Advancing Collective Intelligence in Human–AI Collaboration: Foundations for the COHUMAIN Framework DOI Creative Commons

Sohana Akter

Deleted Journal, Journal Year: 2024, Volume and Issue: 4(1), P. 252 - 261

Published: May 22, 2024

Artificial Intelligence (AI) powered machines are increasingly mediating our work and many of managerial, economic, cultural interactions. While technology enhances individual capabilities in ways, how can we ensure that the sociotechnical system as a whole—comprising complex web hundreds human–machine interactions—is exhibiting collective intelligence? Research on interactions has been conducted within different disciplinary silos, resulting social science models underestimate vice versa. Integrating these diverse perspectives methods is crucial at this juncture. To truly advance understanding important rapidly evolving area, need frameworks to facilitate research bridges boundaries. This paper advocates for establishing an interdisciplinary domain—Collective Human-Machine (COHUMAIN). It outlines agenda holistic approach designing developing dynamics systems. illustrate envision domain, describe recent sociocognitive architecture, transactive systems model intelligence, which articulates critical processes underlying emergence functioning intelligence human–AI collaborations.

Language: Английский

Ethical Considerations in AI Simulations for Designing Assistive Technologies DOI Creative Commons

Evin Miser,

Orcun Sarioguz

Deleted Journal, Journal Year: 2024, Volume and Issue: 4(1), P. 209 - 218

Published: May 20, 2024

Current ethical debates on the use of artificial intelligence (AI) in healthcare approach AI technology three primary ways. First, they assess risks and potential benefits current AI-enabled products using checklists. Second, propose ex ante lists values relevant to design development assistive technologies. Third, advocate for incorporating moral reasoning into AI's automation processes. These perspectives dominate discourse, as evidenced by a brief literature summary. We fourth approach: viewing methodological tool aid reflection. This involves an simulation concept informed elements: 1) stochastic human behavior models based behavioral data simulating realistic scenarios, 2) qualitative empirical value statements regarding internal policy, 3) visualization components illustrate impact variable changes. aims inform interdisciplinary field about anticipated challenges or trade-offs specific settings, prompting re-evaluation implementation plans. is particularly useful applications involving complex behaviors limited communication resources, such dementia care individuals with cognitive impairments. While does not replace reflection, it allows detailed, context-sensitive analysis during process before implementation.Finally, we discuss quantitative methods enabled simulations these enhance traditional thought experiments future-oriented assessments.

Language: Английский

Citations

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An Expedited Examination of Responsible AI Frameworks: Directing Ethical AI Development DOI Creative Commons

Jeff Shuford

Deleted Journal, Journal Year: 2024, Volume and Issue: 4(1), P. 241 - 251

Published: May 22, 2024

In recent years, the rapid expansion of Artificial Intelligence (AI) and its integration into various aspects daily life have ignited significant discourse on ethical considerations governing application. This study addresses these concerns by swiftly reviewing multiple frameworks designed to guide development utilization Responsible AI (RAI) applications. Through this exploration, we analyze each framework's alignment with Software Development Life Cycle (SDLC) phases, revealing a predominant focus Requirements Elicitation phase, limited coverage other stages. Furthermore, note scarcity supportive tools, predominantly offered private entities. Our findings underscore absence comprehensive framework capable accommodating both technical non-technical stakeholders across all SDLC thus notable gap in current landscape. sheds light imperative need for unified encompassing RAI principles accessible users varying expertise objectives.

Language: Английский

Citations

0
Towards a Platform for Robot-Assisted Minimally Supervised Hand Therapy: Design and Pilot Usability Evaluation DOI Creative Commons

Venkata Dinesh Reddy Kalli

Deleted Journal, Journal Year: 2024, Volume and Issue: 4(1), P. 230 - 240

Published: May 22, 2024

Background Robot-assisted therapy has the potential to enhance doses post-stroke, addressing often insufficient treatment of hand function in clinical settings and after discharge. Traditionally, these systems have been complex required therapist supervision. To better leverage robot-assisted therapy, we propose a platform designed for minimal supervision present preliminary evaluation its immediate usability, key challenge neglected real-world applications. This approach could increase by enabling single train multiple patients simultaneously, as well supporting independent training clinics or at home. Methods We implemented design changes on rehabilitation robot, focusing minimally-supervised therapy. involved developing new physical graphical user interfaces creating two functional exercises aimed motor coordination, somatosensation, memory. Ten participants with chronic stroke evaluated platform's usability reported their perceived workload during session. The ability use independently was assessed using checklist. Results After brief familiarization period, were able perform session, needing assistance only 13.46% (range: 7.69–19.23%) tasks. They rated interface highly System Usability Scale, scores 85.00 (75.63–86.88) 73.75 (63.13–83.75) out 100, respectively. Nine indicated they would frequently. within acceptable ranges. most challenging tasks identified object grasping simultaneous control forearm pronosupination stiffness discrimination. Discussion Our findings indicate that device can be safely intuitively used upon first exposure adhering requirements. highlighted specific challenges need addressed enable use. complement conventional providing increased existing resources establishing continuum care transitions from clinic

Language: Английский

Citations

0
Data Sources as a Driver for Market-Oriented Tourism Organizations: A Bibliometric Perspective DOI Creative Commons

Amizur Nachshoni

Deleted Journal, Journal Year: 2024, Volume and Issue: 4(1), P. 219 - 229

Published: April 19, 2024

This paper introduces a conceptual framework that captures both current and future perspectives of data-driven tourism companies by analyzing the data sources utilized in research literature associated topics. To achieve this, bibliometric analysis was conducted. The study encompasses tourism-related publications relied on from 1982 to 2020. findings reveal fundamental performance indicators science mapping, identifying key themes their evolution. Three major thematic areas emerge: topics, information sources, techniques. From these areas, model architecture processes for organizations sector is developed. Additionally, qualitative performed.

