Beyond Extraordinary: Theorizing Artificial Intelligence and the Self in Daily Life

This study integrates the theory of multiple selves within the theoretical framework of dynamic motivational activation (DMA) to identify the dynamic patterns of multiple self-concepts (i.e., the potential self, the actual self) in multitasking (e.g., primary and secondary activities) in daily life. A three-week experience sampling study was conducted on college students. Dynamic panel modeling results suggest that the self-concepts are both sustaining and shifting in daily activities and media activities. Specifically, the potential and actual selves sustained themselves over time in primary and secondary activities, but they also shifted from one to another to achieve a balance in primary activities over time. Interestingly, secondary activities were not driven by the alternative self-concept in primary activities, but instead, by the emotional experiences of primary activities. Furthermore, the findings identified that multitasking to fulfill their actual self did not motivate people to re-prioritize their potential self later.

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Artificial Intelligence in Biomedicine: A Legal Insight

BioTech ◽

10.3390/biotech10030015 ◽

2021 ◽

Vol 10 (3) ◽

pp. 15

Author(s):

Takis Vidalis

Keyword(s):

Artificial Intelligence ◽

Personal Data ◽

Health Data ◽

The Self ◽

Data Handling ◽

Direct Control ◽

Eu Legislation ◽

Attending Physicians ◽

Self Learning ◽

The Eu

The involvement of artificial intelligence in biomedicine promises better support for decision-making both in conventional and research medical practice. Yet two important issues emerge in relation to personal data handling, and the influence of AI on patient/doctor relationships. The development of AI algorithms presupposes extensive processing of big data in biobanks, for which procedures of compliance with data protection need to be ensured. This article addresses this problem in the framework of the EU legislation (GDPR) and explains the legal prerequisites pertinent to various categories of health data. Furthermore, the self-learning systems of AI may affect the fulfillment of medical duties, particularly if the attending physicians rely on unsupervised applications operating beyond their direct control. The article argues that the patient informed consent prerequisite plays a key role here, not only in conventional medical acts but also in clinical research procedures.

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Armut und Autobiographie – Versuch einer Begriffsanalyse

ETHICS IN PROGRESS ◽

10.14746/eip.2014.2.6 ◽

2014 ◽

Vol 5 (2) ◽

pp. 69-76

Author(s):

Małgorzata Bogaczyk-Vormayr

Keyword(s):

Oral History ◽

Daily Life ◽

Concept Analysis ◽

Migration Background ◽

The Self ◽

Working Paper ◽

Non Fiction ◽

And Migration ◽

Childhood Suffering ◽

Short Working

This short working paper is my first attempt to present my concept analysis of relation between the poverty experiences – e.g. childhood suffering by war and migration background, daily life suffering by starvation, abuse, racism etc. – and the process of self-understanding and resilience with the help of an oral history or literature (non-fiction as much as fiction novels). I reflect Wilhelm Dilthey’s opinion about the distinction between autobiography and Self-biography, and I present the Self-biography as a right way to concretize the themes of poverty and exclusion.

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Taming Artificial Intelligence in Psychiatry and Pain Medicine

Overlapping Pain and Psychiatric Syndromes ◽

10.1093/med/9780190248253.003.0029 ◽

2020 ◽

pp. 399-412

Author(s):

Usef Faghihi ◽

Sioui Maldonado-Bouchard ◽

Mario Incayawar

Keyword(s):

Artificial Intelligence ◽

United States ◽

Health Care ◽

Deep Learning ◽

State Of The Art ◽

Daily Life ◽

Health Care Sector ◽

Human Cells ◽

Pain Medicine ◽

Medical Field

Today, deep learning (DL) algorithms are intertwined with our daily life. This subdomain of artificial intelligence (AI) technology is used to unlock your phone by only detecting your face, find the best path from work to your home or vice versa, or detect anomalies in the human cells taken for lab tests. Yet, although AI technology is helping in many fields, whether it has done so in the medical field is debatable. DL lacks reasoning; it is unable to determine the causes of events. This is especially crucial when it comes to the health care sector. At this point, computers cannot help physicians with their duties. On the contrary, they are the cause of burnout in more than half of physicians in United States. One of the causes of burnout repeatedly pointed out by physicians is the digitalization of medicine. This chapter presents some of the AI approaches that could help physicians. It also discusses the current limitations and dangers inherent to many of today’s state-of-the-art AI systems. The authors provide some ideas about the future of AI in pain medicine and psychiatry.

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Uber and the making of an Algopticon - Insights from the daily life of Montreal drivers

Capital & Class ◽

10.1177/0309816820904031 ◽

2020 ◽

Vol 44 (2) ◽

pp. 241-260

Author(s):

Rabih Jamil

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Daily Life ◽

The World ◽

Taxi Industry ◽

Platform Economy

Using machine learning and artificial intelligence, Uber has been disrupting the world taxi industry. However, the Uber algorithmic apparatus managed to perfectionize the scalable decentralized tracking and surveillance of mobile living bodies. This article examines the Uber surveillance machinery and discusses the determinants of its algorithmically powered ‘all-seeing power’. The latter is being figured as an Algopticon that reinvents Bentham’s panopticon in the era of the platform economy.

