New book highlights real-world applications of artificial intelligence (AI) and machine learning (ML)

Bentham Science Publishers
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Bentham Science is pleased to announce the release of Advancements in Artificial Intelligence and Machine Learning, a timely publication exploring the transformative role of AI and ML across diverse industries and domains.
This book is a detailed collection of twelve research-backed chapters, each focusing on a key area of artificial intelligence and machine learning, ranging from mechatronics and cybersecurity to digital health and automation. Readers will get insights into the impact of AI-based techniques in power systems, social media management, drone robotics, smart grids, healthcare diagnostics, and crime prevention systems.
Beginning with an overview of AI’s potential in next-generation mechatronics, this volume navigates through the role of AI and deep learning in energy systems, sentiment analysis, image processing, wireless networks, and advanced medical technologies such as brain tumor detection. Each chapter provides practical insights into emerging tools and real-world applications, making this an essential reference for researchers and professionals.
Key Features:
A multidisciplinary focus on AI and ML applications in robotics, energy, cybersecurity, and healthcare

Contemporary research exploring intelligent automation and secure systems

Case-based insights from industry and academia

Practical guidance on AI-driven innovation, decision-making, and technology implementation
Learn more about this book here: http://bit.ly/4524NYk
For media inquiries, review copies, or interviews, please contact Bentham Science Publishers.

About the Editors

Dr. Asif Khan
Dr. Khan is an Assistant Professor in the Department of Computer Applications at Integral University, Lucknow. He holds a Ph.D. and postdoctoral experience from the University of Electronic Science and Technology of China (UESTC), with over eight years of academic and research experience. His expertise includes artificial intelligence, robotics, and machine learning. He has published over 100 research articles and holds nine patents. Dr. Khan is an active member of IEEE, IAENG, and other professional bodies.
Dr. Mohammad Kamrul Hasan
Dr. Hasan is an Associate Professor at Universiti Kebangsaan Malaysia (UKM), where he leads the Network and Communication Technology Research Lab at the Center for Cyber Security. He earned his Ph.D. in Electrical and Communication Engineering from the International Islamic University Malaysia. His research interests span cybersecurity, Industrial IoT, privacy protection, and transparent AI. He has authored over 150 indexed research publications and serves on editorial boards of top-tier journals including IEEE, Elsevier, and MDPI.
Dr. Naushad Warish
Dr. Warish earned his Ph.D. in Computer Science from the Indian Institute of Technology (ISM), Dhanbad. His specialization includes content-based image retrieval, artificial intelligence, and digital image processing. He has also qualified the UGC-NET and has extensive knowledge of programming languages such as C, C++, and Python. His work bridges core computational theory with practical implementation in AI and ML.
Dr. Mohammed Aslam Husain
Dr. Husain is an Assistant Professor in the Department of Electrical Engineering at Rajkiya Engineering College, Ambedkar Nagar, India. He has held academic positions at Integral University and Aligarh Muslim University. Recipient of the Young Scientist Award (2017) and the Institution of Engineers (India) Young Engineers Award (2022–23), he has authored more than 60 scientific publications. His areas of interest include electrical systems, automation, and AI-driven control systems.

DOI

10.2174/97898153225831250101

Researchers advocate for separate roles between AI and humans

Radiological Society of North America

OAK BROOK, Ill. – Renowned physician-scientist Eric J. Topol, M.D., and Harvard artificial intelligence (AI) expert Pranav Rajpurkar, Ph.D., advocate for a clear separation of the roles between AI systems and radiologists in an editorial published today in Radiology, a journal of the Radiological Society of North America (RSNA).

“We’re stuck between distrust and dependence, and missing out on the full potential of AI,” said Dr. Rajpurkar, associate professor of Biomedical Informatics at Harvard University.

The authors urge a rethinking of the assistive role of AI, which is designed to work alongside human radiologists to improve diagnostic accuracy. But so far, fully integrating AI into radiology workflows has fallen short of expectations.

“It’s still early for getting a definitive assessment,” said Dr. Topol, professor and executive vice president, Scripps Research. “But several recent studies of GenAI have not demonstrated the widely anticipated synergy between AI and physicians.”

"Current evidence suggests that neither fully integrated assistive approaches nor complete automation are optimal," Dr. Rajpurkar said. "Radiologists don't know when to trust AI and when to trust themselves. Add AI errors into the mix, and you get a perfect storm of uncertainty."

Implementing assistive AI has presented notable challenges, including cognitive biases that cause radiologists to disregard or over-rely on AI suggestions. Misaligned incentives, unclear workflows, liability concerns, and economic models that don't support AI integration have also slowed its adoption.

"After years of hype, AI penetration in U.S. radiology remains surprisingly low," Dr. Rajpurkar said. "This suggests we've been implementing AI like sprinkling digital fairy dust on broken workflows. The real opportunity isn't marginal accuracy gains, it's workflow transformation."

