A.L./Blog

Morte di un cibernetico napoletano

noreply@blogger.com (Antonio Lieto) — Sun, 02 Nov 2025 07:17:00 +0000

Sono stato alla commemorazione in onore di Giuseppe Trautteur (condivido qui un suo ricordo di Guglielmo Tamburrini) tenutasi a Napoli presso l'Istituto Italiano per gli Studi Filosofici, a Palazzo Serra di Cassano.

Giuseppe Trautteur è stato - in Italia - un pioniere e un riferimento (per generazioni di studiosi) della cibernetica (poi scienze cognitive) e dell'intelligenza artificiale. Conosciuto grazie a Roberto Cordeschi e Marcello Frixione durante i loro anni salernitani, l'ho poi incontrato successivamente in diverse occasioni.

Tra i ricordi più belli e recenti che conservo con lui c'è un panel del 2017 (da cui è tratta la foto in basso) che organizzai a Bari come evento della conferenza AI*IA 2017, coordinata da Floriana Esposito e dal gruppo barese di AI. Quel panel (intitolato: Can AI and Cognitive Science still live together happily ever after) è stato il primo evento congiunto tra Associazione Italiana per l'Intelligenza Artificiale e Associazione Italiana di Scienze Cognitive e vide come partecipanti: Amedeo Cesta, Antonio Chella, Fabio Paglieri, Oliviero Stock e Giuseppe Trautteur.

Ho visto Giuseppe un'ultima volta lo scorso febbraio, quando venne a moderare (un po' a sorpresa), a Napoli, una sessione di questo evento in cui presentavo un mio lavoro https://sites.unimi.it/brio/brio-meeting-unina-unit/. Di quest'ultima volta ricordo, come sempre, le sue osservazioni brillanti.

La sua perdita è incolmabile: una persona con un sapere così ampio (e al contempo profondo) è impossibile da ritrovare, specialmente nella ipersettorializzazione (spesso miope) dell'accademia italiana di oggi. La scorsa settimana, nell'ambito della decima edizione del workshop internazionale su Artificial Intelligence and Cognition (AIC 2025) tenutosi nell'ambito della conferenza ECAI a Bologna (foto in basso), non ho potuto fare a meno di dedicare l'evento alla sua memoria (un piccolo attestato di riconoscenza, in attesa di eventi ben più importanti che andranno organizzati per ricordare il suo lascito intellettuale e scientifico).

Ieri è stato molto bello ascoltare i numerosi ricordi delle tante persone che hanno avuto la fortuna di collaborare - in vario modo - con lui.

La sensazione di fondo che ho percepito è stata, però, da parte di tutti i presenti e di coloro che sono intervenuti, la difficoltà a trovare le parole giuste: quelle in grado descrivere in modo adeguato la grandezza dello scienziato e dell'uomo. Tutte e tutti erano consci del fatto che la verbalizzazione del ricordo - seppure lucida, chiara, sincera, affettuosa - non restituiva la pienezza dell'esperienza vissuta.

Mi è venuto in mente l'epilogo del celebre film di Martone "Morte di un matematico napoletano", dedicato alla vita di Renato Caccioppoli, in cui è evidente - durante il commiato finale dal grande matematico - la costernazione per l'inadeguatezza del linguaggio nell'afferrare pezzi di vita irripetibili. Con Giuseppe Trautteur, se ne va l'ultimo grande l'ultimo grande cibernetico della scuola napoletana fondata da Edoardo Caianiello.

Feedback by Péter Érdi

noreply@blogger.com (Antonio Lieto) — Tue, 08 Apr 2025 10:44:00 +0000

The notion of feedback represents one of the most important contribution of the cybernetics to the science of (any) complex systems design. In the cybernetic tradition, machines capable of adapting themselves actively to the environments via trial-and-error process based on negative feedback (used for autocorrection) were called “servomechanisms” or “negative feedback automata”. A recent example of machines using these type of mechanisms comes from the Artificial Intelligence, since current artificial neural networks (at least the once that are more successful nowadays) make use, in their supervised learning phase, of a well knoan feedback mechanism called "backpropagation".

