Reasons, Coherence, and Group Rationality

Philosophy and Phenomenological Research, EarlyView

Discovering the Dynamics of Smart Business Networks

In an earlier paper ,was discussed the necessary evolution from smart business networks, as based on process need satisfaction and governance, into business genetics [1] based on strategic bonds or decay and opportunistic complementarities. This paper will describe an approach and diffusion algorithms whereby to discover the dynamics of emergent smart business network structures and their performance in view of collaboration patterns over time. Some real life early analyses of dynamics are discussed based on cases and date from the high tech sector. Lessons learnt from such cases are also given on overall smart network dynamics with respect to local interaction strategies, as modelled like in business genetics by individual partner profiles, goals and constraints. It shows the weakness of static "business operating systems", as well as the possibly destabilizing clustering effects amongst nodes linked to filtering, evaluation and own preferences.dynamics;network performance;smart business networks;SBN;business genetics

Discovering the dynamics of smart business networks

Earlier research discussed the necessary evolution from smart business networks, as based on process need satisfaction and governance, into business genetics [1] based on strategic bonds or decay and opportunistic complementarities. This paper will describe an approach and diffusion algorithms whereby to discover the dynamics of emergent smart business network structures and their performance in view of collaboration patterns over time. Some real life early analyses of dynamics are discussed based on cases and date from the high tech sector. Lessons learnt from such cases are also given on overall smart network dynamics with respect to local interaction strategies, as modelled like in business genetics by individual partner profiles, goals and constraints. It shows the weakness of static “business operating systems”, as well as the possibly destabilizing clustering effects amongst nodes linked to filtering, evaluation and own preferences.smart business networks; business genetics; network performance; SBN; dynamics

Equality of Voice: Towards Fair Representation in Crowdsourced Top-K Recommendations

To help their users to discover important items at a particular time, major websites like Twitter, Yelp, TripAdvisor or NYTimes provide Top-K recommendations (e.g., 10 Trending Topics, Top 5 Hotels in Paris or 10 Most Viewed News Stories), which rely on crowdsourced popularity signals to select the items. However, different sections of a crowd may have different preferences, and there is a large silent majority who do not explicitly express their opinion. Also, the crowd often consists of actors like bots, spammers, or people running orchestrated campaigns. Recommendation algorithms today largely do not consider such nuances, hence are vulnerable to strategic manipulation by small but hyper-active user groups. To fairly aggregate the preferences of all users while recommending top-K items, we borrow ideas from prior research on social choice theory, and identify a voting mechanism called Single Transferable Vote (STV) as having many of the fairness properties we desire in top-K item (s)elections. We develop an innovative mechanism to attribute preferences of silent majority which also make STV completely operational. We show the generalizability of our approach by implementing it on two different real-world datasets. Through extensive experimentation and comparison with state-of-the-art techniques, we show that our proposed approach provides maximum user satisfaction, and cuts down drastically on items disliked by most but hyper-actively promoted by a few users.Comment: In the proceedings of the Conference on Fairness, Accountability, and Transparency (FAT* '19). Please cite the conference versio

How Insensitive: Principles, Facts and Normative Grounds in Cohen’s Critique of Rawls

Cohen’s hostility to Rawls’ justification of the Difference Principle by social facts spawned Cohen’s general thesis that ultimate principles of justice and morality are fact-insensitive, but explain how any fact-sensitive principle is grounded in facts. The problem with this thesis, however, is that when facts F ground principle P, reformulating this relation as the "fact-insensitive" conditional “If F, then P” is trivial and thus explanatorily impotent. Explanatory, hence justificatory, force derives either from subsumption under more general principles, or precisely exhibiting value in light of relevant (actual or hypothetical) facts. In examples where no subsumption occurs, actual facts trivially become hypothetical facts in "fact-insensitive" conditionals, an empty formalism. Indeed, Rawls’ grounding of principles of justice in “conditions of life” can easily be reformulated as a conditional principle “sensitive” only to hypothetical such conditions, and thus formally fact-insensitive in Cohen's sense, for all Cohen’s ire against Rawls’s grounding.Moreover, any plausible “ultimate fact-insensitive principle” must be intricately qualified, which tacit ceteris paribus clauses mask. Each qualification implies prioritisation of one principle over another in conceivable circumstances, and wherever the now qualified principle is given scope, that too implies prioritisation over competing principles in typical circumstances. Any principle is thus sensitive to conceivable circumstances of application, as recognised by more sophisticated intuitionisms. Non-trivial ultimate principles – luck egalitarianism, act utilitarianism, etc. - require defense, which inevitably involves showing how they best interpret and respond to facts about human needs, goals, and capacities in predictable circumstances. Finally, the substantive debate between Rawls and Cohen about which facts are relevant to the DP is only obscured by the doctrine of fact-insensitivity

Aggregating Moral Preferences

Preference-aggregation problems arise in various contexts. One such context, little explored by social choice theorists, is metaethical. “Ideal-advisor” accounts, which have played a major role in metaethics, propose that moral facts are constituted by the idealized preferences of a community of advisors. Such accounts give rise to a preference-aggregation problem: namely, aggregating the advisors’ moral preferences. Do we have reason to believe that the advisors, albeit idealized, can still diverge in their rankings of a given set of alternatives? If so, what are the moral facts (in particular, the comparative moral goodness of the alternatives) when the advisors do diverge? These questions are investigated here using the tools of Arrovian social choice theory

Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings