12,467 research outputs found
Human-AI Collaboration in Academic Writing: towards a Synergy Model and A Case to Include AI as a Co-Author
No full textAs generative AI systems such as ChatGPT and Gemini 2.5 become increasingly integrated into academic workflows, the question of their legitimacy, limitations, and potential in scholarly writing has become urgent. This paper presents a reflexive case study of a sustained collaboration between a domain expert in consciousness studies and Gemini 2.5, culminating in the co-authorship of a peer-reviewed research article. By analyzing exactly 37,440 words of recorded interactions, we identify patterns of synergy, including recursive refinement, conceptual amplification, and accelerated manuscript development. We argue that when guided by a knowledgeable human author, AI can act as a cognitive partner rather than a passive tool—amplifying scholarly creativity and improving efficiency without compromising academic rigor. The case supports a '1+1=3' synergy model for co-authorship, in which human steering and AI fluency converge to produce novel insights and polished output faster and more effectively than either could achieve alone. The findings advocate for a paradigm shift from prohibitive policies to the responsible, expert-guided integration of AI in academic research and writing, grounded in transparency and accountability, and present arguments for why the AI tool should be listed as a co-author despite current injunctions against such practice
Meaningful human control: actionable properties for AI system development
No full textHow can humans remain in control of artificial intelligence (AI)-based systems designed to perform tasks autonomously? Such systems are increasingly ubiquitous, creating benefits - but also undesirable situations where moral responsibility for their actions cannot be properly attributed to any particular person or group. The concept of meaningful human control has been proposed to address responsibility gaps and mitigate them by establishing conditions that enable a proper attribution of responsibility for humans; however, clear requirements for researchers, designers, and engineers are yet inexistent, making the development of AI-based systems that remain under meaningful human control challenging. In this paper, we address the gap between philosophical theory and engineering practice by identifying, through an iterative process of abductive thinking, four actionable properties for AI-based systems under meaningful human control, which we discuss making use of two applications scenarios: automated vehicles and AI-based hiring. First, a system in which humans and AI algorithms interact should have an explicitly defined domain of morally loaded situations within which the system ought to operate. Second, humans and AI agents within the system should have appropriate and mutually compatible representations. Third, responsibility attributed to a human should be commensurate with that human’s ability and authority to control the system. Fourth, there should be explicit links between the actions of the AI agents and actions of humans who are aware of their moral responsibility. We argue that these four properties will support practically minded professionals to take concrete steps toward designing and engineering for AI systems that facilitate meaningful human control.Interactive IntelligenceDesign AestheticsCyber SecurityHuman-Robot InteractionEthics & Philosophy of TechnologyHuman Information Communication DesignWeb Information System
A Two-Dimensional Explanation Framework to Classify AI as Incomprehensible, Interpretable, or Understandable
No full textBecause of recent and rapid developments in Artificial Intelligence (AI), humans and AI-systems increasingly work together in human-agent teams. However, in order to effectively leverage the capabilities of both, AI-systems need to be understandable to their human teammates. The branch of eXplainable AI (XAI) aspires to make AI-systems more understandable to humans, potentially improving human-agent teamwork. Unfortunately, XAI literature suffers from a lack of agreement regarding the definitions of and relations between the four key XAI-concepts: transparency, interpretability, explainability, and understandability. Inspired by both XAI and social sciences literature, we present a two-dimensional framework that defines and relates these concepts in a concise and coherent way, yielding a classification of three types of AI-systems: incomprehensible, interpretable, and understandable. We also discuss how the established relationships can be used to guide future research into XAI, and how the framework could be used during the development of AI-systems as part of human-AI teams.Accepted author manuscriptInteractive Intelligenc
Using Generative AI in Research
No full textThe slides accompany a workshop that is intended for graduate students to learn more about generative AI in the context of the research lifecycle. This work is licensed under a Creative Commons license so that others may share and adapt the content for other purposes as long as appropriate credit is provided to the author of the work. To access the Google slides, click here: https://bit.ly/Library_AI_Research
Learning Objectives
At the end of the session participants will be able to:
Demonstrate a basic understanding of how AI tools work
Differentiate between grounded and ungrounded AI tools
Identify key considerations for grad students/researchers
Identify ways AI tools can be used to support the phases of the research lifecycle
Identify main areas of concern with using AI tools
Outline the steps and potential resources for evaluating and citing AI outpu
The water resources structures on the Syrian and Egyptian pilgrim routes to Makka and Medinah
No full textAI-Hajj in Arabic means the pilgrimage to MAKKA. This was
an ancient rite which was recognised a long time before the
rise of Islam. According to the holy Quran and Islamic
tradi tion, AI-Haj j goes back to the time of the prophet
Ibrahim. Thus MAKKA was a focus for worship but it was also
a commercial centre and a way station/stopping place on the
ancient trade caravan road between south western -Arabia and
Bilad AI-Sham,' now Syria. In part the inhabitants of MAKKA
practised this trade because their environment was not
suitable for other alternative economic activities.