The book "Feedback, how to destroy or save the worlds" (Springer, 2024) by Péter Érdi is an intellectual journey in the science of feedback and shows, with clear examples coming from different fields, how either the design or the discovery of feedback mechanisms is crucial for the advancement of science, technology, economics and society since feedback is a crucial component of any complex system.

The book focuses not only on the well known importance of negative feedback (e.g. for learning) but also, and more importantly, on the importance of understanding what are feedback mechanisms governing the behavior of a certain system and upon which it is possibile to intervene (using both positive and negative corrective signals) in order to lead to (biological/computational/mechanical/physical/chemical...) states that can lead to homeostatsis, market stability, environmental sustainability and so on.

If there is any chance of saving this World, the realization of powerful feedback mechanisms able to avoid catastrophic outcomes represents one of the few elements to put in place. And, in this state of affairs, the science of feedback (Cybernetics) strikes back and seems to be even more relevant today!

Why Hinton is Wrong about AI taking over (and about conscious AI)

noreply@blogger.com (Antonio Lieto) — Sat, 01 Feb 2025 10:48:00 +0000

Recently the The Nobel Prize and ACM, Association for Computing Machinery Turing Award Winner Geoffrey Hinton relaunched his ideas and fears about "AI's taking over" (see this recent interview https://www.youtube.com/watch?v=vxkBE23zDmQ, when he claims that "AI is already conscious" because - among the other things - 1) it has its own goals, 1) it can create subgoals and, 3) since - if implanted in a biological tissue of biological entity that biological entity remains conscious such biological entity remains conscious, as a consequence also the implanted device is (yes he said that). First: the fact that AI systems have goals (always provided by the humans) and create subgoals to achieve them is not new (see e.g. the subgoaling procedure in the cognitive architecture SOAR that relies on the means-end analysis heuristics, used already in the General Problem Solver developed by Newell, Shaw and Simon in 1959! I repeat: 1959!). So these two points do not make any sense. Also the fact that AI systems are able to invent new knowledge (going beyond subgoaling procedures) to solve new problems is not something new: in 2018-2019 with my colleague Gian Luca Pozzato and our students we developed a system that used the TCL logical framework, https://www.antoniolieto.net/tcl_logic.html, to invent new knowledge for solving problems via concept combination, blending and fusion (the paper is here: https://doi.org/10.1016/j.cogsys.2019.08.005 ). None of these things make an AI system conscious: they are just general heuristic procedures that allow a system to have yet another strategy (provided by us) to perform better on unknown tasks. In addition: the discourse that an AI system can functionally replace biological cells/neurons/tissues without making the system subject to this replacement “unconscious” (and therefore - this is how the reasoning of Hinton goes - the AI system is also “conscious”) is a complete nonsense since there is a confusion on many levels. The first confusion concerns the distinction between functional and structural systems (discussed extensively in my book Cognitive Design for Artificial Minds https://www.amazon.com/Cognitive-Design-Artificial-Minds-Antonio/dp/1138207950). The second one - connected to the first - concerns the attribution to a functional component of a “structural” (i.e. cognitive/biological) explanation. This is a sort of ascription fallacy that is also described in the book (and that is very common nowadays). More specifically: of course we can have bionic systems that are integrated - via partial or total replacement - with biological cells and tissues but functional replacement does not imply any biological/cognitive attribution (on this please also see this paper https://doi.org/10.3389/frobt.2022.888199) Think for example to the exoskeletons controlled via semi-invasive medical devices to record brain activity: these systems “function as” our biological counterpart and communicate well with other biological components leading to locomotion. But… Would you say that they (i.e.: the semi-invasive component implanted in our brain in this case…to follow Hinton’s unreasonable reasoning chain) are conscious (just because the biological entity that have them implanted is conscious)? That’s plain wrong and non sense. These kind of claims are completely unjustified and wrong from a scientific perspective and have nothing to do with the typical concerns and legitimate discussions about the risks coming from the societal and ethical impact that AI has any technology.

Large Language Models, Super Human Intelligence and the Methodological Hallucinations of Modern AI

noreply@blogger.com (Antonio Lieto) — Wed, 31 May 2023 16:39:00 +0000

In the last months a major source of confusion related to the interpretation of the behavior exhibited by the current state of the art AI systems (e.g. Large Language Models like GPT4 and chatGPT for natural language processing) is due to the wrong ascription of cognitive capabilities to them. This confusion, when genuine (and not generated ad-hoc like in this case), is factually wrong since it prefigures Strong AI scenarios that are scientifically ungrounded (while there are reasons to urgently consider other ethical issues regarding the impact on the society of these techologies from the point of view of the biases introduced, their potential misuse, their impact on the job market etc.)

