Contradiction of modern and social-humanitarian artificial intelligence

Raikov, Alexander; Pirani, Massimiliano

doi:10.1108/k-01-2022-0057

Cited by 5 publications

(6 citation statements)

References 31 publications

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“…Therefore, some recent initiatives have started to explore the contact between natural and artificial artifacts and computers. A notable one is the definition and study of Symbiotic Autonomous Systems (Kaynak et al, 2021;Saracco et al, 2021;Wang et al, 2021;Raikov A. N. and Pirani, 2022). Efimov et al (2023) noted many unexplained aspects in processing human speech and thinking: AI cannot understand language in the human sort of sense.…”

Section: Xai a Reviewmentioning

confidence: 99%

“…The most natural example of such dependence is the logico-mathematical entailment, but it is not unique. For instance, even probabilistic forms of causality can provide explanations in scientific realms (Pearl, 2009(Pearl, , 2018 under well-controlled methodologies like the do-calculus, beyond logic representations or closed-form mathematical expressions (Raikov A. N. and Pirani, 2022).…”

Section: Structures Of Explanationmentioning

confidence: 99%

“…Simon (1996) explains the irreducibility of the undoubtedly causal underlying mechanism. It is now possible to express a generalized view of causality that lets an agent, be it natural or artificial, express causality in the hybrid reality that concerns the new ways of interactions between artificial and natural intelligence actors (Pirani et al, 2022;Raikov A. N. and Pirani, 2022).…”

Section: Structures Of Explanationmentioning

confidence: 99%

“…An infinite regression process occurs in some cases that is difficult to handle with a closed-form solution. The recursiveness of the contexts of cognition must be approached in a highly flexible and open but structurally determined manner (Bonci et al, 2018;Raikov A. N. and Pirani, 2022). The contradiction of the semantics of reality occurs if we try to use one unified language for cognition.…”

Section: Introductionmentioning

confidence: 99%

“…The solution proposed to this contradiction is switching nimbly across one and another representation language with the same flexibility as humans seemingly do. The agility that allows traversing multiple semiotic systems must reside in the mystery of general AI and maybe with some seeds of consciousness (Raikov A. N. and Pirani, 2022). In any case, the complexity and number of computations required to obtain automated explanations grow exponentially, which often forces us to abandon the search for and inclusion of explanation components in an AI system.…”

Section: Introductionmentioning

confidence: 99%

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Accelerating human–computer interaction through convergent conditions for LLM explanation

Raikov,

Giretti,

Pirani

et al. 2024

Front. Artif. Intell.

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The article addresses the accelerating human–machine interaction using the large language model (LLM). It goes beyond the traditional logical paradigms of explainable artificial intelligence (XAI) by considering poor-formalizable cognitive semantical interpretations of LLM. XAI is immersed in a hybrid space, where humans and machines have crucial distinctions during the digitisation of the interaction process. The author’s convergent methodology ensures the conditions for making XAI purposeful and sustainable. This methodology is based on the inverse problem-solving method, cognitive modeling, genetic algorithm, neural network, causal loop dynamics, and eigenform realization. It has been shown that decision-makers need to create unique structural conditions for information processes, using LLM to accelerate the convergence of collective problem solving. The implementations have been carried out during the collective strategic planning in situational centers. The study is helpful for the advancement of explainable LLM in many branches of economy, science and technology.

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Section: Xai a Reviewmentioning

confidence: 99%

Section: Structures Of Explanationmentioning

confidence: 99%

Section: Structures Of Explanationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Accelerating human–computer interaction through convergent conditions for LLM explanation

Raikov,

Giretti,

Pirani

et al. 2024

Front. Artif. Intell.

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What makes electricity consumers change their behavior? Influence of attitude and perceived impact of DR programs on awareness

Bârã

Oprea

2023

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PurposeIn this study, the authors propose a confirmatory factor analysis (CFA) to create a tenable measurement model and identify the factors that have the potential to enhance awareness of pro-environmental measures. The successful implementation of demand response (DR) programs and their required infrastructure is significant for moving towards green energy communities and a better environment for living. Not only can renewable energy capacities contribute to this desideratum, but also electricity consumers who, until the last decade, have played a passive role.Design/methodology/approachTo answer these questions, a complex data set of 243 post-trial questions created by the Irish CER are analyzed using first-order and hierarchical CFA models with several SAS procedures (PROC CALIS, MIANALYZE). The questionnaire was launched to over 3,000 electricity consumers from Ireland that were participants to a trial program after the installation of smart metering systems and implementation of DR programs.FindingsThe effect of five latent factors – positive attitude, negative attitude, perceived impact of own actions, price- and incentive-DR programs – is measured. With a bi-factor CFA measurement model, the authors assess that they significantly influence the electricity consumers' awareness.Research limitations/implicationsHowever, these findings have to be backed up by relevant information and simulations showing consumers benefits in exchange to their efforts. They have research implications on the design of the business models and DR programs pointing out the importance of benefits and fairness of value sharing mechanisms within energy communities.Practical implicationsThus, the electricity consumers may change their consumption behavior as they positively perceive the implementation of DR programs.Originality/valueThis paper fulfills an identified need to study post-trial questionnaire and reveal latent factors that make electricity consumer change their behavior.

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Domestic tourism and the effects of behavioral changes, government-media trust and moderation of “maintenance of country image”: theoretical analysis

Yasir,

Hu,

Aktan

et al. 2024

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PurposeContemporary changes have occurred in country-level policies and tourists’ intentions in recent years. The role of maintaining a country’s image is trendy in crisis control but has not yet been discussed in domestic tourism research. Extending the Stimulus Organism Response model, this study aims to focus on “trustable WOM creation” in China. In addition, it aimed to discover how behavioral changes encourage domestic tourism intention (DTI).Design/methodology/approachThis study explored the mediating role of DTI and the moderating role of maintenance of country image (MCI) for trustable word of mouth (WOM) creation. Using the snowball sampling technique, a structural equation modeling analysis (Smart PLS-4) was employed to analyze the data of 487 Chinese tourists.FindingsFindings confirm that behavioral changes positively encourage domestic tourism and discourage international tourism, with significant negative moderation by MCI. MCI has an insignificant positive moderating effect between government-media trust and DTI. Furthermore, DTI positively and directly affects the creation of trustable WOM. In addition, it had a 20% mediation effect (VAF%) between behavioral changes and WOM creation, higher than the rejected mediation effect (12%), in the causal relationship between government-media trust and WOM creation.Practical implicationsWOM creation varies from different behavioral changes, but findings suggest that government-media trust and DTI influenced it significantly. Based on the study findings, the government and media can enhance domestic tourism by maintaining the country’s image. These findings both encourage and control the recovery of tourism.Originality/valueThis study provides a theoretical explanation for tourists' behavioral changes during the pandemic. Moreover, it shows that despite avoiding international tourism due to behavioral changes and government-media trust, MCI moderation with the mediation effect of DTI can create trustable WOM. To the best of the authors’ knowledge, this is the first study to theoretically promote tourism through DTI-induced psychology as a mediator and an organism affect prevailing among Chinese tourists.

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Contradiction of modern and social-humanitarian artificial intelligence

Cited by 5 publications

References 31 publications

Accelerating human–computer interaction through convergent conditions for LLM explanation

Accelerating human–computer interaction through convergent conditions for LLM explanation

What makes electricity consumers change their behavior? Influence of attitude and perceived impact of DR programs on awareness

Domestic tourism and the effects of behavioral changes, government-media trust and moderation of “maintenance of country image”: theoretical analysis

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