arXiv subjects

Eamonn O'Neill

Publications and source records attributed to Eamonn O'Neill.

5 recordsLinked to original sources

arXiv2024

Regulating AI: Applying insights from behavioural economics and psychology to the application of article 5 of the EU AI Act

Article 5 of the European Union's Artificial Intelligence Act is intended to regulate AI use to prevent potentially harmful consequences. Nevertheless, applying this legislation practically is likely to be challenging because of ambiguously used terminologies and because it fails to specify which manipulation techniques may be invoked by AI, potentially leading to significant harm. This paper aims to bridge this gap by defining key terms and demonstrating how AI may invoke these techniques, drawing from insights in psychology and behavioural economics. First, this paper provides definitions of the terms "subliminal techniques", "manipulative techniques" and "deceptive techniques". Secondly, we identified from the literature in cognitive psychology and behavioural economics three subliminal and five manipulative techniques and exemplify how AI might implement these techniques to manipulate users in real-world case scenarios. These illustrations may serve as a practical guide for stakeholders to detect cases of AI manipulation and consequently devise preventive measures. Article 5 has also been criticised for offering inadequate protection. We critically assess the protection offered by Article 5, proposing specific revisions to paragraph 1, points (a) and (b) of Article 5 to increase its protective effectiveness.

cs.CY↗

arXiv2023

Performance of data-driven inner speech decoding with same-task EEG-fMRI data fusion and bimodal models

Decoding inner speech from the brain signal via hybridisation of fMRI and EEG data is explored to investigate the performance benefits over unimodal models. Two different bimodal fusion approaches are examined: concatenation of probability vectors output from unimodal fMRI and EEG machine learning models, and data fusion with feature engineering. Same task inner speech data are recorded from four participants, and different processing strategies are compared and contrasted to previously-employed hybridisation methods. Data across participants are discovered to encode different underlying structures, which results in varying decoding performances between subject-dependent fusion models. Decoding performance is demonstrated as improved when pursuing bimodal fMRI-EEG fusion strategies, if the data show underlying structure.

cs.LG↗

arXiv2016

Towards the Design of Effective Freehand Gestural Interaction for Interactive TV

As interactive devices become pervasive, people are beginning to looking for more advanced interaction with televisions in the living room. Interactive television has the potential to offer a very engaging experience. But most common user tasks are still challenging with such systems, such as menu selection or text input. And little work has been done on understanding and sup-porting the effective design of freehand interaction with an TV in the living room. In this paper, we perform two studies investi-gating freehand gestural interaction with a consumer level sensor, which is suitable for TV scenarios. In the first study, we inves-tigate a range of design factors for tiled layout menu selection, including wearable feedback, push gesture depth, target size and position in motor space. The results show that tactile and audio feedback have no significant effect on performance and prefer-ence, and these results inform potential designs for high selection performance. In the second study, we investigate a common TV user task of text input using freehand gesture. We design and evaluate two virtual keyboard layouts and three freehand selec-tion methods. Results show that ease of use and error tolerance can be both achieved using a text entry method utilizing a dual circle layout and an expanding target selection technique. Finally, we propose design guidelines for effective, usable and com-fortable freehand gestural interaction for interactive TV based on the findings.

cs.HC↗

arXiv2008

Size matters: performance declines if your pixels are too big or too small

We present a conceptual model that describes the effect of pixel size on target acquisition. We demonstrate the use of our conceptual model by applying it to predict and explain the results of an experiment to evaluate users' performance in a target acquisition task involving three distinct display sizes: standard desktop, small and large displays. The results indicate that users are fastest on standard desktop displays, undershoots are the most common error on small displays and overshoots are the most common error on large displays. We propose heuristics to maintain usability when changing displays. Finally, we contribute to the growing body of evidence that amplitude does affect performance in a display-based pointing task.

cs.GR↗

arXiv2007

Brief encounter networks

Many complex human and natural phenomena can usefully be represented as networks describing the relationships between individuals. While these relationships are typically intermittent, previous research has used network representations that aggregate the relationships at discrete intervals. However, such an aggregation discards important temporal information, thus inhibiting our understanding of the networks dynamic behaviour and evolution. We have recorded patterns of human urban encounter using Bluetooth technology thus retaining the temporal properties of this network. Here we show how this temporal information influences the structural properties of the network. We show that the temporal properties of human urban encounter are scale-free, leading to an overwhelming proportion of brief encounters between individuals. While previous research has shown preferential attachment to result in scale-free connectivity in aggregated network data, we found that scale-free connectivity results from the temporal properties of the network. In addition, we show that brief encounters act as weak social ties in the diffusion of non-expiring information, yet persistent encounters provide the means for sustaining time-expiring information through a network.

cs.CY↗