In particular, the expression “Strong AI” was introduced by John Searle to identify the position assuming that computational models, embodied or not, can have a “mind”, a “consciousness” etc. in the same way of human beings. On the other hand, the expression "Weak AI” synthesizes the position according to which computational models can simulate human behaviour and thinking abilities but cannot pretend to possess any kind of “real” cognitive state.

In Cognitive Design for Artificial Minds (Routledge Books/ Taylor & Francis, 2021) I show how the current #AI and cognitive modelling research are perfectly aligned with the weak-AI hypothesis. In particular, current AI systems, can be described (at the very best) as "shallow”, imprecise and often biologically and cognitively implausible technological depictions of biological brains, from which our intelligent capabilities arise. They are what I call "functionally designed" systems: they apparently "function as" biological brains (i.e. are able to superficially reproduce the same output) but the mechanisms determining that behavior/output are completely different from the ones we know from biology, neuroscience, physiology and cognitive psychology.

As a consequence, we cannot ascribe theories and faculties explaining biological phenomena to interpret the behavior of such artifacts since the differences and the asymmetries between these classes of systems are enormous (a corollary of this consequence is that also the discourse about the eventual emergence of intentional or "conscious" signals from such systems is literally science fiction).

Now: the fact that for "functionally designed" AI systems it is not possible to generate artifacts that can be "intelligent" or "conscious" exactly like us (or like other biological entities) makes it irrelevant also the fear about super intelligent machines. We already have a huge number of systems achieving super-human performances in a number of different tasks (ranging from computer vision to NLP). However their incredible performance is not a symptom of the acquisition of the underlying competence that, in our brains, explains a certain intelligent behavior.

And what about the class of “constrained” artificial systems then (i.e. those designed and implemented by explicitly taking into account neuroscientific and/or psychological theories and constraints to build computational models of cognition)? Also for this category of systems, built by adopting what I call in the book a "structural design approach" (Chapter 2), I showed how they can be used to actually simulate the human-like mechanisms determining a given behaviour, and this can enable the understanding of some hidden mechanistic dynamics. Such computational models, therefore, can be used (and are used) to better understand biological or mental phenomena without pretending that that they are the real phenomena that they are modelling. By using a famous analogy proposed by Searle himself: "just as a model of the weather is not the weather, a model of the human mind is not a human mind".

As a consequence of this state of affairs, both these classes of artificial systems (that are build by following different design principles and with different goals) methodologically fall within the "weak AI" approach. This consideration - that I argue and detail extensively in Cognitive Design for Artificial Minds - is in contrast with the nowadays popular (but uncorrect) vulgata that see them as instances of the “Strong AI” hypothesis (and that is one of the main sources of confusion on these topics).

The fact that both the fields of AI and Computational Cognitive Science build models and systems falling within the weak AI hypotheses does not make weaker any of the two disciplines: AI researchers, indeed, continue to build better systems and technologies with the purpose that they can (in principle) be useful for the human beings and that can, in principle, perform better than humans in specific tasks; computational cognitive scientist, on the other hand, continue to build computational simulation of biological/cognitive processes without pretending to build any system able to really be described as “intelligent” or “conscious” in the proper human sense.

It is just incredible to see nowadays many comments (including those of AI experts) that are not able to recognize the asymmetries between the incredible technologies that have been built and what biological brains do in the way they are built. It would be about time to dismiss the alarmist claims about the AI and their (hypothetical) existential risks for humanity. They represent nothing less than hallucinations (generated by humans this time) determined by the methodological fog enveloping the modern AI field.

Cognitive Design for Artificial Minds on Substack!

noreply@blogger.com (Antonio Lieto) — Fri, 26 Aug 2022 10:50:00 +0000

Cognitive Design for Artificial Minds (Routledge/Taylor and Francis, 2021) https://www.amazon.com/Cognitive-Design-Artificial-Minds-Antonio-dp-1138207950/dp/1138207950/ has now its Substack channel at https://artificialminds.substack.com! It is possible now to subscribe to the #newsletter to get updates, news and inedited content about the themes and topics of the book. Coming in the next months with podcasts and video interviews!

