A Study on Exponential Advancement of Unmeasurable Artificial Intelligence in Destructing the Power of Human Decision Making in Near Future

2017 ◽  
Vol 6 (10) ◽  
pp. 70
Author(s):  
M. Kumarasamy ◽  
G. N. K. Suresh Babu
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Significant Risk ◽  
Machine Intelligence ◽  
Health Science ◽  
Human Capabilities ◽  
Human Decision ◽  
Almost All ◽  
The Military ◽  
Near Future

Machine intelligence will in near future replace human capabilities in almost all organizations across the world. Manufacturers, Services sectors and institutions will rapidly move on to Artificial superintelligence that will surpass human decision making power to bring significant risk for humanity. Advances in artificial intelligence will transform modern life by reshaping transportation, health, science, finance, and the military. This development turns out to be ‘bad’ or ‘extremely bad’ for humanity.

Who’s making the decisions? How managers can harness artificial intelligence and remain in charge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Digital Transformation ◽  
Decision Processes ◽  
Decision Makers ◽  
Content Type ◽  
Human Decision ◽  
Practical Implications

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.

scholarly journals Applicability of Artificial Intelligence in Decision-Making for Land Forces

2021 ◽  
Vol 30 (2) ◽  
pp. 039-054
Author(s):  
Paul Tudorache
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Research Methodology ◽  
Research Paper ◽  
The Other ◽  
Military Operations ◽  
Other Hand ◽  
The Military

Similar to other fields, also in the military one, the Artificial Intelligence has become recently an evident solution for optimizing specific processes and activities. Therefore, this research paper aims to highlight the potential uses of Artificial Intelligence in the military operations carried out by the Land Forces. In this regard, analysing the framework of the operations process and applying suitable research methodology, the main findings are related to AI’s contributions in optimizing commander’s decisions during the progress of planning and execution. On the other hand, picturing the AI upgrated combat power of the Land Forces is another significant result of this study.

scholarly journals How should we regulate artificial intelligence?

2018 ◽  
Vol 376 (2128) ◽  
pp. 20170360 ◽  
Author(s):  
Chris Reed
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Decision Making ◽  
Current System ◽  
General System ◽  
Fundamental Rights ◽  
Ex Post ◽  
Ex Ante ◽  
Human Decision

Using artificial intelligence (AI) technology to replace human decision-making will inevitably create new risks whose consequences are unforeseeable. This naturally leads to calls for regulation, but I argue that it is too early to attempt a general system of AI regulation. Instead, we should work incrementally within the existing legal and regulatory schemes which allocate responsibility, and therefore liability, to persons. Where AI clearly creates risks which current law and regulation cannot deal with adequately, then new regulation will be needed. But in most cases, the current system can work effectively if the producers of AI technology can provide sufficient transparency in explaining how AI decisions are made. Transparency ex post can often be achieved through retrospective analysis of the technology's operations, and will be sufficient if the main goal is to compensate victims of incorrect decisions. Ex ante transparency is more challenging, and can limit the use of some AI technologies such as neural networks. It should only be demanded by regulation where the AI presents risks to fundamental rights, or where society needs reassuring that the technology can safely be used. Masterly inactivity in regulation is likely to achieve a better long-term solution than a rush to regulate in ignorance. This article is part of a discussion meeting issue ‘The growing ubiquity of algorithms in society: implications, impacts and innovations'.

Artificial Intelligence Inroads Into HR

2022 ◽  
pp. 231-246
Author(s):  
Swati Bansal ◽  
Monica Agarwal ◽  
Deepak Bansal ◽  
Santhi Narayanan
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Human Resources ◽  
Generation Y ◽  
Industry 4.0 ◽  
Career Aspirations ◽  
Work Life ◽  
Human Decision ◽  
The Right ◽  
Talent Acquisition

Artificial intelligence is already here in all facets of work life. Its integration into human resources is a necessary process which has far-reaching benefits. It may have its challenges, but to survive in the current Industry 4.0 environment and prepare for the future Industry 5.0, organisations must penetrate AI into their HR systems. AI can benefit all the functions of HR, starting right from talent acquisition to onboarding and till off-boarding. The importance further increases, keeping in mind the needs and career aspirations of Generation Y and Z entering the workforce. Though employees have apprehensions of privacy and loss of jobs if implemented effectively, AI is the present and future. AI will not make people lose jobs; instead, it would require the HR people to upgrade their skills and spend their time in more strategic roles. In the end, it is the HR who will make the final decisions from the information that they get from the AI tools. A proper mix of human decision-making skills and AI would give organisations the right direction to move forward.

scholarly journals Viewpoint: When Will AI Exceed Human Performance? Evidence from AI Experts

2018 ◽  
Vol 62 ◽  
pp. 729-754 ◽  
Author(s):  
Katja Grace ◽  
John Salvatier ◽  
Allan Dafoe ◽  
Baobao Zhang ◽  
Owain Evans
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
High School ◽  
Public Policy ◽  
Human Performance ◽  
Health Science ◽  
Modern Life ◽  
North Americans ◽  
Large Survey ◽  
The Military

