Open Data and transparency in artificial intelligence and machine learning: A new era of research

Abstract

<ns4:p>Artificial Intelligence (AI) and machine learning are the current forefront of computer science and technology. AI and related sub-disciplines, including machine learning, are essential technologies which have enabled the widespread use of <ns4:italic>smart </ns4:italic>technology, such as smart phones, smart home appliances and even electric toothbrushes. It is AI that allows the devices used day-to-day across people’s personal lives, working lives and in industry to better anticipate and respond to our needs. However, the use of AI technology comes with a range of ethical questions – including issues around privacy, security, reliability, copyright/plagiarism and whether AI is capable of independent, conscious thought. We have seen several issues related to racial and sexual bias in AI in the recent times, putting the reliability of AI in question. Many of these issues have been brought to the forefront of cultural awareness in late 2022, early 2023, with the rise of AI art programs (and the copyright issues arising from the deep-learning methods employed to train this AI), and the popularity of ChatGPT alongside its ability to be used to mimic human output, particularly in regard to academic work. In critical areas like healthcare, the errors of AI can be fatal. With the incorporation of AI in almost every sector of our everyday life, we need to keep asking ourselves— can we trust AI, and how much?</ns4:p><ns4:p> This Editorial outlines the importance of openness and transparency in the development and applications of AI to allow all users to fully understand both the benefits and risks of this ubiquitous technology, and outlines how the <ns4:ext-link xmlns:ns5="http://www.w3.org/1999/xlink" ext-link-type="uri" ns5:href="https://f1000research.com/ai_machinelearning">Artificial Intelligence and Machine Learning</ns4:ext-link> Gateway on F1000Research meets these needs.</ns4:p>

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