Cognitive Design for Artificial Minds nominated in the Top 3 "Best Artificial Intelligence Design Books of All Time" according to BookAuthority

noreply@blogger.com (Antonio Lieto) — Wed, 09 Feb 2022 15:39:00 +0000

Cognitive Design for Artificial Minds made it to the Best Artificial Intelligence Design Books of All Time. I'm happy to announce that my book, "Cognitive Design for Artificial Minds", made it BookAuthority's Best Artificial Intelligence Design Books of All Time. BookAuthority collects and ranks the best books in the world, and it is a great honor to get this kind of recognition. Thank you for all your support! The book is available for purchase on on Amazon and on the Taylor and Francis website at https://doi.org/10.4324/9781315460536

Cognitive Design for Artificial Minds in the list of the "Best New Artificial Intelligence Design Books To Read" according to BookAuthority

noreply@blogger.com (Antonio Lieto) — Wed, 14 Jul 2021 17:02:00 +0000

Cognitive Design for Artificial Minds made it to the Best New Artificial Intelligence Design BooksI'm happy to announce that my book, "Cognitive Design for Artificial Minds", made it to BookAuthority's Best New Artificial Intelligence Design Books:
https://bookauthority.org/books/new-artificial-intelligence-design-books?t=12uofh&s=award&book=1138207926

BookAuthority collects and ranks the best books in the world, and it is a great honor to get this kind of recognition. Thank you for all your support!

The book is available for purchase on Amazon.

Cognitive Design for Artificial Minds - Presentation and Discussion (YouTube Videos)

noreply@blogger.com (Antonio Lieto) — Thu, 08 Jul 2021 06:57:00 +0000

In the past months, the book "Cognitive Design for Artificial Minds" (Routledge/Taylor & Francis, 2021) has been presented and discussed in a couple of events.

The first event was an invited author presentation at the Northwestern AGI Forum in Seattle on April 28th, 2021 https://www.meetup.com/Northwest-Artificial-General-Intelligence-Meetup-Group/events/277014146/. The presentation was held online and the video is available below

The second one was held on June 30th 2021 and was a joint discussion done on GatherTown with Shiwali Mohan (Xerox Parc, USA), David Peebles (University of Huddersfield, UK), Karen Pollitt-Cham (University of Brighton, UK) and with Antonio Chella (University of Palermo) acting as a moderator. We had a great discussion about some of the main themes touched in the book. The video of the event is also available below and on the YouTube Channel of the book. Enjoy!

Cognitive Design for Artificial Minds in the Libraries around the World

noreply@blogger.com (Antonio Lieto) — Fri, 16 Apr 2021 13:08:00 +0000

The book "Cognitive Design for Artificial Minds" has already found its place in #52 Libraries around the World!

This list includes: the Library of Congress, the Libraries of Columbia University in the City of New York, the UCI Langson Library of UC Irvine, the Université de Montréal Library, the McGill University Library, the University of Alberta Library, the Universidad Nacional Autónoma de México Library, the Koninklijke Bibliotheek (KB), nationale bibliotheek van Nederland and many many more.

The data are provided by WorldCat.org (the World's Largest Library Catalog).

The list full of libraries currently having a copy of the book is available here: https://lnkd.in/dFNMKDj

You can take your copy of Cognitive Design for Artificial Minds on:

- Amazon.com: https://lnkd.in/dkuhyGK

- Routledge: https://lnkd.in/dUR38Kh

Cognitive Design for Artificial Minds on Facebook and Twitter

noreply@blogger.com (Antonio Lieto) — Fri, 01 Jan 2021 18:17:00 +0000

The book Cognitive Design for Artificial Minds (Taylor & Francis, 2021) has now its own Facebook page and Twitter profile where will be shared updates, events, presentations, excerpts etc. regarding the book. Link to the Facebook page here: https://www.facebook.com/cognitivedesignforartificialminds/ Link to the Twitter account here: https://twitter.com/CognitiveFor

Commonsense reasoning as a key feature for dynamic knowledge invention and computational creativity (Invited Talk)

noreply@blogger.com (Antonio Lieto) — Mon, 14 Dec 2020 15:33:00 +0000

I had to oppurtunity to deliver this keynote talk at ICAR-MEET 2020, the annual workshop of the Institute for High Performance Computing of the National Research Council of Italy (CNR).

