Public lecture by Luca Longo "The Turing Test, Artificial Intelligence and the Human Stupidity"


Dr Luca Longo, opened the show at the prestigious TEDx Vicenza 2017 in Italy with "Can machines think?", following his innovative research on Artificial Intelligence (AI). The sold out event saw more than 1000 spectators attend the third edition of TEDxVicenza, with a futher 5000 people following the live stream on the TEDxVicenza website. Social media was alive with chatter from the event as #TEDxVicenza began trending.  Dr. Longo will replicate the talk to INNOPOLIS UNIVERSITY live, starting his contribution with the famous question proposed by Alan Turing: “can machines think?”. It will briefly described the state of the art in Artificial Intelligence and will present a future time line mentioning the ‘technological singularity” concept introduced some years ago by Ray Kurzweil. He will continue with future predictions of technological events within the next 28 years.The talk will also cover contemporary and ethical issues around the field of Artificial Intelligence.  To conclude Dr. Longo will introduce a provocative 10th objection, following the 9 objections proposed by the renowned Computer Scientist Alan Turing’s to his own Turing Test. This provocation is: “If it is true we will be able to transfer human intelligence to machines, and they will become more intelligent than us, it is also true that we have let them become more intelligent. An absurdum.”

Dr. Luca Longo is currently lecturer at Dublin Institute of Technology, where he is a member of the Applied Intelligence Research Center, a member of the ADAPT global centre of excellence for digital content and innovation and  MSc theses coordinator in the School of Computing. He is author of 30+ academic articles appeared in conference proceedings, book chapters, and journals in various theoretical and applied computer science fields. He is the founder of the first international symposium of human mental workload, models and applications.

His core research interest is in Mental Workload modelling using deductive inference techniques (Defeasible Reasoning, Argumentation Theory, Recommender/Expert systems) as well as knowledge discovery and inductive predictive modelling techniques (Supervised/Unsupervised Machine Learning). Domains of application of Mental Workload models include human-computer/web interaction (HCI), health-care (HC), education (EDU) and Universal Design (UD). In particular, computational models of mental workload can be used for designing, personalising and adapting technologies and multi-modal interactions, better aligned to the human mental limited capacities and in turn enhancing user engagement, satisfaction and learning.

Luca owns a BSc (honors) and a MSc (distinction) in Computer Science (Italy), a PostGraduate Diploma in statistics, a MSc (distinction) in Health Informatics and a PhD in Artificial Intelligence awarded at Trinity College Dublin. He also owns a post-graduate diploma in Learning and Teaching at Dublin Institute of Technology and completing an MSc in Applied e-Learning.”

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