How AI will change the pace of scientific discovery
ARTICLE SUMMARY
Jill Luber, CTO, Elsevier explores how AI is revolutionising scientific research and healthcare. Jill also also discusses the ethical considerations of AI.
Jill Luber is the Chief Technology Officer (CTO) at Elsevier, leading a global team of over 2000 technologists.
She fosters an inclusive work environment that drives innovation and continuous learning, resulting in her team being recognized as the Best Engineering team by Comparably in 2024. Previously, as VP & CTO – Healthcare & Government at LexisNexis Risk Solutions, Jill spearheaded technology development and growth in these sectors. Her leadership roles at Risk included VP – Technology/Architect and Senior Architect, where she oversaw critical product development and optimization. Jill’s expertise spans various industries and technologies, highlighted by her successful management of large-scale data fabrication projects and integration efforts during mergers and acquisitions. With a Bachelor’s degree in Computer Engineering from Mississippi State University, Jill’s exceptional leadership, commitment to excellence, and dedication to diversity and inclusion make her a highly respected figure in the technology industry
There is no doubt that generative AI is a game changer and has emerged as a transformative force across industries, especially in scientific research and healthcare.
It is revolutionizing the way scientific information is utilized by researchers, scientists, and healthcare professionals.
A prime example of this is through the launch of AI-powered tools, such as Elsevier’s Scopus AI and ClinicalKey AI, that enable researchers to extract valuable insights from vast amounts of scientific literature quickly and efficiently. These tools employ natural language processing, machine learning, and data mining techniques to analyze and interpret scientific articles, accelerating the discovery process and facilitating evidence-based decision-making.
For researchers, AI algorithms can analyze vast amounts of scientific data, identifying patterns and correlations that may have otherwise gone unnoticed by the human eye. This enables researchers to make connections and draw conclusions more rapidly, leading to accelerated scientific discoveries. Additionally, AI can assist in automating repetitive tasks, freeing up researchers’ time to focus on more complex and critical thinking activities. By augmenting human intelligence with AI capabilities, critical thinking can be enhanced, leading to more innovation and impactful research.
Given the pace of evolution, AI is already transforming the industry at an unprecedented rate. For example, in health education, AI-powered platforms can provide personalized learning experiences, tailoring educational content to individual needs and enhancing knowledge retention. In diagnosis, AI algorithms can analyze medical images, patient records, and genetic data, aiding in the early detection of diseases and improving accuracy. Furthermore, AI can assist in treatment planning by examining vast amounts of patient data and recommending personalized treatment options, leading to more effective and efficient care.
As exciting as all of this is, as with any technology, we always need to be mindful of its limitations. One significant concern is the ethical use of AI, including data privacy and bias. AI requires access to a lot of data, which may be sensitive or personal, so appropriate privacy and copywrite permissions must be applied when training any AI tool. Additionally, if the data used to train an AI algorithm is biased, then the algorithm will be biased too, and in most cases without the user’s knowledge. Ensuring transparency, fairness, and accountability in AI algorithms is crucial to avoid biases and unintended consequences.
The reliance on AI may lead to a reduction in human involvement, potentially impacting the development of scientific intuition and creativity. It is so important that we are mindful of how we can effectively strike a balance between AI-driven automation and human expertise to maximize the benefits of both to society.
AI is a field that is evolving at unprecedented speed and scale. While challenges and ethical considerations exist, the potential benefits of AI in advancing critical thinking, accelerating scientific discoveries, and shaping the future of healthcare are immense. These capabilities give us space to imagine products and services that we would never have been able to deliver before – while, making sure we are embracing AI responsibly and collaboratively, will undoubtedly lead to a brighter and more innovative future in science and healthcare.
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How AI will change the pace of scientific discovery
ARTICLE SUMMARY
Jill Luber is the Chief Technology Officer (CTO) at Elsevier, leading a global team of over 2000 technologists.
She fosters an inclusive work environment that drives innovation and continuous learning, resulting in her team being recognized as the Best Engineering team by Comparably in 2024. Previously, as VP & CTO – Healthcare & Government at LexisNexis Risk Solutions, Jill spearheaded technology development and growth in these sectors. Her leadership roles at Risk included VP – Technology/Architect and Senior Architect, where she oversaw critical product development and optimization. Jill’s expertise spans various industries and technologies, highlighted by her successful management of large-scale data fabrication projects and integration efforts during mergers and acquisitions. With a Bachelor’s degree in Computer Engineering from Mississippi State University, Jill’s exceptional leadership, commitment to excellence, and dedication to diversity and inclusion make her a highly respected figure in the technology industry
There is no doubt that generative AI is a game changer and has emerged as a transformative force across industries, especially in scientific research and healthcare.
It is revolutionizing the way scientific information is utilized by researchers, scientists, and healthcare professionals.
A prime example of this is through the launch of AI-powered tools, such as Elsevier’s Scopus AI and ClinicalKey AI, that enable researchers to extract valuable insights from vast amounts of scientific literature quickly and efficiently. These tools employ natural language processing, machine learning, and data mining techniques to analyze and interpret scientific articles, accelerating the discovery process and facilitating evidence-based decision-making.
For researchers, AI algorithms can analyze vast amounts of scientific data, identifying patterns and correlations that may have otherwise gone unnoticed by the human eye. This enables researchers to make connections and draw conclusions more rapidly, leading to accelerated scientific discoveries. Additionally, AI can assist in automating repetitive tasks, freeing up researchers’ time to focus on more complex and critical thinking activities. By augmenting human intelligence with AI capabilities, critical thinking can be enhanced, leading to more innovation and impactful research.
Given the pace of evolution, AI is already transforming the industry at an unprecedented rate. For example, in health education, AI-powered platforms can provide personalized learning experiences, tailoring educational content to individual needs and enhancing knowledge retention. In diagnosis, AI algorithms can analyze medical images, patient records, and genetic data, aiding in the early detection of diseases and improving accuracy. Furthermore, AI can assist in treatment planning by examining vast amounts of patient data and recommending personalized treatment options, leading to more effective and efficient care.
As exciting as all of this is, as with any technology, we always need to be mindful of its limitations. One significant concern is the ethical use of AI, including data privacy and bias. AI requires access to a lot of data, which may be sensitive or personal, so appropriate privacy and copywrite permissions must be applied when training any AI tool. Additionally, if the data used to train an AI algorithm is biased, then the algorithm will be biased too, and in most cases without the user’s knowledge. Ensuring transparency, fairness, and accountability in AI algorithms is crucial to avoid biases and unintended consequences.
The reliance on AI may lead to a reduction in human involvement, potentially impacting the development of scientific intuition and creativity. It is so important that we are mindful of how we can effectively strike a balance between AI-driven automation and human expertise to maximize the benefits of both to society.
AI is a field that is evolving at unprecedented speed and scale. While challenges and ethical considerations exist, the potential benefits of AI in advancing critical thinking, accelerating scientific discoveries, and shaping the future of healthcare are immense. These capabilities give us space to imagine products and services that we would never have been able to deliver before – while, making sure we are embracing AI responsibly and collaboratively, will undoubtedly lead to a brighter and more innovative future in science and healthcare.
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