Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Performance in the Workplace: a Critical Evaluation of Cognitive Enhancement
Download
index.pdf
Date
2022-04-01
Author
Acartürk, Cengiz
Mücen, Barış
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
328
views
127
downloads
Cite This
The popular debates about the future organization of work through artificial intelligence technologies focus on the replacement of human beings by novel technologies. In this essay, we oppose this statement by closely following what has been developed as AI technologies and analyzing how they work, specifically focusing on research that may impact work organizations. We develop this argument by showing that the recent research and developments in AI technologies focus on developing accurate and precise performance models, which in turn shapes organizational patterns of work. We propose that the increased interest in the relationship between human cognition and performance will shortly bring human cognition to the focus on AI systems in workplaces. More specifically, we claim that the cognitive load measurement will shape human performance in manufacturing systems shortly.
Subject Keywords
Performance
,
Cognitive sciences
,
Artificial intelligence
,
Mind as a machine
,
Cognitive enhancement
,
DEEP BRAIN-STIMULATION
,
WORKING-CONDITIONS
,
MENTAL-HEALTH
,
JOB STRESS
,
FOLLOW-UP
,
MACHINE
,
WORKERS
,
BURNOUT
,
LEVEL
URI
https://hdl.handle.net/11511/97278
Journal
NANOETHICS
DOI
https://doi.org/10.1007/s11569-021-00407-6
Collections
Graduate School of Informatics, Article
Suggestions
OpenMETU
Core
Ethics of artificial intelligence: moral responsibility of self-driving cars and sex robots
Özmen, M. Cem; Demir, Mehmet Hilmi; Department of Philosophy (2019)
This thesis analyzes the ethical impacts of the Artificial Intelligence (AI) applications. AI applications are used in many areas to make daily life more comfortable and efficient. They are used for cleaning houses, taking care of old or sick people, working at dangerous jobs replacing human beings, giving medical advisory, preventing fraudulent situations in finance, etc. Similarly, the usage of sex robots, self-driving cars, translation tools, image and emotion recognition applications, etc. are expected ...
Online mining of human deep intention by proactive environment changes using deep neural networks
Er, Nur Baki; Erkmen, Aydan Müşerref; Department of Electrical and Electronics Engineering (2015)
This thesis focuses on surfacing human deep intention, which is known or assumed, in a smart environment that consists of autonomous robotic systems which can interact with the human. Deep intentions are defined as kind of actions that humans would like to behave but pushed deeper in the stack of the intentions in a daily life. The purpose of the designed system is to observe the human in the smart room for a while and to analyze human’s behaviors to offer the optimal set of system behavior to surface a des...
Evaluating the convergence of high-performance computing with big data, artificial intelligence and cloud computing technologies
Dildar Korkmaz, Yeşim; Eren, Pekin Erhan; Kayabay, Kerem; Department of Information Systems (2023-1-24)
The advancements in High-Performance Computing (HPC), Big Data, Artificial Intelligence (AI), and Cloud Computing technologies have led to a convergence of these fields, resulting in the emergence of significant improvements for a wide range of fields. Identifying the state of development of technology convergence and forecasting promising technology convergence is critical for both academia and industry. That's why technology assessment and forecasting for HPC-Big Data-AI-Cloud Computing convergence is nee...
Traversability: A Case Study for Learning and Perceiving Affordances in Robots
Ugur, Emre; Şahin, Erol (SAGE Publications, 2010-06-01)
The concept of affordances, introduced in psychology by J. J. Gibson, has recently attracted interest in the development of cognitive systems in autonomous robotics. In earlier work (Sahin, Cakmak, Dogar, Ugur, & Ucoluk), we reviewed the uses of this concept in different fields and proposed a formalism to use affordances at different levels of robot control. In this article, we first review studies in ecological psychology on the learning and perception of traversability in organisms and describe how the ex...
In relation: re-assessing responsiveness through human-machine interaction
Erdinç, Melda; Mennan, Zeynep; Department of Architecture (2022-11-14)
Advances in cybernetics, material research and network technologies affected the volume and the interpretation of human involvement in responsive architecture. The study scrutinizes the notion of responsiveness and its reflection(s) on/in the field of architecture. In this respect, it aims to investigate the role of the human in responsive bodies and seeks to redefine the boundaries of the participants through human-machine interaction in a responsive manner. The thesis offers a reassessment of the in-rela...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
C. Acartürk and B. Mücen, “Performance in the Workplace: a Critical Evaluation of Cognitive Enhancement,”
NANOETHICS
, pp. 0–0, 2022, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/97278.