SEGUNDO SEMINARIO DE LECTURA 2015

INTELIGENCIA ARTIFICIAL Y GERENCIACoordinador: Nelson Lara

Centro de Investigaciones Postdoctorales (CIPOST) Postgrado en Ciencias Administrativas (PCA)

Universidad Central de Venezuela (UCV)Lugar: Planta baja edificio Rodolfo Quintero

Horario: 7:00 A.M. a 9:00 A.M.

Después del impacto positivo que se desprende del primer Seminario de Lectura 2015, al utilizar uno de sus Artículos como referencia para introducir cambios en nuestros Postgrados, que con toda seguridad nos ubicarán en el “estado del arte”, ahora vamos a continuar dando pinceladas en el foco del estudio de la gerencia, como lo expresaba Simon “gerenciar es decidir”, de allí que nos hayamos centrado en los últimos años en trabajar la Teoría de la Decisión desde sus diferentes aproximaciones. Ahora, en el segundo Seminario de Lectura 2015 retomaremos el tema de la Inteligencia Artificial, teniendo como telón de fondo la “gerencia”.

Cuando hablamos de retomar es porque la IA es un tema que tuvo un auge en los 80, luego un decaimiento y hoy en día con los avances tecnológicos, especialmente en la neurociencia, cobra un vigor académicamente importante. De allí mis queridos amigos, que como una tarea previa al inicio del Seminario el próximo lunes 28 de Septiembre, tendremos que ponernos al día leyendo el Artículo publicado en 1993: A Research Perspective: Artificial Intelligence, Management and Organizations, de Peter Duchessi University at Albany, Albany, NY, USA, Robert O'Keefe Rensselaer Polytechnic Institute, Troy, NY, USA y Daniel O'Leary University of Southern California, Los Angeles, CA, USA, el cual se anexa.

Como es nuestra costumbre de muchos años, el Seminario de Lectura se cumple en el horario de 7:00 A.M. a 9:00 A.M. de manera estrictamente puntual, dirigido a investigadores natos: profesores, estudiantes y ejecutivos. Los artículos están en el idioma inglés, lo cual es un plus en la construcción académica personal. El Seminario se desarrollara en nueve sesiones, donde cada participante deberá previamente “leer, estudiar, reflexionar y complementar” el contenido del material correspondiente, el cual será debatido en análisis por todos y cada uno de los participantes, de acuerdo al siguiente programa:

PROGRAMA

1. 28-09-2015

Artificial Intelligence and Consciousness (2007) Drew McDermottYale University

Abstract: Consciousness is only marginally relevant to artificial intelligence (AI), because to most researchers in the field other problems seem more pressing. However, there have been proposals for how consciousness would be accounted for in a complete computational theory of the mind, from theorists such as Dennett, Hofstadter, McCarthy, McDermott, Minsky, Perlis, Sloman, and Smith. One can extract from these speculations a sketch of a theoretical synthesis, according to which consciousness is the property a system has by virtue of modeling itself as having sensations and making free decisions. Critics such as Harnad and Searle have not succeeded in demolishing a priori this or any other computational theory, but no such theory can be verified or refuted until and unless AI is successful in finding computational solutions of difficult problems such as vision, language, and locomotion.

2. 2. Artificial Intelligence and Human Thinking (2012)

Robert Kowalski

Imperial College London United Kingdom rak@doc.ic.ac.uk

Abstract

Research in AI has built upon the tools and techniques of many different disciplines, including formal logic, probability theory, decision theory, management science, linguistics and philosophy. However, the application of these disciplines in AI has necessitated the development of many enhancements and extensions. Among the most powerful of these are the methods of computational logic. I will argue that computational logic, embedded in an agent cycle, combines and improves upon both traditional logic and classical decision theory. I will also argue that many of its methods can be used, not only in AI, but also in ordinary life, to help people improve

their own human intelligence without the assistance of computers.

3. 12-10-2015

Artificial Intelligence as a Positive and Negative Factor in Global Risk (2008)

Eliezer Yudkowsky

Machine Intelligence Research Institute

Yudkowsky,Eliezer.2008.“Artificial Intelligence as a Positive and Negative Factor in Global Risk.” In Global Catastrophic Risks, edited by Nick Bostrom and Milan M. Ćirković, 308–345. New York: Oxford University Press.

