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Introduction to Artificial Intelligence

• First Online: 27 January 2022

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• Xiangming Zeng 3 &
• Liangqu Long 4  

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Information technology is the third industrial revolution in human history. The popularity of computers, the Internet, and smart home technology has greatly facilitated people's daily lives. Through programming, humans can hand over the interaction logic designed in advance to the machine to execute repeatedly and quickly, thereby freeing humans from simple and tedious repetitive labor. However, for tasks that require a high level of intelligence, such as face recognition, chat robots, and autonomous driving, it is difficult to design clear logic rules. Therefore, traditional programming methods are powerless to those kinds of tasks, whereas artificial intelligence (AI), as the key technology to solve this kind of problem, is very promising.

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Zeng, X., Long, L. (2022). Introduction to Artificial Intelligence. In: Beginning Deep Learning with TensorFlow. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-7915-1_1

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The Journal of Artificial Intelligence Research (JAIR) is dedicated to the rapid dissemination of important research results to the global artificial intelligence (AI) community. The journal’s scope encompasses all areas of AI, including agents and multi-agent systems, automated reasoning, constraint processing and search, knowledge representation, machine learning, natural language, planning and scheduling, robotics and vision, and uncertainty in AI.

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• Published: 27 August 2024

Artificial intelligence in medical genomics

• Yoichiro Kamatani   ORCID: orcid.org/0000-0001-8748-5597 1 &
• Tadashi Kaname   ORCID: orcid.org/0000-0003-0281-9610 2  

Journal of Human Genetics ( 2024 ) Cite this article

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• Medical genomics

Artificial intelligence (AI) and machine learning (ML) are rapidly growing and becoming essential research tools in the world of science. Genetics is no exception, and many approaches have been developed to incorporate a variety of these techniques. For example, Support Vector Machine (SVM) was used for genome-wide automatic variant filtering in the early phase of the 1000 genomes project, or for integrating prediction scores of the variant impacts, such as SIFT or PolyPhen-2, through CADD (Combined Annotation-Dependent Depletion).

The convolutional neural network, which revolutionized image learning and initially led the third wave of the AI boom, also forms the basis of several state-of-the-art genetic methods. These include DeepVariant for variant calling, SpliceAI for predicting the variant impact on splicing patterns, and DeepSEA, ExPecto, and Basenji for predicting the effect of non-coding genetic variations on gene expression levels.

Lastly, a language model with contextual understanding, based on Transformer architecture, realized highly accurate protein structure prediction by AlphaFold, followed by a better prediction of variant impacts with fine-tuning by human and primate frequency data, as seen by AlphaMissense. The Transformer-based language model was further utilized for predicting non-coding variant functions by Enformer. In addition, generative AI based on language models (e.g., large-scale language model) is being used to support diagnosis of rare diseases.

As shown by these examples, the application of AI techniques in genetics is one of the highly productive research fields that has explored many new possibilities. It is also worth noting that AI has significant applications in cancer genomics as well. In this special issue of the Journal of Human Genetics , we aim to introduce various possibilities to our readers by having the developers of AI methods explain the diverse applications.

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Kamatani, Y., Kaname, T. Artificial intelligence in medical genomics. J Hum Genet (2024). https://doi.org/10.1038/s10038-024-01282-1

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• Published: 28 August 2024

Transforming simulation in healthcare to enhance interprofessional collaboration leveraging big data analytics and artificial intelligence

• Salman Yousuf Guraya 1  

BMC Medical Education volume  24 , Article number:  941 ( 2024 ) Cite this article

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Simulation in healthcare, empowered by big data analytics and artificial intelligence (AI), has the potential to drive transformative innovations towards enhanced interprofessional collaboration (IPC). This convergence of technologies revolutionizes medical education, offering healthcare professionals (HCPs) an immersive, iterative, and dynamic simulation platform for hands-on learning and deliberate practice. Big data analytics, integrated in modern simulators, creates realistic clinical scenarios which mimics real-world complexities. This optimization of skill acquisition and decision-making with personalized feedback leads to life-long learning. Beyond clinical training, simulation-based AI, virtual reality (VR), and augmented reality (AR) automated tools offer avenues for quality improvement, research and innovation, and team working. Additionally, the integration of VR and AR enhances simulation experience by providing realistic environments for practicing high-risk procedures and personalized learning. IPC, crucial for patient safety and quality care, finds a natural home in simulation-based education, fostering teamwork, communication, and shared decision-making among diverse HCP teams. A thoughtful integration of simulation-based medical education into curricula requires overcoming its barriers such as professional silos and stereo-typing. There is a need for a cautious implantation of technology in clinical training without overly ignoring the real patient-based medical education.