Language: Английский

Citations

0
The Impact of Large Language Models on Medical Education: Preparing for a Revolutionary Shift in Doctor Training DOI Creative Commons

Sreeram Mullankandy

Deleted Journal, Journal Year: 2024, Volume and Issue: 4(1), P. 270 - 277

Published: May 22, 2024

Artificial intelligence holds immense potential to transform healthcare, though its widespread implementation has yet be realized. This lag is partly because efforts have traditionally focused on easily predicted rather than actionable problems. Large language models (LLMs) represent a paradigm shift in our approach artificial due their accessibility and the fact that frontline clinicians are already testing them identifying applications. LLMs healthcare could significantly reduce clerical burdens, enhance patient education, more. As we enter this new era of delivery, will bring both opportunities challenges medical education.[1-5] Future should designed help trainees develop clinical reasoning skills, promote evidence-based medicine, provide case-based training opportunities. may also necessitate changes how documentation taught. Additionally, can contribute refining next generation as explore best ways integrate these into education. Whether ready or not, soon integrated various aspects practice. We must collaborate closely with students educators ensure developed mind, guiding education responsibly era.[21]

Language: Английский

Citations

0
Enhancing Machine Learning Performance: The Role of GPU-Based AI Compute Architectures DOI Creative Commons

Bhuvi Chopra

Journal of Knowledge Learning and Science Technology ISSN 2959-6386 (online), Journal Year: 2024, Volume and Issue: 3(3), P. 29 - 42

Published: March 9, 2024

This paper advances the field of GPU-based embedded intelligence (EI) by providing a comprehensive review current and emerging architectures applications. It covers key paradigms in EI, focusing on architecture, technologies, practical The is structured as follows: (1) An overview classification EI research, broad perspective concise summary paper's scope; (2) in-depth discussion various architectural technologies for deep learning techniques applications; (3) A detailed examination machine aims to offer valuable insights into research area, encouraging further development deployment

Language: Английский

Citations

0
Enhancing Machine Learning Performance: The Role of GPU-Based AI Compute Architectures DOI Creative Commons

Bhuvi Chopra

Journal of Knowledge Learning and Science Technology ISSN 2959-6386 (online), Journal Year: 2024, Volume and Issue: 3(3), P. 29 - 42

Published: March 9, 2024

This paper advances the field of GPU-based embedded intelligence (EI) by providing a comprehensive review current and emerging architectures applications. It covers key paradigms in EI, focusing on architecture, technologies, practical The is structured as follows: (1) An overview classification EI research, broad perspective concise summary paper's scope; (2) in-depth discussion various architectural technologies for deep learning techniques applications; (3) A detailed examination machine aims to offer valuable insights into research area, encouraging further development deployment

Language: Английский

Citations

0
Enhancing Machine Learning Performance: The Role of GPU-Based AI Compute Architectures DOI Creative Commons

Bhuvi Chopra

Journal of Knowledge Learning and Science Technology ISSN 2959-6386 (online), Journal Year: 2024, Volume and Issue: 3(3), P. 29 - 42

Published: March 9, 2024

This paper advances the field of GPU-based embedded intelligence (EI) by providing a comprehensive review current and emerging architectures applications. It covers key paradigms in EI, focusing on architecture, technologies, practical The is structured as follows: (1) An overview classification EI research, broad perspective concise summary paper's scope; (2) in-depth discussion various architectural technologies for deep learning techniques applications; (3) A detailed examination machine aims to offer valuable insights into research area, encouraging further development deployment

Language: Английский

Citations

0
DNA Cryptography for Enhanced Data Storage Security in Cloud Environments DOI Creative Commons

Mithun Sarker

Deleted Journal, Journal Year: 2024, Volume and Issue: 4(1), P. 262 - 269

Published: May 22, 2024

Despite the persistent security challenges inherent in cloud systems, a distributed environment necessitates an access control model that is contextually aware to effectively manage these challenges. This should incorporate role activation process based on user's contextual information. Within this process, rationale behind data collection and usage disclosed, enabling administrators establish context-based policies. Consequently, permissions are dynamically activated association of roles with context. To mitigate complications role-based model, users categorized into classes or groups, each its own standards. Access specific resources determined by identity upon request. Traditional models often fall short environments due their inability address all aspects diverse entities, resources, present. In proposed system perception reasoning, entities expanded using Extensible Control Markup Language (XACML), while trust module monitors user behavior dynamically, detecting restricting malicious attempting illegal access. includes assigning tag users, which involves task classification along database tagging.

Language: Английский

Citations

0
Advancing Collective Intelligence in Human–AI Collaboration: Foundations for the COHUMAIN Framework DOI Creative Commons

Sohana Akter

Deleted Journal, Journal Year: 2024, Volume and Issue: 4(1), P. 252 - 261

Published: May 22, 2024

Artificial Intelligence (AI) powered machines are increasingly mediating our work and many of managerial, economic, cultural interactions. While technology enhances individual capabilities in ways, how can we ensure that the sociotechnical system as a whole—comprising complex web hundreds human–machine interactions—is exhibiting collective intelligence? Research on interactions has been conducted within different disciplinary silos, resulting social science models underestimate vice versa. Integrating these diverse perspectives methods is crucial at this juncture. To truly advance understanding important rapidly evolving area, need frameworks to facilitate research bridges boundaries. This paper advocates for establishing an interdisciplinary domain—Collective Human-Machine (COHUMAIN). It outlines agenda holistic approach designing developing dynamics systems. illustrate envision domain, describe recent sociocognitive architecture, transactive systems model intelligence, which articulates critical processes underlying emergence functioning intelligence human–AI collaborations.

Language: Английский

Citations

0