The troika of artificial intelligence, emotional intelligence and customer intelligence

Author(s):  
Pritam Babu Sharma ◽  
Shikha N. Khera ◽  
Manish Sharma
2021 ◽  
Author(s):  
Erik Hermann

AbstractThe increasing humanization and emotional intelligence of AI applications have the potential to induce consumers’ attachment to AI and to transform human-to-AI interactions into human-to-human-like interactions. In turn, consumer behavior as well as consumers’ individual and social lives can be affected in various ways. Following this reasoning, I illustrate the implications and research opportunities related to consumers’ (potential) attachment to humanized AI applications along the stages of the consumption process.


Author(s):  
Jesús Ignacio Martínez García

Resumen: Se efectúa una aproximación a los derechos humanos desde la perspectiva de la inteligencia en sus distintas facetas, especialmente desde la inteligencia artificial pero también desde la inteligencia institucional y la emocional. Aparecen como derechos inteligentes, que desarrollan la inteligencia de los individuos y hacen a las sociedades más inteligentes. Se presenta su dimensión cognitiva y su capacidada para cuestionar programas. Son instancias críticas que preservan la dignidad de los seres humanos en su compleja interacción con las máquinas inteligentes y estimulan un pensamiento no mecánico. Absrtact: This article aims to give an approach to the human rights from the point of view of intelligence in their different types, especially from artificial intelligence, but also from institutional and emotional intelligence. They appear as smart rights that develop the intelligence of the individuals and make societies more intelligent. Their cognitive dimension is shown, as well as their capacity to question programs. They are critical instances that preserve the human dignity in their complex interaction with intelligent machines and stimulate a not-mechanical thinking.


10.2196/25372 ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. e25372
Author(s):  
Ronda Sturgill ◽  
Mary Martinasek ◽  
Trine Schmidt ◽  
Raj Goyal

Background Emotional intelligence (EI) and mindfulness can impact the level of anxiety and depression that an individual experiences. These symptoms have been exacerbated among college students during the COVID-19 pandemic. Ajivar is an app that utilizes artificial intelligence (AI) and machine learning to deliver personalized mindfulness and EI training. Objective The main objective of this research study was to determine the effectiveness of delivering an EI curriculum and mindfulness techniques using an AI conversation platform, Ajivar, to improve symptoms of anxiety and depression during this pandemic. Methods A total of 99 subjects, aged 18 to 29 years, were recruited from a second-semester group of freshmen students. All participants completed the online TestWell Wellness Inventory at the start and end of the 14-week semester. The comparison group members (49/99, 49%) were given routine mental wellness instruction. The intervention group members (50/99, 51%) were required to complete Ajivar activities in addition to routine mental wellness instruction during the semester, which coincided with the onset of the COVID-19 pandemic. This group also completed assessments to evaluate for anxiety, using the 7-item Generalized Anxiety Disorder (GAD-7) scale, and depression, using the 9-item Patient Health Questionnaire (PHQ-9). Results Study participants reported a mean age of 19.9 (SD 1.94) years; 27% (27/99) of the group were male and 60% (59/99) identified as Caucasian. No significant demographic differences existed between the comparison and intervention groups. Subjects in the intervention group interacted with Ajivar for a mean time of 1424 (SD 1168) minutes. There was a significant decrease in anxiety, as measured by the GAD-7: the mean score was 11.47 (SD 1.85) at the start of the study compared to 6.27 (SD 1.44) at the end (P<.001). There was a significant reduction in the symptoms of depression measured by the PHQ-9: the mean score was 10.69 (SD 2.04) at the start of the study compared to 6.69 (SD 2.41) at the end (P=.001). Both the intervention and comparison groups independently had significant improvements in the TestWell Wellness Inventory from pretest to posttest. The subgroups in the social awareness and spirituality inventories showed significant improvement in the intervention group. In a subgroup of participants (11/49, 22%) where the GAD-7 was available during the onset of the COVID-19 pandemic, there was an increase in anxiety from the start of the study (mean score 11.63, SD 2.16) to mid-March (ie, onset of the pandemic) (mean score 13.03, SD 1.48; P=.23), followed by a significant decrease at the end of the study period (mean score 5.9, SD 1.44; P=.001). Conclusions It is possible to deliver EI and mindfulness training in a scalable way using the Ajivar app during the COVID-19 pandemic, resulting in improvements in anxiety, depression, and EI in the college student population.


Author(s):  
Sandeep Singh ◽  
Chetan Sharma ◽  
Shamneesh Sharma ◽  
Neeraj Kumar Verma

Author(s):  
Huma Shah ◽  
Kevin Warwick

The Turing Test, originally configured as a game for a human to distinguish between an unseen and unheard man and woman, through a text-based conversational measure of gender, is the ultimate test for deception and hence, thinking. So conceived Alan Turing when he introduced a machine into the game. His idea, that once a machine deceives a human judge into believing that they are the human, then that machine should be attributed with intelligence. What Turing missed is the presence of emotion in human dialogue, without expression of which, an entity could appear non-human. Indeed, humans have been confused as machine-like, the confederate effect, during instantiations of the Turing Test staged in Loebner Prizes for Artificial Intelligence. We present results from recent Loebner Prizes and two parallel conversations from the 2006 contest in which two human judges, both native English speakers, each concomitantly interacted with a non-native English speaking hidden-human, and jabberwacky, the 2005 and 2006 Loebner Prize bronze prize winner for most human-like machine. We find that machines in those contests appear conversationally worse than non-native hidden-humans, and, as a consequence attract a downward trend in highest scores awarded to them by human judges in the 2004, 2005 and 2006 Loebner Prizes. Analysing Loebner 2006 conversations, we see that a parallel could be drawn with autistics: the machine was able to broadcast but it did not inform; it talked but it did not emote. The hidden-humans were easily identified through their emotional intelligence, ability to discern emotional state of others and contribute with their own ‘balloons of textual emotion’.


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