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Simulation in healthcare, powered by big data analytics (BDA) and artificial intelligence (AI), stands at the forefront of transformative innovations with a promise to facilitating interprofessional collaboration (IPC). This convergence of technologies towards educational philosophies not only revolutionizes medical training but also enhances the quality of care and patient safety in an IPC climate for an efficient delivery of healthcare system [ 1 ]. Simulation in healthcare showcases a controlled, versatile, and safe environment for healthcare professionals (HCPs) from diverse disciplines to engage in hands-on learning with deliberate practice [ 2 ]. Learners are engrossed in immersive, iterative, and interactive climate which can nurture opportunities for the acquisition of transferable psychomotor and cognition-based skills [ 3 ]. A simulated environment nurtures the real jest of life-long learning where learners can be trained by deliberate practice till the acquisition of their skills.

BDA, embedded in modern cutting-edge simulators, can utilize enormous healthcare data for clinical training and skills acquistion [ 4 ]. For instance, Bateman and Wood employed Amazon’s Web Service to accumulate a complete human genomic scaffold including 140 million individual base pairs by adopting an advanced hashing algorithm [ 5 ]. Later, a BDA platform successfully matched patients’ data of children in hospital to their whole-genome sequencing for the management of potentially incurable clinical conditions [ 6 ]. From another perspective, leveraging clinical scenarios with realism, BDA can be a valuable tool in reflecting the complexities of the real-world medical practice. This data-driven approach diligently mimics the variability and inconsistency encountered in real clinical settings, preparing HCPs for diverse patient encounters and crisis management. Artificial intelligence (AI) with its machine learning algorithm (MLA) and natural language processing (NLP) further fortifies the impact of simulation by enabling adaptive learning experiences [ 7 ]. Moreover, AI-powered patient simulators with automated interfaces can demonstrate high fidelity realistic physiological responses such as pulse, blood pressure, breathing patterns, and facial expressions to allow learners to practice decision-making in lifelike scenarios. By analyzing simulation data, institutions can identify trends, best practices, and areas for improvement, ultimately enhancing patient outcomes and advancing medical knowledge.

Applications of BDA harness the experimental usage of electronic health records, medical imaging, genetic information, and patients’ demographics. By aggregating and analyzing this data, simulation platforms can create realistic scenarios that can be used by learners for clinical reasoning and critical decision-making. Additionally, MLA and NLP have the ability to predict disease prognosis, treatment efficacy, and unwanted outcomes, thereby offering a reliable hub for interactive and immersive learning for HCPs [ 8 ]. MLA and NLP encourage adaptive learning experiences by analyzing learner interactions and performance in real-time. This unique opportunity of acquiring skills mastery with personalized feedback either by simulator, peer, or facilitator makes simulation a master-class educational and training tool for all HCPs. For instance, if a learner consistently makes errors in decision-making or a procedural skill, a smart simulator can tailor further exercises to provide targeted practice opportunities for individual learners.

Clinical training is interposed at the crossroads of adopting AI, virtual reality (VR), and augmented reality (AR) technologies. Beyond training, simulation-driven medical education holds immense potential for quality improvement and research in healthcare [ 9 ]. VR and AR technologies offer immersive experiences that simulate clinical settings with unprecedented realism. VR headsets transform learners into a cyber space where they deal with animations, digital images, and a host of other exercises in virtual climate [ 10 ]. AR overlays digital information onto the physical world, allowing learners to visualize anatomical structures, medical procedures, or patient data in real-time. Moreover, VR and AR can be used to perform high risk medical procedures till the complete acquisition of skill mastery. Such opportunity is not possible due to threats to patient safety and limited time for learners’ training in real-world workplaces [ 11 ]. At the same time, the mapping of learners’ needs with the curriculum is possible only in simulated environment where learners’ expectations can be tailored to meet their learning styles [ 11 ]. AI, VR, and AR technologies in healthcare simulators essentially empower learners to develop clinical expertise, enhance patient care, and drive innovations in healthcare delivery.

