Logic List Mailing Archive

CfR: Virtual Ethical Innovation Lecture Series: May-July: V. Sikimić (Eidhoven)/ M. Gottschling (Tübingen)/ and A. Vučković (Belgrade)

=== Call for Registration
We are excited to invite you to participate in our upcoming Virtual Ethical
 Innovation Lecture Series hosted by the Ethical Innovation Hub of the Univ
ersity of Lbeck, Germany. 

This lecture series will feature a diverse lineup of speakers addressing cr
itical topics at the intersection of ethics and innovation with a particula
r focus on issues of artificial intelligence. 


Registration is Now Open!
Secure your spot by registering at the following link:
https://www.eih.uni-luebeck.de/veilseries
Participation is free

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Event Details:
This series allows for participation in individual lectures, so you can cho
ose the topics most relevant to you. Each session consists of a short talk 
and a pen Q&A session. 

Full abstracts to be found below.

= 2024/05/14 - Vlasta Sikimi (Eindhoven University of Technology), 13:
00 - 13:45 (CEST)   "Is AI to be used in grant review"

= 2024/06/04 Markus Gottschling (Universitt Tbingen), 13:00 - 13:45
 (CEST)  "Persuasive Machines and the Rhetoric of Generative AI"

= 2024/07/09 - Aleksandra Vukovi (University of Belgrade), 13:00 - 
13:45 (CEST)  "Can AI Contribute to Fairness in Education?"

We look forward to your participation in what promises to be an enlightenin
g and thought-provoking series! 

It is aimed at philosophical interested practitioners but open to philosoph
ers and interested public as well. 


Learn More About Us
For more information about our group and our activities, please visit our w
ebsite:
https://www.eih.uni-luebeck.de/

Best regards,
The Ethical Innovation Hub Team

== Full abstracts: 

Title: Is AI to be used in grant review?
By Vlasta Sikimi (Eindhoven University of Technology)
Abstract: The existing peer review system for scientific grants is criticiz
ed for being costly, time-intensive, and unreliable. Could AI be the soluti
on, i.e., could AI be successfully employed in grant review? On the one han
d, AI is a fast and cheap method that can even be trained using the prefere
nces of peer reviewers. On the other hand, transitioning to automated grant
 review poses significant epistemic and ethical hurdles. The epistemic chal
lenges include qualitative assessments of data and making appropriate param
eter selections, while the ethical concerns include the accuracy and transp
arency of automated grant evaluation. We will argue against fully automatin
g the grant review process, highlighting the risk of neglecting important v
alues in science, such as diversity of thoughts and epistemic inclusion.

Title: Persuasive Machines and the Rhetoric of Generative AI By Markus Gott
schling (Universitt Tbingen)
Abstract: The growing influence of generative AI on communication requires 
a nuanced understanding of its impact. While these tools promise to increas
e efficiency and audience engagement, concerns about authenticity and poten
tial misuse persist. As AI co-creates content, questions of authorship, ori
ginality, and ethical boundaries arise. This talk will explore the rhetoric
al strategies employed by AI, the ethical considerations of language models
, and their evolving capacity for understanding and persuasion within the c
ommunications landscape. 


Title: Can AI Contribute to Fairness in Education?
By: Aleksandra Vukovi (University of Belgrade)
Abstract: When we discuss AI implementation in education, we often think ab
out predictive models that indicate the individual's progress in the educat
ional system. On top of that, another type of AI - large language models (L
LMs) - has recently gained attention in the debates on education due to the
 concerns regarding students' potential overreliance on ChatGPT and similar
 software. We analyze these technologies in a somewhat different context an
d reason they could contribute to a more wholesome approach to education or
, more precisely, one that is governed by the principles of equity and incl
usion. If properly introduced, predictive models and LLMs could significant
ly improve the process of gaining knowledge and contribute to fairness in t
eaching and grading. Moreover, personalized curriculums would not only maxi
mize each individual's potential but, as we argue, could also mitigate the 
disbalance between the capitalist center and periphery and broaden overall 
cultural diversity.
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