The ethics of using artificial intelligence in scientific research: new guidance needed for a new tool

AI and Ethics, Год журнала: 2024, Номер unknown

Опубликована: Май 27, 2024

Using artificial intelligence (AI) in research offers many important benefits for science and society but also creates novel complex ethical issues. While these issues do not necessitate changing established norms of science, they require the scientific community to develop new guidance appropriate use AI. In this article, we briefly introduce AI explain how it can be used research, examine some raised when using it, offer nine recommendations responsible use, including: (1) Researchers are identifying, describing, reducing, controlling AI-related biases random errors; (2) should disclose, describe, their including its limitations, language that understood by non-experts; (3) engage with impacted communities, populations, other stakeholders concerning obtain advice assistance address interests concerns, such as related bias; (4) who synthetic data (a) indicate which parts synthetic; (b) clearly label data; (c) describe were generated; (d) why used; (5) systems named authors, inventors, or copyright holders contributions disclosed described; (6) Education mentoring conduct include discussion

Язык: Английский

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AI in analytical chemistry: Advancements, challenges, and future directions

Talanta, Год журнала: 2024, Номер 274, С. 125949 - 125949

Опубликована: Март 19, 2024

Язык: Английский

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Advanced Computational Methods for Modeling, Prediction and Optimization—A Review

Materials, Год журнала: 2024, Номер 17(14), С. 3521 - 3521

Опубликована: Июль 16, 2024

This paper provides a comprehensive review of recent advancements in computational methods for modeling, simulation, and optimization complex systems materials engineering, mechanical energy systems. We identified key trends highlighted the integration artificial intelligence (AI) with traditional methods. Some cited works were previously published within topic: "Computational Methods: Modeling, Simulations, Optimization Complex Systems"; thus, this article compiles latest reports from field. The work presents various contemporary applications advanced algorithms, including AI It also introduces proposals novel strategies production domain. is essential to optimize properties used energy. Our findings demonstrate significant improvements accuracy efficiency, offering valuable insights researchers practitioners. contributes field by synthesizing state-of-the-art developments suggesting directions future research, underscoring critical role these advancing engineering technological solutions.

Язык: Английский

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Machine intelligence in metamaterials design: a review

Oxford Open Materials Science, Год журнала: 2024, Номер 4(1)

Опубликована: Янв. 1, 2024

Abstract Machine intelligence continues to rise in popularity as an aid the design and discovery of novel metamaterials. The properties metamaterials are essentially controllable via their architectures until recently, process has relied on a combination trial-and-error physics-based methods for optimization. These processes can be time-consuming challenging, especially if space metamaterial optimization is explored thoroughly. Artificial (AI) machine learning (ML) used overcome challenges like these pre-processed massive datasets very accurately train appropriate models. models broad, describing properties, structure, function at numerous levels hierarchy, using relevant inputted knowledge. Here, we present comprehensive review literature where state-of-the-art design, development In this review, individual approaches categorized based methodology application. We further trends over wide range problems including: acoustics, photonics, plasmonics, mechanics, more. Finally, identify discuss recent research directions highlight current gaps

Язык: Английский

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AI-Based Metamaterial Design

ACS Applied Materials & Interfaces, Год журнала: 2024, Номер 16(23), С. 29547 - 29569

Опубликована: Май 29, 2024

The use of metamaterials in various devices has revolutionized applications optics, healthcare, acoustics, and power systems. Advancements these fields demand novel or superior that can demonstrate targeted control electromagnetic, mechanical, thermal properties matter. Traditional design systems methods often require manual manipulations which is time-consuming resource intensive. integration artificial intelligence (AI) optimizing metamaterial be employed to explore variant disciplines address bottlenecks design. AI-based also enable the development by parameters cannot achieved using traditional methods. application AI leveraged accelerate analysis vast data sets as well better utilize limited via generative models. This review covers transformative impact for current challenges, emerging fields, future directions, within each domain are discussed.