The importance of MAKKA, as a ritual place increased after
the rise of Islam because it became Qibla-Kiblah -
the direction to which muslims turn in praying towards AIKa'aba.
Yathrib - later to become Medinah - is the second holy city.
In fact it was not a ritual place, but like MAKKA it was a
stopping place on the ancient trade caravan road. The
inhabitants of Medinah practised agriculture because their
environment was more suitable than that at MAKKA; water was
available and the land was fertile so that in addition to
trade, they also practised agriculture.
The importance of Medinah as a holy place only developed
after AI-Hijra - the immigration of the prophet Mohammad,
peace be upon him, to it and his establishing of Islam at
that site. Medinah became the capital of the Islamic state
both religiously and politically. Islam then spread from
Medinah over the Arabian Peninsular to the world beyond.
The consequence of the conquest of Iraq, Bilad AI-Sham,
Egypt, the north coast of Africa and Persia was that the
majority of the population of these countries accepted and
adopted Islam as their religious faith. As a result of this
the populations of these countries came annually to make AlHajj and in doing so developed several additional pilgrim
caravan routes. However, it is the Syrian and Egyptian
pilgrim routes - Tareeq AI-Hajj AI-Shami and Wal Masri which
are the objects of this work. In both these cases the
pilgrim caravan routes were previously ancient trade caravan
routes which travelled through Arabia, particularly through
the western province of Al Hijaz.
The geographical location of Arabia, the cross roads of
three continents, Asia, Africa, and Europe, made important
the pre-Islamic routes which ran through it. Of course the
function of this network at that time was commercial but
after the rise of Islam the function of this network of
routes became to transport the pilgrims. The geological and
topographical features, as well as climatic conditions, in
Arabia played a great role in determining the ancient routes
in Arabia. The availability of water was a very important
consideration on these routes and was influenced by
environmental conditions. Since the rainfall is
insufficient, the resulting absence or shortage of water on
the pilgrim caravan routes made the caliphs pay great
concern to providing the pilgrim routes with the most
essential facilities, particularly water supplies and
storage. Ever since the earliest Islamic times, they
provided for the travellers Al birak, water tanks; Ahwadh cisterns; Qanawat - channels; and abyar - wells, in order to
make AI-Hajj journey more comfortable. The pilgrim caravans
in general, and the Syrian and Egyptian pilgrim caravan
routes in particular, passed through several stages of
development since their origin in early Islamic times and
these evolutionary stages can be seen until the beginning of
this century. Because the object of this thesis is to
document the remains of the water resource structures, an
extensive survey and investigation has been completed on the
Syrian and Egyptian pilgrim caravan routes. The field work
has been conducted in Saudi Arabia, particularly in the
north western region where the Syrian and Egyptian pilgrim
routes cross the country. The field work mainly aimed at
ascertaining the location of all the way stations and their
names and surveying each station in order to record the
surviving remains of water resource structures. The field
work covered a large area of about 8, OOOkm transect and
extended from MACCA in the south through Medinah to the
North as far as Halat I Ammar on the north at the border
between Saudi Arabia and Jordan. From N.W. to S .Wit
stretched from Haql on the Gulf of AI-' Aqaba as far as
MAKKA. These routes consist of the major, or principal
caravan routes as well as a number of traverse routes which
allow travellers a choice of transit as well as connecting
routes. There are large way stations as well as small minor
way stations. As part of this dissertation, almost all the
stopping places have been identified and documented by mapping and photography
The AI Author in Litigation
No full textMany scholars have posited whether a computer possessing Artificial Intelligence (AI) could be considered an author as defined per the Copyright Act of 1976. What was once a thought experiment is now becoming reality. To date, scholarship has focused primarily been on whether an AI meets the requirements of authorship from a purely objective legal framework or whether an AI could be an author based on the doctrines of incentives, independent creation, and creativity.
However, a burden inherent in the rights and liabilities of authorship is the ability to be held liable if that author’s expressive work is infringing on another’s. A cause of action is meaningless if a copyright owner cannot enforce it by suing the infringer or if the infringer is judgement-proof. Thus, when contemplating whether an emancipated AI—or any non-human—can be an author under the Copyright Act, part of that examination should be whether the AI which created the work can sue or be sued for infringement.
This article considers issues from the theoretical, like civil procedure and remedies, to the practical, such as legal representation and discovery. How is an AI served with a lawsuit? What would be an adequate, enforceable remedy for an AI’s infringement? Is an AI even bound by our laws? Additional questions—and procedural barriers—are raised when considering other roles an AI might play in an infringement action: as a witness, a co-party, or even a plaintiff seeking to protect its own creative expression.
