„Why do people judge humans differently from machines? The role of agency and experience”
Prof. Cesar A. Hidalgo
University of Toulouse and Corvinus University of Budapest
People are known to judge artificial intelligence using a utilitarian moral philosophy and humans using a moral philosophy emphasizing perceived intentions. But why do people judge humans and machines differently? Psychology suggests that people may have different mind perception models for humans and machines, and thus, will treat human-like robots more similarly to the way they treat humans. Here we present a randomized experiment where we manipulated people’s perception of machines to explore whether people judge more human-like machines more similarly to the way they judge humans. We find that people’s judgments of machines become more similar to that of humans when they perceive machines as having more agency (e.g. ability to plan, act), but not more experience (e.g. ability to feel). Our findings indicate that people’s use of different moral philosophies to judge humans and machines can be explained by a progression of mind perception models where the perception of agency plays a prominent role. These findings add to the body of evidence suggesting that people’s judgment of machines becomes more similar to that of humans motivating further work on differences in the judgment of human and machine actions.
Curriculum Vitae
César A. Hidalgo is a Chilean-Spanish-American scholar known for his contributions to economic complexity, data visualization, and applied artificial intelligence. Hidalgo leads the Center for Collective Learning at the Artificial and Natural Intelligence Institute (ANITI) of the University of Toulouse and the Corvinus Institute for Advanced Studies at Corvinus University of Budapest. He is also an Honorary Professor at the University of Manchester. Between 2010 and 2019 Hidalgo led MIT’s Collective Learning group. Prior to working at MIT, Hidalgo was a research fellow at Harvard’s Kennedy School of Government. Hidalgo is also a founder of Datawheel, an award winning company specialized in the creation of data distribution and visualization systems. He holds a PhD in Physics from the University of Notre Dame and a Bachelor in Physics from Universidad Católica de Chile. Hidalgo’s contributions have been recognized with numerous awards, including the 2018 Lagrange Prize and three Webby Awards. Hidalgo is also the author of dozens of peer-reviewed papers and of three books: Why Information Grows (Basic Books, 2015), The Atlas of Economic Complexity (MIT Press, 2014), and How Humans Judge Machines (MIT Press, 2021).
„Crisp vs. Soft Computing behind AI transformation”
Prof. Péter Baranyi
Corvinus University of Budapest, Hungary
The plenary lecture will delve into the evolutionary trajectory of mathematical tools that have paved the way for the emergence of pivotal learning technologies in the field of Artificial Intelligence (AI). It will explore the notion that contemporary modelling and control methodologies are predominantly grounded in „crisp” mathematical frameworks, such as convex optimization and linear matrix inequalities, which are characterized by precise closed-form solutions. Conversely, the mathematical underpinnings of soft computing techniques, such as artificial neural networks, genetic algorithms, and fuzzy logic, are not firmly rooted in closed-form expressions but rather draw inspiration from biologically motivated structures.
To effectively harness the cutting-edge „crisp” mathematical tools in AI, particularly in controlling the AI engine, it becomes imperative to establish a common mathematical platform or, at the very least, establish a gateway between the realms of „crisp” and soft computing. The central focus of this lecture revolves around elucidating strategies to bridge the gap between crisp and soft computing techniques within the AI processes.
Curriculum Vitae
Peter Baranyi, a renowned Hungarian scholar, has made significant contributions to the fields of non-linear control theory & modelling, as well as the cognitive aspects of digital reality. In 2010, he introduced the concept of Cognitive Info-Communications, which focuses on the new cognitive capabilities of the blended combination of human and informatics. One of his notable inventions is the TP model transformation, a higher-order singular value decomposition of continuous functions. This transformation plays a crucial role in the development of nonlinear control design theories and paves the way for optimization techniques. Baranyi’s scientific achievements have been recognized with prestigious awards, including the Investigator Award from Sigma Xi and the International Design Gabor Award. He has published over 100 journal papers and authored three books. In 2006, he was honoured with a doctorate from the Hungarian Academy of Sciences.
