Managing Uncertainty in AI-Enabled Decision Making and Achieving Sustainability

Artificial intelligence (AI) has been applied to various decision-making tasks. However, scholars have yet to comprehend how computers can integrate decision making with uncertainty management. Obtaining such comprehension would enable scholars to deliver sustainable AI decision-making applications that adapt to the changing world. This research examines uncertainties in AI-enabled decision-making applications and some approaches for managing various types of uncertainty. By referring to studies on uncertainty in decision making, this research describes three dimensions of uncertainty, namely informational, environmental and intentional. To understand how to manage uncertainty in AI-enabled decision-making applications, the authors conduct a literature review using content analysis with practical approaches. According to the analysis results, a mechanism related to those practical approaches is proposed for managing diverse types of uncertainty in AI-enabled decision making.

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Perceived Effectiveness of Artificial Intelligence based Decision Support System in a Clinical Setting: A Systematic Literature Review (Preprint)

10.2196/preprints.19282 ◽

2020 ◽

Author(s):

Avishek Choudhury

Keyword(s):

Artificial Intelligence ◽

Decision Making ◽

Decision Support ◽

Literature Review ◽

Decision Support System ◽

Support System ◽

Clinical Setting ◽

Clinical Decision Making ◽

Theoretical Perspective ◽

Care Providers

UNSTRUCTURED Objective: The potential benefits of artificial intelligence based decision support system (AI-DSS) from a theoretical perspective are well documented and perceived by researchers but there is a lack of evidence showing its influence on routine clinical practice and how its perceived by care providers. Since the effectiveness of AI systems depends on data quality, implementation, and interpretation. The purpose of this literature review is to analyze the effectiveness of AI-DSS in clinical setting and understand its influence on clinician’s decision making outcome. Materials and Methods: This review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta- Analyses reporting guidelines. Literature will be identified using a multi-database search strategy developed in consultation with a librarian. The proposed screening process consists of a title and abstract scan, followed by a full-text review by two reviewers to determine the eligibility of articles. Studies outlining application of AI based decision support system in a clinical setting and its impact on clinician’s decision making, will be included. A tabular synthesis of the general study details will be provided, as well as a narrative synthesis of the extracted data, organised into themes. Studies solely reporting AI accuracy an but not implemented in a clinical setting to measure its influence on clinical decision making were excluded from further review. Results: We identified 8 eligible studies that implemented AI-DSS in a clinical setting to facilitate decisions concerning prostate cancer, post traumatic stress disorder, cardiac ailment, back pain, and others. Five (62.50%) out of 8 studies reported positive outcome of AI-DSS. Conclusion: The systematic review indicated that AI-enabled decision support systems, when implemented in a clinical setting and used by clinicians might not ensure enhanced decision making. However, there are very limited studies to confirm the claim that AI based decision support system can uplift clinicians decision making abilities.

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Literature review and discussion on collaborative decision making approaches in Industry 4.0

FME Transaction ◽

10.5937/fme2104817s ◽

2021 ◽

Vol 49 (4) ◽

pp. 817-826

Author(s):

A.C. Sousa ◽

A.F. Bertachini ◽

C. Cunha ◽

R. Chaves ◽

M.L.R. Varela

Keyword(s):

Artificial Intelligence ◽

Decision Making ◽

Literature Review ◽

Mathematical Models ◽

Concurrent Engineering ◽

Industry 4.0 ◽

Collaborative Decision Making ◽

Collaborative Decision

Nowadays, companies are faced with an increasingly higher level of competition while trying to adapt to the exigencies imposed by the Industry 4.0, regarding its usually referred dimensions and pillars, among which one that although is not so often referred is also expressing an increasing visibility and importance, related to collaboration, and more specifically to collaborative decision making and co-working. Thus, in this paper an analysis is carried out regarding the evolution of publications that have been put available over the last decade about collaborative decision making approaches, varying from approaches based on mathematical models up to the application of artificial intelligence and other kind of approaches. Moreover, a discussion about the relation between collaborative decision making, concurrent engineering and Industry 4.0 dimensions is also done.

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Innovative Systems Structure for Real Corporate Governance

International Journal of System Dynamics Applications ◽

10.4018/ijsda.20211001oa01 ◽

2021 ◽

Vol 10 (4) ◽

pp. 0-0

Keyword(s):

Decision Making ◽

Corporate Governance ◽

Economic Development ◽

Content Analysis ◽

Literature Review ◽

Systematic Literature Review ◽

Wealth Creation ◽

The World ◽

Socio Economic Development ◽

Large Corporations

All around the world, trends of globalization and industrialization have been experienced both in the development of large corporations and conglomerates. These larges firms contribute enormously to the socio-economic development of countries. Adopting a systematic literature review method with in-depth content analysis, the paper explores the concept of corporate governance holistically from systems lens and proposes an innovative systems structure-based framework namely Cultural Legal Oriented Value Embedded (CLOVE) for corporate governance to enable better decision making. In this paper, the structure proposed refers to components of culture, legal, orientation, value embeddedness that may be internal or external to the firm and these components are those, which will have a role in undertaking effective corporate governance and wealth creation for shareholders and the firm.