An example of integration of AI, NP, ML, and certain other algorithms in simulation is the sepsis management of a virtual patient being managed by a team of HCPs from different healthcare disciplines. A patient presents with fever, confusion, and rapid breathing in the emergency room. AI platform creates a detailed medical record of the patient with past hospital visits, medications, allergies, and baseline health metrics. AI simulates patient’s symptoms in real-time with tachycardia, tachypnea, hypotension, and fever. The trainees interview the virtual patient and AI responds, using NLP, by providing coherent and contextually appropriate answers. The trainees order a set of tests, including blood cultures, a complete blood count, and lactate levels. AI presents realistic test results where blood cultures show a bacterial infection, leukocytosis, and elevated lactate levels. Based on the diagnosis of sepsis, the trainees plan treatment which typically includes oxygen, broad-spectrum antibiotics, and intravenous fluid. AI then adjusts the patient condition based on the trainees’ actions which may lead to improvement in clinical parameters. However, a delayed treatment could lead to worsening symptoms such as septic shock. Furthermore, AI can introduce complications if initial treatments were ineffective or if the trainees commit errors. Thereupon, AI provides real-time feedback on the trainees’ decisions which can highlight missed signs, suggest alternative diagnostic tests, or recommend adjustments to treatment plans. Lastly, AI would generate a summary report of the performance with a breakdown of diagnostic accuracy, treatment efficacy, and adherence to clinical guidelines. MLAs analyze patterns in patient data to assist in diagnosis. In this context, decision trees and neural networks of MLAs analyze vast datasets of patient records to create realistic virtual patients with diverse medical histories and clinical conditions.

There has been a proliferation of empirical research about the powerful role of IPC in medical education [ 12 , 13 ]. IPC fosters shared decision-making, role identification and negotiations, team coherence, and mitigates potential errors [ 14 ]. Through simulated scenarios, HCPs learn to navigate interdisciplinary challenges, appreciate each other’s roles, and develop a shared approach to patient care. Additionally, simulation in healthcare faces the challenges of costs, access, development, and ethical considerations. Nevertheless, the integration of simulation, BDA, VR, AR, and AI heralds a new era of IPC in healthcare, where learning, practice, and innovation converge to shape the future of medicine.

The overarching goal of all healthcare systems focuses on patient safety as reiterated by the World Health Organization (WHO) sustainable development goals [ 15 ]. General Medical Council, Irish Medical Council, Canada MEDs, Accreditation Council for Graduate Medical Education, and EmiatesMEDS are also in agreement with WHO and, in this context, IPC can potentially enhance the quality of care and patient safety [ 16 ]. Though the role of IPC is widely accepted, there is a lukewarm response from medical institutions about its integration into the existing curricula. Professional silos, stereotyping, bureaucratic inertia, and resistant mindsets are some of the deterring factors [ 17 ]. In the era of simulation in healthcare, IPC can be efficiently embedded into this technology-powered educational tool for impactful collaborative teamwork. By harnessing the technological power of VR, AR, and AI, simulation platforms can leverage the indigenous advantage of IPC in clinical training. Once skills acquisition is accomplished in the simulated platform, its recreation in the real world would be a seamless transition of transferable skills.

To sum up, despite an exponential growth in the use of technology-driven simulation in healthcare, educators should be mindful of its careful integration in medical curricula. Clinical training on real patients cannot be replaced by any strategy or tool regardless of its perceived efficiency or effectiveness. Bearing in mind the learning styles of our learners with a preference toward fluid than crystalloid verbal comprehension and fluid reasoning, technology-driven simulation plays a vital role in medical education. A thoughtful integration of simulation pitched at certain courses and modules spiraled across the curriculum will enhance the learning experience of medical and health sciences students and HCPs [ 18 ].

Data availability

No datasets were generated or analysed during the current study.

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Guraya, S.Y. Transforming simulation in healthcare to enhance interprofessional collaboration leveraging big data analytics and artificial intelligence. BMC Med Educ 24 , 941 (2024). https://doi.org/10.1186/s12909-024-05916-y

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NEH Awards $2.72 Million to Create Research Centers Examining the Cultural Implications of Artificial Intelligence

Five institutions receive neh grants to coordinate research on the societal, ethical, and legal ramifications of ai technology.

