the potential risks and opportunities it presents. Drawing on two decades of research, this exploration delves into the criticalities and positive potentials this amalgamation offers. By examining the complex feedback loop of AI-mediated information dissemination and its influence of people's opinions, this discussion sheds light on its power to inform and manipulate. As AI and social media become increasingly intertwined, the pertinence of the Turing test comes into question. Rethinking the significance of this test —designed to evaluate an AI's human-like behavior— elicits a reconsideration in light of modern AI capabilities. This prompts a call for an updated assessment framework that reflects the evolving societal needs and the complex interplay of technology, information, and human values.

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