4. 19-10-2015

Human Intelligence Needs Artificial Intelligence (2012)

Daniel S. Weld and Mausam Peng Dai

Dept of Computer Science and Engineering University of Washington Seattle, WA-98195 {weld,mausam,daipeng}@cs.washington.edu

Abstract

Crowd sourcing platforms, such as Amazon Mechanical Turk, have enabled the construction of scalable applications for tasks ranging from product categorization and photo tagging to audio transcription and translation. These vertical applications are typically realized with complex, self-managing workflows that guarantee quality results. But constructing such workflows is challenging, with a huge number of alternative decisions for the designer to consider. We argue the thesis that “Artificial intelligence methods can greatly simplify the process of creating and managing complex crowdsourced workflows.” We present the design of CLOWDER, which uses machine learning to continually refine models of worker performance and task difficulty. Using

these models, CLOWDER uses decision-theoretic optimizationto1) choose between alternative workflows, 2) optimize parameters for a workflow, 3) create personalized interfaces for individual workers, and 4) dynamically control the workflow. Preliminary experience suggests that these optimized workflows are significantly more economical (and return higher quality output) than those generated by humans.

5. 26-10-2015

Aligning Superintelligence with Human Interests: A Technical Research Agenda (2015)

Nate Soares and Benja Fallenstein

Machine Intelligence Research Institute {nate,benja}@intelligence.org

6. 02-11-2015

The Value Learning Problem (2015)

Nate Soares Machine Intelligence Research Institute nate@intelligence.org

AbstractA super intelligent machine would not automatically act as intended: it will act as programmed, but the fit between human intentions and formal specification could be poor. We discuss methods by which a system could be constructed to learn what to value. We highlight open problems specific to inductive value learning (from labeled training data), and raise a number of questions about the construction of systems which model the preferences of their operators and act accordingly.

7. 09-11-2015

Research priorities for robust and beneficial artificial intelligence (2015)The initial version of this document was drafted by Stuart Russell, Daniel Dewey & Max Tegmark, with major input from Janos Kramar & Richard Mallah, and reflects valuable feedback from Anthony Aguirre, Erik Brynjolfsson, Ryan Calo, Tom Dietterich, Dileep George, Bill Hibbard, Demis Hassabis, Eric Horvitz, Leslie Pack Kaelbling, James Manyika, Luke Muehlhauser, Michael Osborne, David Parkes, Heather Roff, Francesca Rossi, Bart Selman, Murray Shanahan, and many others.

Executive Summary: Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to research how to maximize these benefits while avoiding potential pitfalls. This document gives numerous examples (which should by no means be construed as an exhaustive list) of such worthwhile research aimed at ensuring that AI remains robust and beneficial.

8. 23-11-2015

Corrigibility (2015)Nate Soares and Benja Fallenstein and Eliezer YudkowskyMachine Intelligence Research Institute {nate,benja,eliezer}@intelligence.orgStuart Armstrong Future of Humanity Institute University of Oxford stuart.armstrong@philosophy.ox.ac.uk

AbstractAs artificially intelligent systems grow in intelligence and capability, some of their available options may allow them to resist intervention by their programmers. We call an AI system “corrigible” if it cooperates with what its creators regard as a corrective intervention, despite default incentives for rational agents to resist attempts to shut them down or modify their preferences. We introduce the notion of corrigibility and analyze utility functions that attempt to make an agent shut down safely if a shutdown button is pressed, while avoiding incentives to prevent the button from being pressed or cause the button to be pressed, and while ensuring propagation of the shutdown behavior as it creates new subsystems or self-modifies. While some proposals are interesting, none have yet been demonstrated to satisfy all of our intuitive desiderata, leaving this simple problem in corrigibility wide-open.

9. 30-11-2015

Future Progress in Artificial Intelligence: A Survey of Expert Opinion

(2014)Vincent C. Müller & Nick Bostrom Future of Humanity Institute, Department of Philosophy & Oxford Martin School, University of Oxford. b)Anatolia College/ACT, Thessaloniki

Müller, Vincent C. and Bostrom, Nick (forthcoming 2014), ‘Future progress in artificial intelligence: A Survey of Expert Opinion, in Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library; Berlin: Springer).

Abstract: There is, in some quarters, concern about high–level machine intelligence and super intelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. We thus designed a brief questionnaire and distributed it to four groups of experts in 2012/2013. The median estimate of respondents was for a one in two chance that high level machine intelligence will be developed around 2040-2050, rising to a nine in ten chance by 2075. Experts expect that systems will move on to superintelligence in less than 30 years thereafter. They estimate the chance is about one in three that this development turns out to be ‘bad’ or ‘extremely bad’ for humanity.

El Seminario de Lectura se realiza en el marco del Centro de Investigaciones Postdoctorales (CIPOST- UCV) y del Postgrado en Ciencias Administrativas (PCA) de FaCES-UCV.

Se entregará un Certificado a todos los participantes y adicionalmente se abrirá la oportunidad para que cada participante escriba un Artículo, el cual luego de ser arbitrado positivamente, pasa a integrar una publicación.

Atentamente,

Profesor Nelson Lara