Below the link to the slides:

Commonsense reasoning as a key feature for dynamic knowledge invention and computational creativity from Antonio Lieto

Cognitive Design for Artificial Minds

noreply@blogger.com (Antonio Lieto) — Wed, 11 Nov 2020 13:50:00 +0000

I am really glad to announce my forthcoming book "Cognitive Design for Artificial Minds" that will be published in 2021 by Taylor & Francis (T&F).

The book can already be pre-ordered in the main online bookshops (e.g. from Routledge (T&F) to Amazon Walmart Barnes& Noble etc.)

I am posting below the "blurb" and the Table of Contents of the Book from the Routledge website (T&F).

Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science.

Beginning with an overview of the historical, methodological and technical issues in the field of Cognitively-Inspired Artificial Intelligence, Lieto illustrates how the cognitive design approach has an important role to play in the development of intelligent AI technologies and plausible computational models of cognition. Introducing a unique perspective that draws upon Cybernetics and early AI principles, Lieto emphasizes the need for an equivalence between cognitive processes and implemented AI procedures, in order to realise biologically and cognitively inspired artificial minds. He also introduces the Minimal Cognitive Grid, a pragmatic method to rank the different degrees of biologically and cognitive accuracy of artificial systems in order project and predict their explanatory power with respect to the natural systems taken as source of inspiration.

Providing a comprehensive overview of cognitive design principles in constructing artificial minds, this text will be essential reading for students and researchers of artificial intelligence and cognitive science.

Introduction

Chapter 1. Cognitive Science and Artificial Intelligence: Death and Rebirth of a Collaboration

1.1. When Cognitive Science was AI

1.2. From The General Problem Solver to the Society of Mind: cognitivist insights from the early AI era

1.3. Heuristics and AI Eras

1.4. Modelling Paradigms and AI Eras: Cognitivist and Emergentist Perspective

1.5. Death and Rebirth of a Collaboration

Chapter 2. Cognitive and Machine Oriented Approaches to Intelligence in Artificial Systems

2.1. Nature vs Machine Inspired Approaches to Artificial Systems

2.2. Functionalist vs Structuralist Design Approaches

2.3. Levels of Analysis of Computational Systems

2.4. The Space of Cognitive Systems

2.5. Functional and Structural Neural Systems

2.6. Functional and Structural Symbolic Systems

Chapter 3. Principles of the Cognitive Design Approach

3.1. Classical, Bounded and Bounded-Rational Models of Cognition

3.2. Resource-Rationality Models

3.3 Kinds of Explanations

3.4 Levels of Plausibility and the Minimal Cognitive Grid (MCD)

Chapter 4. Examples of Cognitively Inspired Systems and application of the Minimal Cognitive Grid

4.1 Modern AI Systems: Cognitive Computing?

4.2 Cognitive Architectures

4.3 SOAR

4.4. ACT-R

4.5 Two Problems for the Knowledge Level in Cognitive Architectures

4.6. Knowledge Size and Knowledge Heterogeneity in SOAR and ACT-R

4.7. DUAL PECCS

Chapter 5. Evaluating the Performances of Artificial Systems

5.1. "Thinking" Machines and Turing Test(s)

5.2. The Chinese Room

5.3. The Newell Tests for a Theory of Cognition

5.4. The Winograd Schema Challenge

5.5. DARPA Challenges, Robocup and Robocup@Home

5.6. Comparison

Chapter 6. The Next Steps

6.1. The Road Travelled

6.2. The Way Forward

6.3. Towards a Standard Model of Mind/Common Model of Cognition

6.4. Community

Heterogeneous Proxytypes as a Teaching Tool in Learning Science and Education

noreply@blogger.com (Antonio Lieto) — Sun, 21 Jun 2020 16:59:00 +0000

The post is to share an update about an (unexpected) outcome of one of my main research outputs: the Heterogeneous Proxytypes (HP) hypothesis.