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Artificial Intelligence in Marketing

Advances in Business Information Systems and Analytics - Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry ◽

10.4018/978-1-7998-6985-6.ch016 ◽

2021 ◽

pp. 342-365

Author(s):

Özge Sığırcı

Keyword(s):

Artificial Intelligence ◽

Decision Making ◽

Consumer Behavior ◽

Literature Review ◽

Ethical Decision ◽

Ethical Decision Making ◽

Previous Literature ◽

Human Interactions ◽

Consumer Vulnerability ◽

Shed Light

The purpose of this chapter is to shed light on the consumer-AI interaction in the marketplace. By this aim, the chapter uses a literature review approach. The previous literature examining AI from a consumer behavior perspective is reviewed, and the findings are compiled in a meaningful flow. According to the review, we see that the traditional marketplace is shaped by AI from only human-to-human interactions to human-to-AI and AI-to-AI interactions. In this new marketplace, while consumers interact with AI, they gain new experiences and feel positive or negative because of these experiences. Also, they build different relationships with AI, such as servant, master, or partner. Besides these relationships, there are still concerns about AI that are related to privacy, algorithmic biases, consumer vulnerability, unemployment, and ethical decision making.

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Is it alright to use artificial intelligence in digital health? A systematic literature review on ethical considerations

Health Informatics Journal ◽

10.1177/14604582211052391 ◽

2021 ◽

Vol 27 (4) ◽

pp. 146045822110523

Author(s):

Nicholas RJ Möllmann ◽

Milad Mirbabaie ◽

Stefan Stieglitz

Keyword(s):

Artificial Intelligence ◽

Decision Making ◽

Literature Review ◽

Systematic Literature Review ◽

Digital Health ◽

Status Quo ◽

Ethical Principles ◽

Ethical Considerations ◽

Autonomous Decision ◽

The Status

The application of artificial intelligence (AI) not only yields in advantages for healthcare but raises several ethical questions. Extant research on ethical considerations of AI in digital health is quite sparse and a holistic overview is lacking. A systematic literature review searching across 853 peer-reviewed journals and conferences yielded in 50 relevant articles categorized in five major ethical principles: beneficence, non-maleficence, autonomy, justice, and explicability. The ethical landscape of AI in digital health is portrayed including a snapshot guiding future development. The status quo highlights potential areas with little empirical but required research. Less explored areas with remaining ethical questions are validated and guide scholars’ efforts by outlining an overview of addressed ethical principles and intensity of studies including correlations. Practitioners understand novel questions AI raises eventually leading to properly regulated implementations and further comprehend that society is on its way from supporting technologies to autonomous decision-making systems.

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Legal forms and ways of application of artificial intelligence technology in making corporate decisions by the board of directors: problems and prospects

SHS Web of Conferences ◽

10.1051/shsconf/202110602012 ◽

2021 ◽

Vol 106 ◽

pp. 02012

Author(s):

Olga Sushkova

Keyword(s):

Artificial Intelligence ◽

Decision Making ◽

Corporate Governance ◽

Board Of Directors ◽

Three Dimensions ◽

Corporate Decisions ◽

The Board Of Directors ◽

Artificial Intelligence Technology ◽

Legal Forms ◽

The Impact

This study investigates the impact of scientific and technological advances and adaptation of artificial intelligence on corporate governance practices. It applies or can be applied in three dimensions - business, technology, and society. Therefore, to assess the necessity, feasibility, effectiveness, and responsibility of decision-making automation at the Board of Directors (supervisory body of a legal entity) to ensure effective corporate governance, it is necessary to consider all normative regulators in the field of corporate law. Based on an assessment of the potential and limitations of human and machine learning for effective decision-making at the level of the collegial governance body, the Board of Directors, the paper proposes five AI-based governance scenarios, i.e., supportive, augmented, enhanced, autonomous, and autopoietic, that can shape the governance of organizations today, tomorrow, and in the future. It is important to understand the implications of such AI-enabled governance in the areas where the Board is empowered to make certain corporate decisions.

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Evaluation of the Academic Setting in Spain 1This study was financed by the University of Oviedo.

European Journal of Psychological Assessment ◽

10.1027/1015-5759.11.2.133 ◽

1995 ◽

Vol 11 (2) ◽

pp. 133-137 ◽

Cited By ~ 1

Author(s):

Juan Fernández ◽

Miguel A. Mateo ◽

José Muñiz

Keyword(s):

Higher Education ◽

Decision Making ◽

Social Climate ◽

Three Dimensions ◽

Academic Setting ◽

Teaching And Research ◽

Evaluation Questionnaire ◽

University Teachers ◽

The University

The conditions are investigated in which Spanish university teachers carry out their teaching and research functions. 655 teachers from the University of Oviedo took part in this study by completing the Academic Setting Evaluation Questionnaire (ASEQ). Of the three dimensions assessed in the ASEQ, Satisfaction received the lowest ratings, Social Climate was rated higher, and Relations with students was rated the highest. These results are similar to those found in two studies carried out in the academic years 1986/87 and 1989/90. Their relevance for higher education is twofold because these data can be used as a complement of those obtained by means of students' opinions, and the crossing of both types of data can facilitate decision making in order to improve the quality of the work (teaching and research) of the university institutions.

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