1,720,962 research outputs found
Balancing Access and Accountability: Ethical Challenges in Open-Source AI Deployment
No full textThe release of ChatGPT by OpenAI started a significant shift in information retrieval, by providing
public access to a state-of-the-art Large Language Model (LLM). Since the release of ChatGPT,
the open-source community has significantly improved the quality of their models, making this
advanced technology accessible to anyone. With this accessibility of open-source models, certain
ethical questions arise, like: how does the trade-off between accessibility and accountability in
open-source AI models impact potential misuse and safety? This thesis answers this question and
gives recommendations on how to mitigate these risks in the short term while urging for subsequent
research into this topic. It does so by exploring the potential risks and misuse of LLMs, such as
the creation of misinformation, personalized scams, extremist and discriminatory texts and the
potential threat to cybersecurity. After analysing current technological safety measures and the
limitations of these open-source models it is evident that there is no technical solution that can
keep these models accessible to anyone while also guaranteeing safe deployment. Instead, more
focus should be on solutions around the deployment of these models to enhance safety. This thesis
suggests the implementation of a Certified Access System, usage monitoring, laws or regulations
which ensures that only models with adequate safety measures may be shared, and ethical training
for users. Other findings are that balancing accessibility and accountability is crucial for the safe
deployment of accessible open-source models, and that ethics must guide the design of AI to make
truly safe systems. This work contributes to the understanding of the ethical landscape of open source AI models and provides recommendations for further research to mitigate risks associated
with open-source AI systems
Balancing Access and Accountability: Ethical Challenges in Open-Source AI Deployment
No full textThe release of ChatGPT by OpenAI started a significant shift in information retrieval, by providing
public access to a state-of-the-art Large Language Model (LLM). Since the release of ChatGPT,
the open-source community has significantly improved the quality of their models, making this
advanced technology accessible to anyone. With this accessibility of open-source models, certain
ethical questions arise, like: how does the trade-off between accessibility and accountability in
open-source AI models impact potential misuse and safety? This thesis answers this question and
gives recommendations on how to mitigate these risks in the short term while urging for subsequent
research into this topic. It does so by exploring the potential risks and misuse of LLMs, such as
the creation of misinformation, personalized scams, extremist and discriminatory texts and the
potential threat to cybersecurity. After analysing current technological safety measures and the
limitations of these open-source models it is evident that there is no technical solution that can
keep these models accessible to anyone while also guaranteeing safe deployment. Instead, more
focus should be on solutions around the deployment of these models to enhance safety. This thesis
suggests the implementation of a Certified Access System, usage monitoring, laws or regulations
which ensures that only models with adequate safety measures may be shared, and ethical training
for users. Other findings are that balancing accessibility and accountability is crucial for the safe
deployment of accessible open-source models, and that ethics must guide the design of AI to make
truly safe systems. This work contributes to the understanding of the ethical landscape of open source AI models and provides recommendations for further research to mitigate risks associated
with open-source AI systems
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Designing the robot that says "NO": Design and ethical implications of love and sex relations with robots
No full textThe possibility of love and sex relations between humans and robots
has been put on the scientific map by David Levy. In his doctoral dissertation
Intimate relationships with artificial partners (2007a), he defended
the thesis that such relationships will necessarily happen and will
improve the lives of the humans involved. Technical developments on
emotion and personality simulation and current societal discussions
about the use of sex robots call for, respectively, an updated look at
the design implications for such robots and for a virtue-ethical critique
of Levy’s argument. I develop both in this thesis and do so in
three steps. First, I will critically analyze Levy’s argument and use insights
from the field of philosophy of technology to argue that Levy’s
instrumental view of robots does not correctly capture human–robot
interaction. Second, I will connect Levy’s predictions to current developments
in artificial intelligence and robotics. This step will answer
what the current and near-future possibilities and limitations with
respect to our ability to create androids are. Third, I give an ethical
analysis of Levy’s view on human–robot interaction, based on the
critique I developed in the first part and the updated view on robotics
from the second part. For this analysis I use virtue ethics, which
is specifically suited to pragmatic, situated interactions between humans
and robots. To illustrate how such an ethical analysis helps us
to better understand intimate relations between robots and humans,
I present a potential case study.
ii
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Moreel zorgen of morele zorgen? Kunstmatige intelligentie, phronesis, en de uitholling van de zorgtaak
No full textContains fulltext :
322667.pdf (Publisher’s version ) (Closed access)
Contains fulltext :
322667.pdf (Author’s version preprint ) (Open Access)5 p
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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