„Digital & Cognitive Corporate Reality”
Prof. Andrea Kő
Corvinus University of Budapest, Hungary
The transformative shift of artificial intelligence, the recent development in digital transformation, and the human co-evolution with information and communication technologies have led to a new era in many fields, including corporate management and business. Newly co-evolved cognitive capabilities, both natural and artificial, are emerging, necessitating a paradigm shift in our understanding and approaches to corporate management and business science. This introduces the Digital and Cognitive Corporate Reality (DCR) concept to establish a broader view for higher-level conceptual discussion, adopting a holistic perspective encompassing related scientific fields. Beyond this definition, the presentation briefly explores how different scientific disciplines can be expected to contribute to the development of DCR.
Curriculum Vitae
Andrea Kő, PhD is a Professor at Corvinus University of Budapest and Director of the Institute of Data Analytics and Information Systems. She has a University Doctoral degree in Computer Science (1992) from Corvinus University of Budapest, Hungary and a PhD in Management and Business Administration (2005) from Corvinus University of Budapest, Hungary. She is a board member of the Scientific and Educational Forum for Business Information Systems (Community of the John von Neumann Computer Society, the Member Society of IFIP) and a Program Director of the Business Informatics Doctoral Program of the Doctoral School of Economics, Business, and Informatics. She has been involved in and led several international and national research projects in various areas of digitalisation, business intelligence, data analytics, semantic technologies, and applications of ICT. She is an editor of the Journal of Computing and Information Technology (http://cit.fer.hr/index.php/CIT), and Budapest Management Review (https://journals.lib.uni- corvinus.hu/index.php/vezetestudomany), Volume editor in Springer LNCS 14149, LNCS 13429, LNCS 12926, LNCS 8650, LNCS 8186 and LNCS 8061. She has published more than 130 papers in international scientific journals and conferences. Her research interests include digital and cognitive corporate reality, digital transformation, business analytics, machine learning and semantic technologies.
„The Great Fallacy of AI Ethics”
Prof. Viktor Dörfler
Corvinus University of Budapest, Hungary
Ethics is one of the oldest intellectual quests of humankind, and AI is one of the newest. What happens when we bring the two together? I give a very brief overview of the development of thinking in ethics, and then ask how can any of this be done with AI. I reflect on what AI can do compared to the human mind, arguing that the human mind is better at some things and AI is better at some other things. On this basis, I suggest that we are asking the wrong questions about AI Ethics, and explore some new directions that I find more promising. What emerges from this discussion is an understanding that we are in a serious trouble in Ethics, be it in relation to AI or just between us humans. It seems that we (humans) tried to build all sorts of models on ethics, without succeeding to agree about much. Over the past two and a half millennia, we learned to ask increasingly difficult questions, but we do not have any answers that we all accept. This is a problem, as with AI in our everyday life, we need answers to the basic questions of Ethics now.
Curriculum Vitae
Dr Viktor Dörfler is an Associate Professor of AI Strategy at the University of Strathclyde Business School, Glasgow, UK and a Senior Fellow at the Corvinus Institute of Advanced Studies. As a practitioner, he spearheaded the development of AI software, compared various AI solutions, explored the validity of AI, and conducted AI implementations. Meanwhile, his scholarly research has focused on talent, creativity, and the grandmaster-apprentice relationship. He conducted in-depth open-ended interviews with 20 top scientists, including 17 Nobel Laureates, in order to understand the thinking of scientists at the highest level of mastery. Bringing his practitioner and scholarly roots together, Viktor currently focuses on the human side of AI implementations, in order to increase their success through managing the cultural and organizational learning aspects of using AI. Viktor authored three books, including What Every CEO Should Know About AI (Cambridge University Press, 2022), wrote 30+ journal papers, and 100+ conference papers; his. Viktor has been appointed member of the British Standard Institution’s Artificial Intelligence Committee (BSI ART/001).