The National Endowment for the Humanities (NEH) today announced grant awards totaling $2.72 million for five colleges and universities to create new humanities-led research centers that will serve as hubs for interdisciplinary collaborative research on the human and social impact of artificial intelligence (AI) technologies.

As part of  NEH’s third and final round of grant awards for FY2024 , the Endowment made its inaugural awards under the new  Humanities Research Centers on Artificial Intelligence program, which aims to foster a more holistic understanding of AI in the modern world by creating scholarship and learning centers across the country that spearhead research exploring the societal, ethical, and legal implications of AI. 

Institutions in California, New York, North Carolina, Oklahoma, and Virginia were awarded NEH grants to establish the first AI research centers and pilot two or more collaborative research projects that examine AI through a multidisciplinary humanities lens. 

The new Humanities Research Centers on Artificial Intelligence grant program is part of NEH’s agencywide  Humanities Perspectives on Artificial Intelligence initiative, which supports humanities projects that explore the impacts of AI-related technologies on truth, trust, and democracy; safety and security; and privacy, civil rights, and civil liberties. The initiative responds to President Biden’s  Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence , which establishes new standards for AI safety and security, protects Americans’ privacy, and advances equity and civil rights. 

“The rapid development of artificial intelligence has far-reaching consequences for American society, culture, and democracy,” said NEH Chair Shelly C. Lowe (Navajo). “The humanities provide the ethical compass and historical context to help us understand the full implications of AI technologies, giving both creators and users of AI the necessary tools to navigate its risks and rewards responsibly, critically, and deliberately. Through NEH’s Humanities Perspectives on Artificial Intelligence initiative and these new grants, NEH is fostering much-needed research to help guide technology developers, policy makers, and the public in the responsible and ethical development and adoption of AI.” 

The Humanities Perspective on Artificial Intelligence initiative supports AI-related humanities projects through a number of NEH funding opportunities, including  Humanities Research Centers on Artificial Intelligence and another new grant program,  Dangers and Opportunities of Technology: Perspectives from the Humanities , which supports individuals and teams of scholars engaged in humanities-centered research that examines technology and its relationship to society. It also encompasses AI research and education projects funded through NEH’s longstanding grant programs in  Collaborative Research ,  Institutes for Advanced Topics in Digital Humanities , and  fellowship and summer stipend programs for individual scholars . 

Since launching the Humanities Perspective on Artificial Intelligence initiative in October 2023, NEH has awarded approximately $3.7 million to support research on the promises and pitfalls of AI technologies, on the development of AI tools and methods to investigate humanities topics and resources, and training and curriculum projects that increase AI literacy among humanities scholars and the public. 

In April 2024,  19 new projects were awarded a total of $1.9 million in Dangers and Opportunities of Technology: Perspectives from the Humanities   grants . These awards funded a range of research projects undertaken by individuals and teams of scholars, including: a book on the use of artificial intelligence to generate and disseminate disinformation to influence, manipulate, or deceive audiences; a history of life-support technology in the United States and how it changed American culture and health care in the 20th century; and an analysis of the ways individuals in creative industries engage with generative artificial intelligence technologies and its potential impact on arts and culture.

Other projects under the Humanities Perspective on Artificial Intelligence initiative include a grant to Eastern Connecticut State University to develop an AI-related humanities curriculum across five liberal arts colleges, and a  cooperative agreement with the Modern Language Association to hold a two-day convening on the impact of AI on reading, writing, and languages.

Additional AI-related projects receiving funding today include work at the University of South Dakota on the development and testing of SubjectSpotter , AI-based software to automatically create subject tags for digitized cultural heritage materials to enhance search and usability; and a weeklong institute at the University of Kansas focused on teaching critical AI literacy to secondary, community college, and college-level humanities instructors. 

Researchers at the University of Pennsylvania will receive a $200,000 grant to work as part of a multinational team on a comparative study of the role of large corporations in developing, deploying, and regulating artificial intelligence in the United States, Canada, and the United Kingdom. This grant was awarded by NEH as part of the  Trans-Atlantic Platform , an international collaboration between 11 major funders in the humanities and social sciences from the U.S., Brazil, Canada, Croatia, France, Poland, South Africa, Switzerland, and the United Kingdom to strengthen interdisciplinary cooperation on humanities and social sciences research that addresses the challenges of the 21st century. 