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Psychometric evaluation of the Self-Awareness in Daily Life-3 Scale (SADL-3) for the assessment of self-awareness after acquired brain injury

Brain Injury ◽

10.1080/02699052.2019.1566969 ◽

2019 ◽

Vol 33 (5) ◽

pp. 598-609

Author(s):

Ieke Winkens ◽

Arno Prinsen ◽

Annemieke Meijerink ◽

Caroline Van Heugten ◽

Rudolf Ponds

Keyword(s):

Brain Injury ◽

Daily Life ◽

Psychometric Evaluation ◽

Acquired Brain Injury ◽

The Self ◽

Self Awareness

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Losing Face

Religions ◽

10.3390/rel11110545 ◽

2020 ◽

Vol 11 (11) ◽

pp. 545

Author(s):

Philip J. Ivanhoe

Keyword(s):

Artificial Intelligence ◽

Communist Party ◽

Chinese Communist Party ◽

East Asian ◽

The Self ◽

Self Reflection ◽

Extensive System ◽

The Chinese Communist Party ◽

And Control ◽

Monitor And Control

Notions of “face” play a central role in traditional East Asian ethics and, in particular, in Confucian views about the self and its cultivation. Awareness of and attention to face is central to self-reflection and evaluation and, when properly employed, motivate one to continue to strive to improve oneself morally. Today, the Chinese Communist Party seeks to monitor and control its population by means of an extensive system of surveillance that is increasingly controlled by artificial intelligence programs. This not only undermines traditional conceptions of face but ultimately the role and ability of the party to set and enforce its own view of what Chinese citizens should seek and pursue.

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SUSSOL—Using Artificial Intelligence for Greener Solvent Selection and Substitution

Molecules ◽

10.3390/molecules25133037 ◽

2020 ◽

Vol 25 (13) ◽

pp. 3037 ◽

Cited By ~ 3

Author(s):

Hannes Sels ◽

Herwig De Smet ◽

Jeroen Geuens

Keyword(s):

Neural Network ◽

Artificial Intelligence ◽

Physical Properties ◽

The Self ◽

Self Organizing Map ◽

Solvent Selection ◽

Sustainable Solvents ◽

Cluster A ◽

User Friendly ◽

Intuitive Sense

Solvents come in many shapes and types. Looking for solvents for a specific application can be hard, and looking for green alternatives for currently used nonbenign solvents can be even harder. We describe a new methodology for solvent selection and substitution, by applying Artificial Intelligence (AI) software to cluster a database of solvents based on their physical properties. The solvents are processed by a neural network, the Self-organizing Map of Kohonen, which results in a 2D map of clusters. The resulting clusters are validated both chemically and statistically and are presented in user-friendly visualizations by the SUSSOL (Sustainable Solvents Selection and Substitution Software) software. The software helps the user in exploring the solvent space and in generating and evaluating a list of possible alternatives for a specific solvent. The alternatives are ranked based on their safety, health, and environment scores. Cases are discussed to demonstrate the possibilities of our approach and to show that it can help in the search for more sustainable and greener solvents. The SUSSOL software makes intuitive sense and in most case studies, the software confirms the findings in literature, thus providing a sound platform for selecting the most sustainable solvent candidate.

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Promoting Students’ Well-Being by Developing Their Readiness for the Artificial Intelligence Age

Sustainability ◽

10.3390/su12166597 ◽

2020 ◽

Vol 12 (16) ◽

pp. 6597 ◽

Cited By ~ 1

Author(s):

Yun Dai ◽

Ching-Sing Chai ◽

Pei-Yi Lin ◽

Morris Siu-Yung Jong ◽

Yanmei Guo ◽

...

Keyword(s):

Artificial Intelligence ◽

School District ◽

Teaching Effectiveness ◽

Well Being ◽

Female Students ◽

The Self ◽

Primary Students ◽

Male Students ◽

Survey Questionnaire ◽

Readiness To Learn

This study developed and validated an instrument to measure students’ readiness to learn about artificial intelligence (AI). The designed survey questionnaire was administrated in a school district in Beijing after an AI course was developed and implemented. The collected data and analytical results provided insights regarding the self-reported perceptions of primary students’ AI readiness and enabled the identification of factors that may influence this parameter. The results indicated that AI literacy was not predictive of AI readiness. The influences of AI literacy were mediated by the students’ confidence and perception of AI relevance. The students’ AI readiness was not influenced by a reduction in their anxiety regarding AI and an enhancement in their AI literacy. Male students reported a higher confidence, relevance, and readiness for AI than female students did. The sentiments reflected by the open-ended responses of the students indicated that the students were generally excited to learn about AI and viewed AI as a powerful and useful technology. The student sentiments confirmed the quantitative findings. The validated survey can help teachers better understand and monitor students’ learning, as well as reflect on the design of the AI curriculum and the associated teaching effectiveness.

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SELF-IMPOSED ETHICAL GUIDELINES FOR AI IN EDUCATION

SOCIETY INTEGRATION EDUCATION Proceedings of the International Scientific Conference ◽

10.17770/sie2020vol1.5048 ◽

2020 ◽

Vol 1 ◽

Author(s):

Anri Leimanis

Keyword(s):

Artificial Intelligence ◽

The Self ◽

Ethical Principles ◽

Educational Institutions ◽

Public Agencies ◽

Ethical Guidelines ◽

Ai Ethics ◽

Global Discourse ◽

The Common ◽

Ethics Guidelines

Advances in Artificial Intelligence (AI) applications to education have encouraged an extensive global discourse on the underlying ethical principles and values. In a response numerous research institutions, companies, public agencies and non-governmental entities around the globe have published their own guidelines and / or policies for ethical AI. Even though the aim for most of the guidelines is to maximize the benefits that AI delivers to education, the policies differ significantly in content as well as application. In order to facilitate further discussion about the ethical principles, responsibilities of educational institutions using AI and to potentially arrive at a consensus concerning safe and desirable uses of AI in education, this paper performs an evaluation of the self-imposed AI ethics guidelines identifying the common principles and approaches as well as drawbacks limiting the practical and legal application of the policies.

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