Now open for submissions, Nature Machine Intelligence will study all aspects of intelligent machines by exploring a broad spectrum of topics across artificial Intelligence and robotics, as well as their connections with other fields. We will publish original research, Reviews, Perspectives, Comments, News Features, and News & Views articles.
This guest blog comes from Liesbeth Venema, Chief Editor and Trenton Jerde, Senior Editor at Nature Machine Intelligence
For several decades, research in artificial intelligence and, in parallel, in robotics has been making steady progress. But recently, the pace of developments has accelerated due to well-known factors such as the availability of computing processing power, widespread use of the internet, mobile devices, low-cost sensors and cameras, and the resulting proliferation of big data. Indeed, we regularly hear how artificial intelligence will reinvigorate various technologies, transform society, help address longstanding research questions and – on the flipside – how it poses short- and long-term risks for humanity.
Several years of fast-paced advances in deep learning applications have given us speech recognition, language translation, and image classification applications with close to or surpassing human ability. Current research aims to develop AI systems with wider applicability that will safely interact with humans and the physical world. Different concepts and approaches – machine learning, symbolic reasoning, cognitive science, developmental psychology, robot control engineering, human-machine interactions among others – are increasingly brought together for such goals. Furthermore, scientists from all fields are exploring how emerging concepts from AI can be used to process large amounts of data and transform their disciplines.
Launching in January 2019
By launching Nature Machine Intelligence, we will provide the research community with a forum for these themes and explore a broad spectrum of topics that connect various scientific disciplines with Machine Intelligence, and cover the implications of recent advances for science, society and industry.
We welcome submissions from all fields, including computer science and robotics, but also, for example, from biology, medical sciences, physical sciences, cognitive sciences, and social sciences, since intelligent machines have become important for most disciplines. We are especially interested in topics at the intersection between different fields and will cover diverse perspectives to scientific questions by bringing together authors from different areas. Topics of interest include, but are not limited to, engineering of AI systems and robots, human-machine interactions, fundamental research on natural and artificial intelligence, integration of AI approaches in physics and biology, and AI algorithms in society.
We have a dedicated team of in-house manuscript editors, production editors and editorial assistants in place. Our editors will engage with research communities in academia and industry to provide exceptional author and reviewer service. The journal will uphold high reproducibility standards and high-quality editorial and publishing policies.
Nature Machine Intelligence will commission Comments, Reviews, News & Views articles, and news features to put specific research in a wider context, provide background and perspective, and make scientific discoveries accessible beyond experts. The journal will also discuss community, policy and ethical issues in artificial intelligence and adjacent fields. Nature Research’s experienced press team will ensure that research is responsibly and accurately communicated to the media, helping to share authors’ research with the widest possible audience.
Nature Machine Intelligence is a subscription-based journal, and using this model for a journal in the space of artificial intelligence has generated discussion in the research community in recent months. We believe that the most viable way to produce a journal that reaches out to a wide, interdisciplinary audience, enabled by the editorial investment discussed above, is to spread the costs across many readers.
Editorial and publishing policies
Our intention is for Nature Machine Intelligence to be an informative and stimulating resource for scientists from many fields as well as for anyone who has a professional or personal curiosity about what is possible – and what is not – in artificial intelligence and robotics.
- Importantly, authors remain owners of the content of their research papers and we encourage preprint posting such as via arXiv or bioArxiv (for full policy, see here).
- Like all Nature-branded journals, Nature Machine Intelligence enables the sharing of published PDFs via SharedIt, Springer Nature’s content-sharing initiative that was first successfully trialled with Nature-branded journals in 2014. SharedIt provides authors and readers with links to view-only, full-text versions of papers. The links can be posted anywhere, including via social media channels and on other highly-used sites, institutional repositories and authors’ websites, as well as on scholarly collaborative networks. An example of a SharedIt article in Nature Electronics is given here: https://rdcu.be/PuVR. Additionally, Nature-branded journals collaborate with ResearchGate to enable the sharing of published papers.
- Nature Research journals work to ensure that articles meet the highest standards of reproducibility and transparency in reporting. At Nature Machine Intelligence, the editors will work with authors and reviewers to pay close attention to the peer review and sharing of data and code.
- The journal will encourage authors to adopt open source code and data practices. Code will be peer reviewed where relevant. Nature-branded journals strongly encourage researchers to use repositories such as GitHub to share their code during submission and upon publication and strongly recommend using licenses approved by the Open Source Initiative.
- Nature-branded journals are involved in Springer Nature’s partnership with the Research4life programme. This initiative offers free or low-cost online access to relevant journals to researchers in the world’s poorest countries.
Nature Machine Intelligence is now open for submissions. Find out more here: www.nature.com/natmachintell
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