Five new Humanities Research Centers on Artificial Intelligence grants were awarded today:

• The University of California, Davis Outright: $499,717   to establish the UC Davis Center for Artificial Intelligence and Experimental Futures (CAIEF) on the democratization of AI technology.  Led by project director Colin Milburn, the new CAIEF center will conduct six collaborative projects, three public engagement workshops, one conference, and produce an online handbook of best practices relating to civil rights and the democratization of AI in the United States.   
• Bard College in New York  Outright: $500,000 to establish the Wihanble S'a Center, a humanities research center on Indigenous protocols for AI technology.  Led by project director Suzanne Kite (Oglala Lakota), a team of researchers from across the United States and Canada will conduct a collaborative research program, host interdisciplinary symposia, develop educational workshop modules, and publish scholarly articles and a book on Indigenous protocols for AI development that will guide the creation and refinement of AI wearable and digital technologies.   

North Carolina State University   Outright: $500,000 to establish the Embedding AI in Society Ethically (EASE) Center on the ethics of agent-based AI.

Led by project director Veljko Dubljevic, the new EASE Center will serve as a hub for research on AI ethics. Projects supported by the grant include the creation of a postdoctoral fellow mentoring program, a new graduate minor in AI ethics, an annual conference, and special journal issues on topics such as ethical considerations related to autonomous vehicles, large language models (LLMs), and AI-based technologies for eldercare.   

The University of Oklahoma, Norman Outright: $498,129 to establish the OU Center for Creativity and Authenticity in AI Cultural Production, focusing on generative AI and the meaning of creativity, authenticity, and appropriation.

Led by project director Hunter Heyck, Kim Marshall, and Pete Froslie, the new center will coordinate six research teams investigating questions related to AI and creative and intellectual endeavors, public trust and governance, and Native American cultural sovereignty through a linked set of research projects, interdisciplinary conferences and associated edited volumes, and public lectures.  

• The University of Richmond , in Virginia Outright: $491,863 Match: $226,602 to establish the Center for Liberal Arts and AI (CLAAI) on the social, cultural, and legal dimensions of artificial intelligence, with a focus on visual AI. Led by project director Lauren Tilton, CLAAI will serve as a nexus for a consortium of 16 liberal arts colleges across the Southeast to collaborate on research into the social, cultural, and legal possibilities and challenges of AI. Building upon an existing strength in visual AI, the center will support research fellows, provide faculty support grants to enhance AI expertise and expand course offerings in AI ethics, and convene institutes and a public symposium exploring issues related to AI and power and access, and the effects of AI technology on the environment. 

New application information for NEH’s Humanities Research Centers on Artificial Intelligence funding opportunity will be posted this fall. Consult the  NEH website for application guidelines and deadlines. 

National Endowment for the Humanities(NEH): Created in 1965 as an independent federal agency, the National Endowment for the Humanities supports research and learning in history, literature, philosophy, and other areas of the humanities by funding selected, peer-reviewed proposals from around the nation. Additional information about the National Endowment for the Humanities and its grant programs is available at  neh.gov .

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The Future of Artificial Intelligence

Navigating the future: the societal impact and ethical considerations of artificial intelligence.

The document explores the multifaceted impact of artificial intelligence on society, highlighting economic growth, employment trends, and ethical considerations. It emphasizes the need for proactive measures, including education, ethical practices, and inclusive policies, to harness AI’s benefits while mitigating risks, ensuring equitable progress for all members of society.

Ethics in Artificial Intelligence

Artificial Intelligence and Machine Learning

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The assignment titled “Impact of Artificial Intelligence on Society” by Ian-Paul Eric Chase Douglas delves into the transformative effects of AI across various sectors. It examines economic changes, highlighting both growth opportunities and challenges such as job displacement and income inequality. The essay also addresses ethical considerations, including privacy concerns and algorithmic bias, emphasizing the importance of developing robust guidelines for AI deployment. Recommendations include investing in education and reskilling programs, promoting ethical AI practices, and fostering public engagement to align AI technologies with societal values. Ultimately, the work underscores the necessity of proactive measures to ensure that the benefits of AI are equitably distributed, paving the way for a future that prioritizes fairness, inclusivity, and human well-being.

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