| 1. |
- Feijoo, C., et al.
(författare)
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Harnessing artificial intelligence (AI) to increase wellbeing for all: The case for a new technology diplomacy
- 2020
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Ingår i: Telecommunications Policy. - : Elsevier BV. - 0308-5961. ; 44:6
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Tidskriftsartikel (refereegranskat)abstract
- The field of artificial intelligence (AI) is experiencing a period of intense progress due to the consolidation of several key technological enablers. AI is already deployed widely and has a high impact on work and daily life activities. The continuation of this process will likely contribute to deep economic and social changes. To realise the tremendous benefits of AI while mitigating undesirable effects will require enlightened responses by many stakeholders. Varying national institutional, economic, political, and cultural conditions will influence how AI will affect convenience, efficiency, personalisation, privacy protection, and surveillance of citizens. Many expect that the winners of the AI development race will dominate the coming decades economically and geopolitically, potentially exacerbating tensions between countries. Moreover, nations are under pressure to protect their citizens and their interests—and even their own political stability—in the face of possible malicious or biased uses of AI. On the one hand, these different stressors and emphases in AI development and deployment among nations risk a fragmentation between world regions that threatens technology evolution and collaboration. On the other hand, some level of differentiation will likely enrich the global AI ecosystem in ways that stimulate innovation and introduce competitive checks and balances through the decentralisation of AI development. International cooperation, typically orchestrated by intergovernmental and non-governmental organisations, private sector initiatives, and by academic researchers, has improved common welfare and avoided undesirable outcomes in other technology areas. Because AI will most likely have more fundamental effects on our lives than other recent technologies, stronger forms of cooperation that address broader policy and governance challenges in addition to regulatory and technological issues may be needed. At a time of great challenges among nations, international policy coordination remains a necessary instrument to tackle the ethical, cultural, economic, and political repercussions of AI. We propose to advance the emerging concept of technology diplomacy to facilitate the global alignment of AI policy and governance and create a vibrant AI innovation system. We argue that the prevention of malicious uses of AI and the enhancement of human welfare create strong common interests across jurisdictions that require sustained efforts to develop better, mutually beneficial approaches. We hope that new technology diplomacy will facilitate the dialogues necessary to help all interested parties develop a shared understanding and coordinate efforts to utilise AI for the benefit of humanity, a task whose difficulty should not be underestimated.
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| 2. |
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| 3. |
- Tran, Khanh-Tung, et al.
(författare)
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NeuProNet: neural profiling networks for sound classification
- 2024
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Ingår i: Neural Computing & Applications. - : Springer Nature. - 0941-0643 .- 1433-3058. ; 36:11, s. 5873-5887
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Tidskriftsartikel (refereegranskat)abstract
- Real-world sound signals exhibit various aspects of grouping and profiling behaviors, such as being recorded from identical sources, having similar environmental settings, or encountering related background noises. In this work, we propose novel neural profiling networks (NeuProNet) capable of learning and extracting high-level unique profile representations from sounds. An end-to-end framework is developed so that any backbone architectures can be plugged in and trained, achieving better performance in any downstream sound classification tasks. We introduce an in-batch profile grouping mechanism based on profile awareness and attention pooling to produce reliable and robust features with contrastive learning. Furthermore, extensive experiments are conducted on multiple benchmark datasets and tasks to show that neural computing models under the guidance of our framework gain significant performance gaps across all evaluation tasks. Particularly, the integration of NeuProNet surpasses recent state-of-the-art (SoTA) approaches on UrbanSound8K and VocalSound datasets with statistically significant improvements in benchmarking metrics, up to 5.92% in accuracy compared to the previous SoTA method and up to 20.19% compared to baselines. Our work provides a strong foundation for utilizing neural profiling for machine learning tasks.
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| 4. |
- Tran, Khanh-Tung, et al.
(författare)
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Personalization for robust voice pathology detection in sound waves
- 2023
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Ingår i: Proceedings of the annual conference of the international speech communication association, INTERSPEECH. - : International Speech Communication Association. ; , s. 1708-1712
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Konferensbidrag (refereegranskat)abstract
- Automatic voice pathology detection is promising for noninvasive screening and early intervention using sound signals. Nevertheless, existing methods are susceptible to covariate shifts due to background noises, human voice variations, and data selection biases leading to severe performance degradation in real-world scenarios. Hence, we propose a non-invasive framework that contrastively learns personalization from sound waves as a pre-train and predicts latent-spaced profile features through semi-supervised learning. It allows all subjects from various distributions (e.g., regionality, gender, age) to benefit from personalized predictions for robust voice pathology in a privacy-fulfilled manner. We extensively evaluate the framework on four real-world respiratory illnesses datasets, including Coswara, COUGHVID, ICBHI, and our private dataset - ASound under multiple covariate shift settings (i.e., cross-dataset), improving up to 4.12% in overall performance.
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| 5. |
- Vu, Khuong, et al.
(författare)
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ICT as a driver of economic growth: A survey of the literature and directions for future research
- 2020
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Ingår i: Telecommunications Policy. - : Elsevier BV. - 0308-5961. ; 44:2
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Tidskriftsartikel (refereegranskat)abstract
- This paper conducts a comprehensive literature survey of the papers that examine the link between ICT and economic growth. Using a rigorous screening framework, we found 208 academic papers that were published from 1991 to the cutoff date of October 30, 2018. This survey provides a robust set of insights into the distribution, research strategies, and findings of the surveyed papers, taking into account their geographic focus and type of ICT-growth links. This study also reveals the key factors that predict the citation impact by paper. Among the directions for future research, this paper argues that the time has come for the research on the ICT-growth link to shift its main focus from evidencing its positive relationship to advancing the understanding on why and how emerging digital technologies directly or indirectly affect economic performance.
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