45,867 research outputs found
Beyond Quantity: Research with Subsymbolic AI
How do artificial neural networks and other forms of artificial intelligence interfere with methods and practices in the sciences? Which interdisciplinary epistemological challenges arise when we think about the use of AI beyond its dependency on big data? Not only the natural sciences, but also the social sciences and the humanities seem to be increasingly affected by current approaches of subsymbolic AI, which master problems of quality (fuzziness, uncertainty) in a hitherto unknown way. But what are the conditions, implications, and effects of these (potential) epistemic transformations and how must research on AI be configured to address them adequately
Challenging the Computational Metaphor: Implications for How We Think
This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor--a sequence of steps--with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think
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Fewer epistemological challenges for connectionism
Seventeen years ago, John McCarthy wrote the note Epistemological challenges for connectionism as a response to Paul Smolensky’s paper 'On the proper treatment of connectionism'. I will discuss the extent to which the four key challenges put forward by McCarthy have been solved, and what are the new challenges ahead. I argue that there are fewer epistemological challenges for connectionism, but progress has been slow. Nevertheless, there is now strong indication that neural-symbolic integration can provide effective systems of expressive reasoning and robust learning due to the recent developments in the field
Modeling Epistemological Principles for Bias Mitigation in AI Systems: An Illustration in Hiring Decisions
Artificial Intelligence (AI) has been used extensively in automatic decision
making in a broad variety of scenarios, ranging from credit ratings for loans
to recommendations of movies. Traditional design guidelines for AI models focus
essentially on accuracy maximization, but recent work has shown that
economically irrational and socially unacceptable scenarios of discrimination
and unfairness are likely to arise unless these issues are explicitly
addressed. This undesirable behavior has several possible sources, such as
biased datasets used for training that may not be detected in black-box models.
After pointing out connections between such bias of AI and the problem of
induction, we focus on Popper's contributions after Hume's, which offer a
logical theory of preferences. An AI model can be preferred over others on
purely rational grounds after one or more attempts at refutation based on
accuracy and fairness. Inspired by such epistemological principles, this paper
proposes a structured approach to mitigate discrimination and unfairness caused
by bias in AI systems. In the proposed computational framework, models are
selected and enhanced after attempts at refutation. To illustrate our
discussion, we focus on hiring decision scenarios where an AI system filters in
which job applicants should go to the interview phase
The Turing Test and the Zombie Argument
In this paper I shall try to put some implications concerning the Turing's test and the so-called
Zombie arguments into the context of philosophy of mind. My intention is not to compose a review
of relevant concepts, but to discuss central problems, which originate from the Turing's test - as a
paradigm of computational theory of mind - with the arguments, which refute sustainability of this
thesis.
In the first section (Section I), I expose the basic computationalist presuppositions; by
examining the premises of the Turing Test (TT) I argue that the TT, as a functionalist paradigm
concept, underlies the computational theory of mind. I treat computationalism as a thesis that
defines the human cognitive system as a physical, symbolic and semantic system, in such a
manner that the description of its physical states is isomorphic with the description of its symbolic
conditions, so that this isomorphism is semantically interpretable. In the second section (Section
II), I discuss the Zombie arguments, and the epistemological-modal problems connected with them,
which refute sustainability of computationalism. The proponents of the Zombie arguments build their
attack on the computationalism on the basis of thought experiments with creatures behaviorally,
functionally and physically indistinguishable from human beings, though these creatures do not
have phenomenal experiences. According to the consequences of these thought experiments - if
zombies are possible, then, the computationalism doesn't offer a satisfying explanation of
consciousness. I compare my thesis from Section 1, with recent versions of Zombie arguments,
which claim that computationalism fails to explain qualitative phenomenal experience. I conclude
that despite the weaknesses of computationalism, which are made obvious by zombie-arguments,
these arguments are not the last word when it comes to explanatory force of computationalism
Information and Design: Book Symposium on Luciano Floridi’s The Logic of Information
Purpose – To review and discuss Luciano Floridi’s 2019 book The Logic of Information: A Theory of Philosophy as Conceptual Design, the latest instalment in his philosophy of information (PI) tetralogy, particularly with respect to its implications for library and information studies (LIS).
Design/methodology/approach – Nine scholars with research interests in philosophy and LIS read and responded to the book, raising critical and heuristic questions in the spirit of scholarly dialogue. Floridi responded to these questions.
Findings – Floridi’s PI, including this latest publication, is of interest to LIS scholars, and much insight can be gained by exploring this connection. It seems also that LIS has the potential to contribute to PI’s further development in some respects.
Research implications – Floridi’s PI work is technical philosophy for which many LIS scholars do not have the training or patience to engage with, yet doing so is rewarding. This suggests a role for translational work between philosophy and LIS.
Originality/value – The book symposium format, not yet seen in LIS, provides forum for sustained, multifaceted and generative dialogue around ideas
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