Advances in artificial intelligence (AI) will transform modern life by reshaping transportation, health, science, finance, and the military. To adapt public policy, we need to better anticipate these advances. Here we report the results from a large survey of machine learning researchers on their beliefs about progress in AI. Researchers predict AI will outperform humans in many activities in the next ten years, such as translating languages (by 2024), writing high-school essays (by 2026), driving a truck (by 2027), working in retail (by 2031), writing a bestselling book (by 2049), and working as a surgeon (by 2053). Researchers believe there is a 50% chance of AI outperforming humans in all tasks in 45 years and of automating all human jobs in 120 years, with Asian respondents expecting these dates much sooner than North Americans. These results will inform discussion amongst researchers and policymakers about anticipating and managing trends in AI. This article is part of the special track on AI and Society.

scholarly journals The Role of Artificial Intelligence in Many Dental Specialties

2021 ◽  
Vol 41 ◽  
pp. 03005
Author(s):  
Choirunisa Nur Humairo ◽  
Aquarina Hapsari ◽  
Indra Bramanti
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Clinic Management ◽  
Pediatric Dentist ◽  
Dental Procedures ◽  
Evolution Of Technology ◽  
Near Future

Background: Technology has become a fundamental part of human living. The evolution of technology has been advantageous to science development, including dentistry. One of the latest technology that draw many attention is Artificial Intelligence (AI). Purpose: The aim of this review is to explain the use of AI in many disciplines of dental specialties and its benefit. Reviews: The application of Artificial Intelligence may be beneficial for all dental specialties, varying from pediatric dentist to oral surgeon. In dental clinic management, AI may assist in medical record as well as other paperwork. AI would also give a valuable contribution in important dental procedures, such as diagnosis and clinical decision making. It helps the dentist deliver the best treatment for the patients. Conclusion: The latest development of Artificial Intelligence is beneficial for dental practitioner in the near future. It is considered as a breakthrough of the 21st century to support the diagnostic procedure and decision making in clinical practice. The use of AI can be applied in most of dental specialties.

scholarly journals A Review: Artificial Intelligent Approach for Enhancing Adaptability in an Adaptive E-Learning Environment

2021 ◽  
Vol 10 (4) ◽  
pp. 37-42
Author(s):  
M.P.L. Perera
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Decision Making ◽  
Fuzzy Logic ◽  
Artificial Intelligent ◽  
Human Decision ◽  
Decision Making Processes ◽  
E Learning ◽  
Intelligent Approach ◽  
Learning Frameworks

Adaptive e-learning the aim is to fill the gap between the pupil and the educator by discussing the needs and skills of individual learners. Artificial intelligence strategies that have the potential to simulate human decision-making processes are important around adaptive e-Learning. This paper explores the Artificial techniques; Fuzzy Logic, Neural Networks, Bayesian Networks and Genetic Algorithms, highlighting their contributions to the notion of the adaptability in the sense of Adaptive E-learning. The implementation of Artificial Neural Networks to resolve problems in the current Adaptive e-learning frameworks have been established.

We Are All Stakeholders in an AI-supplemented World

2020 ◽  
Vol 03 (04) ◽  
pp. 2050014
Author(s):  
Basil C. Bitas ◽  
Manoj Harjani
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Decision Making ◽  
The United States ◽  
Ethical Sensitivity ◽  
Successful Management ◽  
Human Capabilities ◽  
Transformative Power ◽  
New Phase

Artificial Intelligence (AI) is moving into a new phase where it is demonstrating the ability to supplement or replace humans across a range of decision-making activities. The transformative power of AI will require sensible regulation and heightened ethical sensitivity to ensure that it enhances rather than undermines human capabilities and values. The successful management of AI will necessitate coordination at the national, international and supranational levels among stakeholders of all types. Moreover, the shape of an AI-supplemented world will be heavily influenced by the rivalry between China and the United States as the world’s leading economic and AI powers. This paper will weave together the above themes to outline the relevant issues and stakes and the manner in which they can be managed to yield a productive AI-supplemented future, wherein AI’s promise is maximized and its potential perils avoided or mitigated.

Instruction Modeling

2020 ◽  
pp. 78-106
Author(s):  
George A. Khachatryan
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Expert Systems ◽  
Classroom Teachers ◽  
High Quality ◽  
Teaching Expertise ◽  
Intelligence System ◽  
The Core ◽  
Russian Mathematics ◽  
Human Decision

This chapter describes the core ideas behind instruction modeling. A promising way to improve mathematics instruction is to import successful approaches from other countries; however, it is exceptionally difficult to do this, since instructional traditions are cultural and the volume of teaching expertise that needs to be transferred is vast. Computers offer a possible way to ease the barriers. Expert systems (invented c. 1970) are a type of artificial intelligence system that uses rules to mimic human decision-making. Following the pattern suggested by expert systems, an instruction modeler studies high-quality offline instruction and then designs computer programs that aim to recreate this instruction. Many important activities cannot be automated, and therefore instruction modeling is necessarily blended learning: some instruction takes place online, while other activities are led by classroom teachers. To illustrate these ideas, this chapter describes several instruction modeling programs created by Reasoning Mind. It also discusses Russian mathematics education, explaining why it is a successful instructional tradition and a suitable choice for instruction modeling.

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