Autonomous Human-Machine Teams: Knowledge, Information, and Information Gaps in Knowledge

A special issue of Knowledge (ISSN 2673-9585).

Deadline for manuscript submissions: 15 February 2025 | Viewed by 1513

Special Issue Editor


E-Mail Website
Guest Editor
Department of Mathematics and Psychology, Paine College, Augusta, GA 30901, USA
Interests: autonomous human-machine teams and systems (A-HMT-S); artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the past, we have organized Special Issues for AI Magazine (2019);  Frontiers in Physics (2023); and Entropy (ongoing, until August, 2024).  Recently, we were offered an opportunity to organize a new Special Interest proposal for the journal Knowledge, which follows in draft

If you agree to publish one manuscript in Knowledge and collect one other author to submit a manuscript in Knowledge, you will become a co-editor along with me, in the order of confirmation(s).

This Special Issue calls for submissions to Knowledge that address what can be knowable about autonomous human-machine teams. We include propositional knowledge (a declarative assertion that a claim about reality is true); procedural knowledge (an assertion that a claim is true about how best to perform a task in reality; e.g., engineering decisions, applications, data management); and the unknowable knowledge about interactions that is sui generis to teams, especially those affected by interdependence, as occurs in all human-human interactions. We claim that interactions can cause a gap in knowledge to be unknowable (Lawless et al., 2023).

Dr. William Lawless
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Knowledge is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • propositional knowledge
  • procedural knowledge
  • unknowable knowledge (embodied cognition)
  • Shannon information
  • non-decomposable interaction
  • interdependence
  • autonomy

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

27 pages, 475 KiB  
Article
Shannon Holes, Black Holes, and Knowledge: The Essential Tension for Autonomous Human–Machine Teams Facing Uncertainty
by William Lawless and Ira S. Moskowitz
Knowledge 2024, 4(3), 331-357; https://doi.org/10.3390/knowledge4030019 - 5 Jul 2024
Viewed by 1028
Abstract
We develop a new theory of knowledge with mathematics and a broad-based series of case studies to seek a better understanding of what constitutes knowledge in the field and its value for autonomous human–machine teams facing uncertainty in the open. Like humans, as [...] Read more.
We develop a new theory of knowledge with mathematics and a broad-based series of case studies to seek a better understanding of what constitutes knowledge in the field and its value for autonomous human–machine teams facing uncertainty in the open. Like humans, as teammates, artificial intelligence (AI) machines must be able to determine what constitutes the usable knowledge that contributes to a team’s success when facing uncertainty in the field (e.g., testing “knowledge” in the field with debate; identifying new knowledge; using knowledge to innovate), its failure (e.g., troubleshooting; identifying weaknesses; discovering vulnerabilities; exploitation using deception), and feeding the results back to users and society. It matters not whether a debate is public, private, or unexpressed by an individual human or machine agent acting alone; regardless, in this exploration, we speculate that only a transparent process advances the science of autonomous human–machine teams, assists in interpretable machine learning, and allows a free people and their machines to co-evolve. The complexity of the team is taken into consideration in our search for knowledge, which can also be used as an information metric. We conclude that the structure of “knowledge”, once found, is resistant to alternatives (i.e., it is ordered); that its functional utility is generalizable; and that its useful applications are multifaceted (akin to maximum entropy production). Our novel finding is the existence of Shannon holes that are gaps in knowledge, a surprising “discovery” to only find Shannon there first. Full article
Show Figures

Figure 1

Back to TopTop