A brief recap before going to the point: back in 2014 I proposed heterogeneous proxytypes as a framework (alternative and integrative with respect to other approaches based on prototypes, exemplars, model-theory etc.) for conceptual representation and processing in cognitive science and artificial intelligence research (here the original paper http://www.sciencedirect.com/science/article/pii/S1877050914015233, presented at BICA 2014 held at the MIT in Boston).

Such a proposal has led to the design and development of categorization systems like DUAL-PECCS (the main references of such a cognitively-inspired knowledge representation and processing framework, and of its computational counterpart, are reported below):

- Antonio Lieto, "A Computational Framework for Concept Representation in Cognitive Systems and Architectures: Concepts as Heterogeneous Proxytypes" in Proceedings of BICA 2014, 5th Int. Conference of Biologically Inspired Cognitive Architectures, Boston, Massachusetts Institute of Technology (MIT), USA, 7-9 November 2014. Elsevier Procedia Computer Science, Vol. 41 (2014), pp. 6-14.
- Antonio Lieto, Daniele P. Radicioni and Valentina Rho, A Common-Sense Conceptual Categorization System Integrating Heterogeneous Proxytypes and the Dual Process of Reasoning". In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, July 2015, pp. 875-881. AAAI press.
- Antonio Lieto, Daniele P. Radicioni and Valentina Rho "Dual PECCS: A Cognitive System for Conceptual Representation and Categorization" in Journal of Experimental & Theoretical Artificial Intelligence (JETAI), Vol. 29(2), pp. 433-452.
- Antonio Lieto, "Heterogeneous Proxytypes Extended: Integrating Theory-like Representations and Mechanisms with Prototypes and Exemplars", in Proceedings of BICA 2018, Springer Advances in Intelligent Systems and Computing, 2019.

The fact: in the past few days, thanks to a late notification by Google Scholar, I have discovered that HP hypothesis has been proposed, in a 2017 Ph.D Thesis at the Faculty of Education at the University of Johannesburg entitled "Towards a Science Education Learning Environment for Student Teachers of the Foundation Phase" (by E.C.A. Kok), as a tool for "foundation phase school teachers" (that I have just discovered being "school teachers teaching children the foundations of reading, writing and literacy and are also responsible for helping children to develop their thinking skills") to reflect on what kind of stimulus to present in order to let the students to activate the "right proxy-representation" in their working memory (by using the HPH terminology) as a trigger for letting learning take place.

Below an excerpt directly taken from the above-mentioned Ph.D. Thesis

I have to say that I did not think (at all) to the possible implications of the HP in the context of teaching and of science education and I am really honored that such a model has been considered as a possible teaching tool. Probably this could be an area of application to explore further (in particular for the conceptual change issue) in the next future and, hopefully, it could be a nice example of cross-fertilization between different disciplines. Let's see...

P.S. Below a couple of photos of the original "drawings" where the idea of concepts as "heterogeneous proxytypes" was conceived. I was having breakfast with a cappuccino and asked for a take-away chocolate croissant. At the moment when the barista gave me the croissant, this simple idea came to my mind and I draw some notes directly on the croissant "envelope" (that I have kept since then).

First diagram sketch of the heterogeneous proxytypes hypothesis (on a croissant take-away "envelope"). Click to see the entire picture.

Back of the "envelope"

Knowledge graph

noreply@blogger.com (Antonio Lieto) — Fri, 19 Jun 2020 17:18:00 +0000

Alphabet sembra aver associato un po' di conosenza al "mio" grafo (che visualizzo quando sono loggato nell'account Google).

Online lecture on Cognitive Artificial Systems

noreply@blogger.com (Antonio Lieto) — Mon, 15 Jun 2020 16:07:00 +0000

I was invited to give a talk on the cognitive paradigm in AI research by the National University of "Kyiv-Mohyla Academy" in Kiev. Due to the COVID-19 crisis, the lecture was given online. The video of the online lecture is available below.