Язык: Английский

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Unveiling physical properties of LaMnSb and LuMnSb half-Heusler compounds for green energy applications: A DFT exploration

Journal of Rare Earths, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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Design thinking and artificial intelligence: A systematic literature review exploring synergies

International Journal of Innovation Studies, Год журнала: 2024, Номер 8(3), С. 297 - 312

Опубликована: Май 24, 2024

This article examines how design thinking and artificial intelligence (AI) work together what it means for the sector. The goal is to understand AI technologies may advance process, encourage innovation, produce more individualized user-centric solutions. study intends shed light on potential of as a catalyst creativity ethical implications AI-driven by discovering overlapping ideas methodologies between AI. According research, can significantly influence process eliminating tedious processes, improving user-centricity, stimulating creativity. support designers' decision-making, prototyping, ideation resulting in creative effective Addressing bias algorithms data privacy imperative ensure integration. Virtual reality, bio-design, inclusive are untapped areas where be used.

Язык: Английский

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Advancing PFAS Remediation through Physics-Based Modeling of 2D Materials: Recent Progress, Challenges, and Opportunities

Industrial & Engineering Chemistry Research, Год журнала: 2025, Номер unknown

Опубликована: Янв. 15, 2025

In recent years, the discovery and optimization of two-dimensional (2D) materials for environmental applications have garnered significant attention, particularly in treatment per- polyfluoroalkyl substances (PFAS). PFAS, known their strong carbon–fluorine bonds persistence environment, present a critical challenge due to resistance degradation harmful health effects. Traditional methods PFAS remediation are often resource-intensive inefficient. this study, we propose leveraging physics-based machine learning (PBM) models accelerate 2D treatment, through adsorption electrochemical degradation. The integration fundamental physical laws with an inverse PBM (IPBM) framework enables faster, more cost-effective predictions material properties tailored remediation. We highlight advancements materials, such as graphene, MXenes, boron nitride, potential This approach promises provide scalable, high-performance solutions address global contamination crisis, offering path forward developing advanced sustainable water technologies.

Язык: Английский

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Recent Advances in the Development of Biomimetic Materials

Gels, Год журнала: 2023, Номер 9(10), С. 833 - 833

Опубликована: Окт. 20, 2023

In this review, we focused on recent efforts in the design and development of materials with biomimetic properties. Innovative methods promise to emulate cell microenvironments tissue functions, but many aspects regarding cellular communication, motility, responsiveness remain be explained. We photographed state-of-the-art advancements biomimetics, discussed complexity a “bottom-up” artificial construction living systems, particular highlights hydrogels, collagen-based composites, surface modifications, three-dimensional (3D) bioprinting applications. Fast-paced 3D printing intelligence, nevertheless, collide reality: How difficult can it build reproducible at real scale line systems? Nowadays, science is urgent need bioengineering technologies for practical use bioinspired biomimetics medicine clinics.

Язык: Английский

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AI and machine learning in climate change research: A review of predictive models and environmental impact

World Journal of Advanced Research and Reviews, Год журнала: 2024, Номер 21(1), С. 1999 - 2008

Опубликована: Янв. 25, 2024

The burgeoning threat of climate change has spurred an increased reliance on advanced technologies to comprehend and mitigate its far-reaching consequences. Artificial Intelligence (AI) Machine Learning (ML) have emerged as indispensable tools in research, offering unprecedented capabilities for predictive modeling assessing environmental impact. This review synthesizes the current state AI ML applications emphasizing their role understanding repercussions. Predictive models leveraging algorithms demonstrated remarkable efficacy forecasting patterns, extreme weather events, sea-level rise. These incorporate vast datasets encompassing meteorological, geospatial, oceanic information, enabling more accurate predictions future scenarios. Moreover, AI-driven excel recognizing intricate patterns non-linear relationships within data, enhancing capacity simulate complex systems. Environmental impact assessment stands a critical facet techniques are proving instrumental this regard. facilitate analysis diverse ecological parameters, including deforestation rates, biodiversity loss, carbon sequestration dynamics. By discerning nuanced immense datasets, systems contribute direct indirect consequences ecosystems. Despite these advancements, challenges persist, such need standardized data formats, model interpretability, ethical considerations. Additionally, integration findings into policy frameworks remains crucial frontier. As intersection AI, ML, research evolves, continuous interdisciplinary collaboration is essential harness full potential safeguarding our planet's future. illuminates landscape applications, providing insights efficacy, challenges, contributions advancing sustainability.

Язык: Английский

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