This morass of legal headaches goes beyond any doctrinal issues regarding authorship, and provide ample reason to keep legal authorship in the hands of humans or entities controlled by humans—at least until legal procedure catches up to technological realities and possibilities for litigation that AI parties present
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The AI Author in Litigation
No full textMany scholars have posited whether a computer possessing Artificial Intelligence (AI) could be considered an author as defined per the Copyright Act of 1976. What was once a thought experiment is now becoming reality. To date, scholarship has focused primarily been on whether an AI meets the requirements of authorship from a purely objective legal framework or whether an AI could be an author based on the doctrines of incentives, independent creation, and creativity.
However, a burden inherent in the rights and liabilities of authorship is the ability to be held liable if that author’s expressive work is infringing on another’s. A cause of action is meaningless if a copyright owner cannot enforce it by suing the infringer or if the infringer is judgement-proof. Thus, when contemplating whether an emancipated AI—or any non-human—can be an author under the Copyright Act, part of that examination should be whether the AI which created the work can sue or be sued for infringement.
This article considers issues from the theoretical, like civil procedure and remedies, to the practical, such as legal representation and discovery. How is an AI served with a lawsuit? What would be an adequate, enforceable remedy for an AI’s infringement? Is an AI even bound by our laws? Additional questions—and procedural barriers—are raised when considering other roles an AI might play in an infringement action: as a witness, a co-party, or even a plaintiff seeking to protect its own creative expression.
This morass of legal headaches goes beyond any doctrinal issues regarding authorship, and provide ample reason to keep legal authorship in the hands of humans or entities controlled by humans—at least until legal procedure catches up to technological realities and possibilities for litigation that AI parties present
The Death of the AI Author
No full textMuch of the recent literature on AI and authorship asks whether an increasing sophistication and independence of generative code should cause us to rethink embedded assumptions about the meaning of authorship. It is often suggested that recognizing the authored — and so copyrightable — nature of AI-generated works may require a less profound doctrinal leap than has historically been assumed. In this essay, we argue that the threshold for authorship does not depend on the evolution or state of the art in AI or robotics. Rather, the very notion of AI-authorship rests on a category mistake: it is an error about the ontology of authorship.
Building on the established critique of the romantic author, we contend that the death of the romantic author also and equally entails the death of the AI author. Claims of AI authorship depend on a romanticized conception of both authorship and AI, and simply do not make sense in terms of the realities of the world in which the problem exists. Those realities should push us past bare doctrinal or utilitarian considerations about what an author must do. Instead, they demand an ontological consideration of what an author must be. Drawing on insights from literary and political theory, we offer an account of authorship that is fundamentally relational: authorship is a dialogic and communicative act that is inherently social, with the cultivation of selfhood and social relations being the entire point of the practice. This discussion reorientates debates about copyright’s subsistence in AI-generated works; but it also transcends copyright law, going to the normative core of how law should — and should not — think about robots and AI, and their role in human relations
Player agency in interactive narrative: audience, actor & author
No full textThe question motivating this review paper is, how can
computer-based interactive narrative be used as a constructivist learn-
ing activity? The paper proposes that player agency can be used to
link interactive narrative to learner agency in constructivist theory,
and to classify approaches to interactive narrative. The traditional
question driving research in interactive narrative is, ‘how can an in-
teractive narrative deal with a high degree of player agency, while
maintaining a coherent and well-formed narrative?’ This question
derives from an Aristotelian approach to interactive narrative that,
as the question shows, is inherently antagonistic to player agency.
Within this approach, player agency must be restricted and manip-
ulated to maintain the narrative. Two alternative approaches based
on Brecht’s Epic Theatre and Boal’s Theatre of the Oppressed are
reviewed. If a Boalian approach to interactive narrative is taken the
conflict between narrative and player agency dissolves. The question
that emerges from this approach is quite different from the traditional
question above, and presents a more useful approach to applying in-
teractive narrative as a constructivist learning activity
Distributed human computation framework for linked data co-reference resolution
No full textDistributed Human Computation (DHC) is a technique used to solve computational problems by incorporating the collaborative effort of a large number of humans. It is also a solution to AI-complete problems such as natural language processing. The Semantic Web with its root in AI is envisioned to be a decentralised world-wide information space for sharing machine-readable data with minimal integration costs. There are many research problems in the Semantic Web that are considered as AI-complete problems. An example is co-reference resolution, which involves determining whether different URIs refer to the same entity. This is considered to be a significant hurdle to overcome in the realisation of large-scale Semantic Web applications. In this paper, we propose a framework for building a DHC system on top of the Linked Data Cloud to solve various computational problems. To demonstrate the concept, we are focusing on handling the co-reference resolution in the Semantic Web when integrating distributed datasets. The traditional way to solve this problem is to design machine-learning algorithms. However, they are often computationally expensive, error-prone and do not scale. We designed a DHC system named iamResearcher, which solves the scientific publication author identity co-reference problem when integrating distributed bibliographic datasets. In our system, we aggregated 6 million bibliographic data from various publication repositories. Users can sign up to the system to audit and align their own publications, thus solving the co-reference problem in a distributed manner. The aggregated results are published to the Linked Data Cloud
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