Ranking

noreply@blogger.com (Antonio Lieto) — Sat, 09 May 2020 22:42:00 +0000

A shortlist of relevant insights from the book Ranking: The Unwritten Rules of the Social Game We All Play by Péter Érdi

Ranking and hierarchies are crucial in the animal behavior (see the "pecking order" in the chicken society)
Rankings can always be manipulated and are never completely "objective"
Mechanisms leading to cyclic dominance do not allow to determine transitive ranks (see the Condorcet Paradox)
Rankings are unavoidable in natural societies (and probably also in artificial and "hybrid" ones)
Our "rationally bounded" minds create biased and manipulable rankings
A "good enough" decision (à la Simon) is a good decision
No voting/ranking system is perfect (see the Arrow law)>
Google is an example of a tech company that has based his success on a ranking algorithm
rank reversal can be a source of manipulation
Ignorance and Manipulation generate deviations from "true" rankings
Metrics can be (and often are) "gamed" to manipulate rankings (see Campbell's law)
Algorithms and Ranking systems even if biased are still better that subjective evaluations
Future and "Personal Ranking>
Reputation is important for ranking and evolutionarily social organization (it can be manipulated also)
Trust and Reputation are important also in modern Recommender Systems (from e-commerce to dating portals)

Influencing the others' minds

noreply@blogger.com (Antonio Lieto) — Mon, 16 Mar 2015 08:59:00 +0000

The paper: "Influencing the Others’ Minds: An Experimental Evaluation of the Use and Efficacy of Fallacious-Reducible Arguments in Web and Mobile Technologies" (co-authored with Fabiana Vernero) is now available on line on Psychnology Journal.

Full reference: Lieto, A. and Vernero, F. (2014). Influencing the Others’ Minds: An Experimental Evaluation of the Use and Efficacy of Fallacious-Reducible Arguments in Web and Mobile Technologies. PsychNology Journal, 12(3), 87 - 105.

H. Simon and AI

noreply@blogger.com (Antonio Lieto) — Thu, 12 Mar 2015 17:47:00 +0000

"Artificial Intelligence can have two purposes. One is to use the power of computers to augment human thinking, just as we use motors to augment human or horse power[...]. The other is to use a computer's artificial intelligence to understand how humans think. In a humanoid way.
If you test your programs not merely by what they can accomplish, but how they accomplish it, then you are really doing cognitive science, you are using AI to understand the human mind".

From Stewart, Doug (1994). "Herbert A. Simon Interview". Omni, 16(9), 72-89.

Back from Boston (@ MIT) for the BICA Conference

noreply@blogger.com (Antonio Lieto) — Wed, 12 Nov 2014 17:53:00 +0000

Tornato da Boston, dove sono stato per la conferenza BICA 2014, in cui ho presentato un articolo su aspetti abbastanza nuovi del mio lavoro di ricerca (in cui sto cercando di integrare il lavoro svolto in ambito rappresentazione della conoscenza con il settore delle architetture cognitive). Sono molto contento di essere stato qui.

BICA e' una conferenza molto stimolante e quest'anno si è tenuta al MIT (Massachusetts Institute of Technology), una sorta di "tempio sacro" nel settore dell'Intelligenza Artificiale.
Finito il talk ho avuto la possibilità, nei giorni successivi, di visitare anche Harvard (praticamente attaccata al posto in cui si è svolta la conferenza). Fantastica esperienza: ho imparato tante cose e avuto moltissime occasioni di confronto con gli altri partecipanti (tra cui il leggendario Patrick Winston e il fisico Max Tegmark).

Obstacles to human level - AI development (from Mc Carthy)

noreply@blogger.com (Antonio Lieto) — Tue, 29 Apr 2014 09:58:00 +0000

"The computer science world is still suffering from a 1990s fit of pseudo-practicality that is inimical to the solution of difficult scientific problems. Lip service is given to basic research, and a lot of basic research is done, but the initiation of ambitious research by young people is hampered by the now prevalent doctrine that “basic research” should be done in connection with applied problems that have been identified by the competent committees. I think that Newell and Minsky and I would have had a much harder time initiating AI research if the atmosphere of the 1950s had been like that of the 1990s. Computer science suffers more than older fields from this disease, one of the main carriers of which was the Com- puter Science and Telecommunications Board of the National Research Council. Its worst sin was merging computer science with computer engineering in its harmful, narrow-minded report Computing the Future [30].Nevertheless, the main problem in reaching human level AI is not the politics of science and technology but the intrinsic difficulty of the scientific problems". [30] C. Science, N.R.C. Telecommunications Board, Computing the Future: A Broader Agenda for Computer Science and Engineering, National Academies Press, 1992. From: Mc Carthy, John, From here to human-level AI, Artificial Intelligence, 171 (2007) 1174–1182

