arXiv:2410.19738v1 Announce Type: new
Abstract: This proceedings contains abstracts and position papers for the work to be presented at the fourth Logic and Practice of Programming (LPOP) Workshop. The workshop is to be held in Dallas, Texas, USA, and as a hybrid event, on October 13, 2024, in conjunction with the 40th International Conference on Logic Programming (ICLP). The focus of this workshop is integrating reasoning systems for trustworthy AI, especially including integrating diverse models of programming with rules and constraints.
The Fourth Logic and Practice of Programming Workshop: Integrating Reasoning Systems for Trustworthy AI
The Logic and Practice of Programming (LPOP) Workshop, set to take place on October 13, 2024, in Dallas, Texas, USA, is an eagerly anticipated event for professionals and researchers in the field of AI. This workshop, being held alongside the 40th International Conference on Logic Programming (ICLP), aims to bring together experts to discuss and explore the integration of reasoning systems for trustworthy AI, with a particular focus on diverse models of programming with rules and constraints.
The multi-disciplinary nature of this workshop is evident in its focus on combining reasoning systems and programming models. As AI technology continues to advance, it is crucial to ensure that these systems are trustworthy and reliable. By integrating diverse models of programming with rules and constraints, researchers aim to develop AI systems that not only make accurate predictions or decisions but also provide explanations and justifications for their actions.
The integration of reasoning systems is a crucial aspect of building trustworthy AI. Reasoning systems play a vital role in AI decision-making processes, enabling machines to process and analyze vast amounts of data, and generate logical conclusions. By combining different models of programming, such as constraint programming or logical programming, researchers can leverage the strengths of each approach to develop AI systems that are more robust and reliable.
One of the key challenges in integrating reasoning systems is the need to ensure consistency and coherency in the decision-making process. Different models of programming may have different assumptions or methodologies, leading to potential conflicts. Researchers at the LPOP Workshop aim to address these challenges by exploring techniques for integrating reasoning systems seamlessly, enabling them to work together to produce accurate and trustworthy AI systems.
Another important aspect of this workshop is the emphasis on trustworthy AI. Trust is a crucial element when it comes to adopting and utilizing AI technology in various domains. Ensuring that AI systems are transparent, explainable, and accountable is essential for building trust. By integrating reasoning systems, researchers can develop AI systems that not only make accurate predictions but also provide explanations for their actions, enabling users to understand and trust the decision-making process.
The significance of this workshop goes beyond just the AI field. The integration of reasoning systems for trustworthy AI has implications for various disciplines, including ethics, law, and policy. As AI becomes more prevalent in society, there is a growing need to address ethical and legal concerns, such as bias, fairness, and privacy. By fostering discussion and collaboration among experts from different disciplines, the LPOP Workshop aims to pave the way for the development of AI systems that are not only technically robust but also ethically and legally sound.
In conclusion, the fourth Logic and Practice of Programming Workshop is an exciting event that brings together experts from various disciplines to discuss the integration of reasoning systems for trustworthy AI. By combining diverse programming models with rules and constraints, researchers aim to develop AI systems that are more reliable, transparent, and accountable. This workshop’s multi-disciplinary nature highlights the broad impact and importance of this research, extending beyond just AI to ethics, law, and policy.