The authors propose a careful, measured approach to role separation—guided by rigorous clinical validation and real-world evidence—as the most pragmatic path forward. Their framework includes three models:

AI-First Sequential Model—Where effective, AI processes the initial segment of the workflow (e.g., preparing clinical context from electronic health records), followed by the radiologist providing expert interpretation.
Doctor-First Sequential Model—The radiologist initiates the diagnostic process while AI performs complementary tasks such as report generation and follow-up recommendations to enhance the workflow.
Case Allocation Model—Cases are triaged based on complexity and clarity, with some managed entirely by AI, others by a radiologist, and the rest through a combination of both.

“Radiologists are stuck in the worst of both worlds—afraid to trust AI fully, but too reliant to ignore it,” Dr. Rajpurkar said. “Clear role separation breaks this cycle.”

The authors envision institutions implementing their framework through repeated interactions rather than strict, sequential processes.

“We’re providing a framework, but the real innovation will come from frontline radiologists adapting it to their specific needs,” Dr. Rajpurkar said. “Institutions will likely discover hybrid approaches we haven’t even imagined yet.”

For example, a trauma center might use the AI-First model to review chest X-rays overnight, then switch to a Doctor-First model when teaching residents. Under the Case Allocation model, an AI screening system may identify and ‘clear’ normal results, escalating only abnormal cases to the radiologist for review.

“The breakthrough moment comes when practices stop asking ‘Which model?’ and start asking ‘Which model when?’” he said. “That’s where the magic happens—adaptive workflows that respond to real-time clinical needs, not rigid theoretical constructs.”

Implementing their vision will require carefully designed pilot programs to test the models in real clinical environments, measuring accuracy, workflow efficiency, radiologist satisfaction and downstream outcomes.

“Results must be shared openly; the field desperately needs honest case studies,” Dr. Rajpurkar said. “Our framework gives radiologists not another promise of AI magic, but a concrete, practical roadmap for integration that acknowledges both the current limitations and the inevitable evolution of AI.”

The researchers also suggest establishing a clinical certification pathway for AI systems, something no single agency is equipped to handle alone.

“The Food & Drug Administration needs to maintain safety oversight, but clinical certification requires understanding real-world workflow integration, which goes beyond traditional regulatory scope,” Dr. Rajpurkar said. “We need new models, perhaps independent certification bodies with input from multiple stakeholders and consortia that bring together clinical expertise, technical knowledge and implementation experience.”

The researchers are awaiting the emergence of general medical AI systems capable of handling routine tasks, preparing cases, and drafting reports, all while learning the patterns of the practice.

“We're not there yet,” Dr. Rajpurkar said. “But when these systems can competently manage the breadth of tasks a senior medical resident handles, the entire conversation changes. That’s the inflection point we’re watching for.”

###

“Beyond Assistance: The Case for Role Separation in AI-Human Radiology Workflows.”

Radiology is edited by Linda Moy, M.D., New York University, New York, N.Y., and owned and published by the Radiological Society of North America, Inc. (https://pubs.rsna.org/journal/radiology)

RSNA is an association of radiologists, radiation oncologists, medical physicists and related scientists promoting excellence in patient care and health care delivery through education, research and technologic innovation. The Society is based in Oak Brook, Illinois. (RSNA.org)

For patient-friendly information on medical imaging, visit RadiologyInfo.org.

Journal

Radiology

Subject of Research

Not applicable

Article Title

Beyond Assistance: The Case for Role Separation in AI-Human Radiology Workflows

Article Publication Date

29-Jul-2025

Human dignity must be protected from rise

of AI, Pope says

Jack Burgess
BBC News

JULY 30, 2025

EPA

Pope Leo XIV has told the Vatican's first Mass for Catholic social media influencers that human dignity needs to be protected online as the world faces the "challenge" of artificial intelligence (AI).

"Nothing that comes from man and his creativity should be used to undermine the dignity of others," the Pope said in St Peter's Basilica.

He said the developing technology should be used for the "benefit of all humanity" during comments at the Vatican's Jubilee of Youth, a week-long gathering for young worshipers which is held every 25 years.

It is the latest in a string of interventions the Pope has made on the subject of AI since he was elected in May.

During Tuesday's speech, the Pope called on the world to protect "our ability to listen and speak" in a "new era".

"We have a duty to work together to develop a way of thinking, to develop a language, of our time, that gives voice to love," the Pope said.

He also urged social media influencers to seek out "those who suffer and need to know the Lord" with their content.

"Be agents of communion, capable of breaking down the logic of division and polarisation, of individualism and egocentrism," he added.

EPA

During his first Sunday address in May, Pope Leo XIV suggested that the development of AI, and other advances, meant the Church was necessary for the defence of human dignity and justice.

Pope Leo XIV, who studied maths at Philadelphia's Villanova University in 1977, is the first pontiff from the United States.

Born in Chicago in 1955 to parents of Spanish and Franco-Italian descent, Leo served as an altar boy and was ordained in 1982.

Although he moved to Peru three years later, he returned regularly to the US to serve as a priest and a prior in his home city.

He has Peruvian nationality and is fondly remembered as a figure who worked with marginalised communities and helped build bridges.

AI Warfare: Can India take the lead?