Leo

noreply@blogger.com (Antonio Lieto) — Sat, 02 Nov 2013 15:07:00 +0000

Non è facile scrivere di Leonardo. Se ne è andato il 1 ottobre scorso e la sua perdita si sente più forte man mano che passano i giorni. E' stato un grandissimo professore e un grande uomo. Nell'anno e mezzo che ho avuto il privilegio di collaborare con lui mi ha insegnato tanto. Abbiamo organizzato insieme la tavola rotonda su "Ontologie e Modellazione del Senso comune" presso la conferenza di mid-term dell'Associazione Italiana di Scienze Cognitive (a Trento) ed è stata la persona che maggiormente ha appoggiato la mia idea di istituire un workshop internazionale sui legami tra Intelligenza Artificiale e Scienze Cognitive (idea concretizzatasi poi nel workshop "Artificial Intelligence and Cognition" (AIC 2013) che si terrà a Torino il prossimo 3 dicembre nell'ambito della conferenza internazionale dell'Associazione Italiana di Intelligenza Artificiale.

E' stata una persona corretta, limpida e brillante. Un esempio (non solo per me ma per tutto il suo gruppo di ricerca). Grazie Leo, grazie di tutto.

Things done

noreply@blogger.com (Antonio Lieto) — Tue, 14 May 2013 10:24:00 +0000

It was a long period that I was unable to update the blog. Many things happened. I'll try to list the main here: i) I will be here at the University of Turin for at least another year since I got another post-doc research grant for working on ontologies and knowledge representation systems in the field of cultural heritage (under the Prof. Rossana Damiano), ii) I'm going to organize (with Marco Cruciani) an international workshop on AI and Cognition within the International Conference of the Italian Association for Artificial Intelligence (AI*IA 2013) that will be held in Turin the next december. iii) It is a travelling period: I was in Finland (February, for the ConChaMo4 Workshop, invited talk), in Paris for the WebScience'13 Conference and I will be in Riga (Latvia) tomorrow for a presentation at the 9th International Symposium of Cognition, Logic and Communication. Next step are Trento and Finland again in June and, maybe, Hamburg (Germany) in August for another workshop (on computational models of narratives) of the CogSci 2013 conference. Many other things going on. I will return on this when I will have more time.

Fabio Varesano

noreply@blogger.com (Antonio Lieto) — Sun, 13 Jan 2013 21:22:00 +0000

E' passata una settimana da quando sono tornato al lavoro in Dipartimento qui a Torino. Non posso negare che la mancanza di Fabio Varesano, scomparso improvvisamente durante il periodo natalizio, si sente tantissimo. Fabio era nella sua stanza di fronte alla mia. Avevamo fatto subito amicizia. Era un ragazzo brillante (grande esperto di Arduino e di wearable computing), di talento e di una incredibile bontà. Non vederlo al suo posto in questi giorni è stata dura.

notes

noreply@blogger.com (Antonio Lieto) — Sun, 02 Dec 2012 22:30:00 +0000

ho ripreso a scrivere due righe sulle peripezie che mi capitano in alcuni viaggi. oggi sono qui: http://appunti-diviaggio.blogspot.fi/2012/12/helsinki.html

Update

noreply@blogger.com (Antonio Lieto) — Fri, 24 Aug 2012 10:04:00 +0000

I'm back to my blog after one year of stop. Many things happened (one year is one year).

The most important:

First: Unfortunately my grandparent (from my father) is no longer with us. So sad.

Second: I finished my doctoral program and obtained my Ph.D. at the University of Salerno in June 2012.

Third: In May 2012 I moved to the Department od Computer Science of the University of Turin for a post-doc fellowship.

Fourth: I met a lot of interesting people at the conferences, workshops and summer schools attended this year (e.g. at sssw2012) and, with some of them, we are trying to build a research collaboration.

In this period I'm full of work but also have a lot of ideas that I'd like to develop (but the things are two: or I really have no time or I'm unable to organize properly my time).

I hope to update the blog more frequently in the next months. Keep in touch.