As autonomous drones execute precision strikes and algorithms command battlefield operations, the question isn't whether AI will dominate military strategy, but whether India will lead or lag in this critical transformation.

AI is rewriting future warfare rules. (Photo: Representational/Getty)

India Today Global Desk
Jul 29, 2025

The future of warfare is being rewritten by artificial intelligence, and India is positioning itself at the forefront of this digital revolution. As autonomous drones execute precision strikes and algorithms command battlefield operations, the question isn’t whether AI will dominate military strategy, but whether India will lead or lag in this critical transformation.

AI: The New Backbone of Military Operations

By 2030, AI is projected to become the backbone of global military operations, merging land, sea, air, space, and cyber warfare into a unified, intelligent theatre. Modern armies cannot remain relevant without embracing this technology, as AI systems now process more data in seconds than human generals can analyse in days.

India has recognised this paradigm shift. The Ministry of Defence has declared 2025 the “Year of Reforms”, with AI and robotics taking centre stage. This isn’t merely symbolic: over 75 AI-powered defence products have been indigenously developed, ranging from autonomous drones to smart surveillance and cyber defence platforms.

Building India’s AI-First Military Strategy

The creation of the Defence AI Council (DAIC) and the Defence AI Project Agency (DAIPA) signals India’s serious commitment to AI integration. Each service arm, the Army, Navy, and Air Force, now operates dedicated AI working groups, with annual budgets allocated and comprehensive roadmaps established.

On the ground, this technology is already operational. In Kashmir, AI-powered drones patrol terrain too dangerous for human forces. Along the Line of Control, swarm drones provide area denial and predictive threat detection. The Avekshan system distinguishes between livestock and genuine threats, filtering false alarms while delivering real-time alerts.

Combat-Ready Innovations

India’s drone capabilities showcase its AI ambitions most clearly. Surveillance UAVs like Heron and Rustom sweep vast border zones with precision, while combat drones like Rudrastra execute strikes in hostile terrain. Swarm technology enables dozens of AI-powered drones to operate as a collective intelligence, jamming enemy radars and intercepting intrusions.

The Indrajaal defensive drone shield protects 4,000 square kilometres using AI-driven interception technology. The D4 Anti-Drone system, featuring 360-degree radar and laser tracking, has intercepted over 80% of rogue drones encountered.

Smart Borders and Strategic Defence

India’s extensive borders now feature “smart” defensive systems with laser walls, facial recognition, motion sensors, and real-time alerts. Project Himshakti utilises satellite data and AI modelling to predict potential cross-border movement routes, shifting focus from reaction to anticipation.

Beyond Government: A Growing Ecosystem

India’s AI defence ecosystem extends beyond government laboratories. Startups like ideaForge and DSRL produce battlefield-ready drones and surveillance tools, while the iDEX initiative fuels defence technology entrepreneurship. Microsoft’s $3 billion commitment to India’s AI infrastructure demonstrates international confidence in the country’s potential.

Global Ambitions and Challenges

With a $5 billion defence export target by 2025, India eyes international markets for its AI-enabled products. These technologies often have dual-use civilian applications in disaster response, logistics, and medical aid, expanding market opportunities and diplomatic influence.

However, challenges remain: procurement delays, fragmented frameworks, ethical considerations, and shortages of AI-literate personnel. The critical question is whether India can maintain momentum in a rapidly evolving global landscape where China, the United States, and Israel continue advancing their own AI warfare capabilities.

India stands at the threshold of military innovation, ready to become not just AI-ready, but AI-dominant in the algorithmic age of warfare.

- Ends

How to survive the explosion of AI slop

PNAS Nexus

Farid deepfake — image:
A deepfake in which the author inserted his own face (source in upper left) into an AI-generated image of an inmate in an orange jumpsuit.
view more
Credit: AI image created by Hany Farid

In a Perspective, Hany Farid highlights the risk of manipulated and fraudulent images and videos, known as deepfakes, and explores interventions that could mitigate the harms deepfakes can cause. Farid explains that visually discriminating the real from the fake has become increasingly difficult and summarizes his research on digital forensic techniques, used to determine whether images and videos have been manipulated. Farid celebrates the positive uses of generative AI, including helping researchers, democratizing content creation, and, in some cases, literally giving voice to those whose voice has been silenced by disability. But he warns against harmful uses of the technology, including non-consensual intimate imagery, child sexual abuse imagery, fraud, and disinformation. In addition, the existence of deepfake technology means that malicious actors can cast doubt on legitimate images by simply claiming the images are made with AI. So, what is to be done? Farid highlights a range of interventions to mitigate such harms, including legal requirements to mark AI content with metadata and imperceptible watermarks, limits on what prompts should be allowed by services, and systems to link user identities to created content. In addition, social media content moderators should ban harmful images and videos. Furthermore, Farid calls for digital media literacy to be part of the standard educational curriculum. Farid summarizes the authentication techniques that can be used by experts to sort the real from the synthetic, and explores the policy landscape around harmful content. Finally, Farid asks researchers to stop and question if their research output can be misused and if so, whether to take steps to prevent misuse or even abandon the project altogether. Just because something can be created does not mean it must be created.