(PDF) A Review of the Role of Artificial Intelligence in Healthcare
The Impact Of Artificial Intelligence On Work
By Steven Cohen, Ph.D., Director of the M.S. In Sustainability Management program, School of Professional Studies
Throughout human history, new technologies have impacted the world of work. Agriculture disrupted hunting and gathering. The technology of sailing ships expanded the practice of global trade. The work of trading goods and products expanded, and more people worked in trade than in earlier times. Manufacturing replaced the production of many hand-crafted products, and automation reduced employment in manufacturing. Today, we live in a brain-based economy dominated by service industries. It is more lucrative to design clothing than to manufacture it. There is more money in computer software than hardware. Technology marches on, leaving humans to adapt as the jobs they once trained for and held are eliminated or radically modified. Along comes artificial intelligence, which transforms many of the routine and even analytic tasks of the brain-based economy. The machine can draft the presentation deck and analyze the key performance indicators. Soon, the robots will be commanding us, and we will work for them.
Perhaps, but probably not. We have good reason to fear AI, but hopefully we can control it and use it. The history of technological change is one that enhances economic productivity and makes our lives more interesting, less dangerous, and more fulfilling. The economy that my grandparents escaped from in Europe was dominated by a relentless search for food, clothing, shelter, and safety. My grandparents would have thought the idea of work as a means of self-actualization as ridiculous. That was what the synagogue was about, and what you derived from family and, to a lesser degree, from friends. My grandfather Ben Cohen was a baker. For him, work was literally about bringing home loaves of bread and cash to support his family. My father was a businessman whose aim was, in part, the satisfaction gained by building a company and, more crucially, by making as much money as he could in the process. The technologies of mass production, communication, and global travel enabled his business endeavors. His work and approach to work were radically different from his father's. I ended up becoming an educator, and I derive satisfaction from applying research about how the world works into professional education that helps people lead organizations that might make the world a better place. I've taught thousands of students and written over a dozen books, but can barely screw in a lightbulb. I never got to bring home loaves of fresh bread to my family, but the nature of my work and its meaning are as satisfying to me as they were to my grandfather.
The nature of work changes. Technology changes what we do and how we do it—even within the same profession. I began my career as a policy and management analyst before the internet was invented. In graduate school, I often spent scores of hours a week in libraries. I searched for books through card catalogues, wandering through the "stacks" looking at the books adjacent to the ones that I was searching for and learning the ins and outs of the Dewey Decimal system. During my early days in the School of International and Public Affairs, I became the best customer of the "Government Documents Room" in the depths of the Lehman Library. I devoured green covered committee prints from Congress and tried to understand the debates that created the Clean Water Act and Superfund. Years later, I was the beneficiary of a technological miracle: The World Wide Web and search engines. All those committee prints were digitized and placed on the Library of Congress website named for Thomas Jefferson. I could find what I needed in minutes instead of days. Most of Columbia's libraries can be accessed online. I haven't done research work inside a physical library in decades. As a result of Columbia's online library resources, my productivity as a researcher and educator increased exponentially. My work has been made easier and more comprehensive by technology. How will Artificial Intelligence change the way I work? Naturally, I asked ChatGPT to tell me: How will artificial intelligence impact my work as a researcher and educator? This is how it responded (in seconds):
"AI will likely affect your work in both research and education in ways that are both enabling and challenging.If we break it down:
1. As a Researcher
AI is becoming a powerful research partner, especially in disciplines where pattern recognition, data analysis, and literature synthesis matter.
Risks / Caveats:
2. As an Educator
AI is changing how students learn and what skills they need.
Risks / Caveats:
3. Strategic Implications for You
To thrive, you might:
I reviewed ChatGPT's response to my question, agreed with most of it, and couldn't help but be impressed with the speed and organization of its response to my inquiry.
Just as I needed to learn how to replace libraries with search engines, I will now need to augment search engines with Artificial Intelligence. This will enable me to do a more thorough and comprehensive job of analyzing the sustainability policy and management issues that are at the heart of my areas of expertise. I need to adapt and raise my game to fully utilize this amazing new tool that is available to me.
At the heart of this, for me and I suspect for everyone, will be the application of human values and the judgment based on my unique life experiences. These values were influenced by teachers, colleagues, friends, and family. The combination of influences and my interpretation of their meaning is a little like DNA. The basic materials that make me who I am are similar to the stuff that makes everyone else, but my DNA is still exclusively mine. That is the value added I bring to my work. My voice remains my own, and that is true of everyone. That is what distinguishes us from AI: humans are unique and imperfect; AI is based on a set of data available to all, and while it strives for perfection, it can never be unique.
What does Artificial Intelligence mean to our economic, political, and cultural life? Just as the transition from rural to urban living and from manufacturing to the service economy disrupted and damaged many forms of employment, jobs, and communities, we will experience massive disruptions from AI. We are already seeing reductions in the entry-level jobs that did the drudgery work that AI does more rapidly and with far less expense. But if every organization now has the benefit of the analysis and knowledge generated by AI, we can expect that the floor and the bar of organizational competition will be raised and the need for creative and rapid introduction of new services and products will grow. Automation generates increased demands by customers for higher levels of service: Why should I wait in a physical line at the Department of Motor Vehicles when I could simply fill out a form online? Now we will ask: Why do I need to fill out the form? Can't AI generate my information for me to review?
The irony of this change is that many of the technical and engineering skills we thought would guarantee employment, while still needed, will only be the starting point to assure a successful career. Creativity, communication skills, critical thought, innovation, and the ability to pursue relentless experimentation are the best bases for employment going forward. This is not an argument for liberal arts but for interdisciplinary education. ChatGPT was right about the importance of interdisciplinary collaboration. People become experts in one field of knowledge but then learn how to engage in creative group work with people from other fields: Engineers, natural scientists, medical professionals, economists, lawyers, social scientists, and many others work in teams to develop improved products and services. The key skill is the ability to work as both a follower and a leader of a team. Be the person that everyone wants on their team.
The employers who are ecstatic about the prospect of cost savings from AI have decided to eliminate entry-level hiring because the old grinding staff are no longer needed. That is beyond short-sighted and more than a little idiotic. Changing culture and technology cause young people to have radically different life experiences than their elders. The new services and products required due to AI-induced competition will need their input to succeed. Moreover, as middle management ascends, who will replace them a decade from now? Hiring should focus on people who work well in teams, have demonstrated a love of learning, and are self-conscious about the way their own generation thinks the world works.
Artificial Intelligence is a powerful and unpredictable new technology. It will be as transformative as the internet and will change economic and work life. To succeed, workers must learn how to use it to facilitate innovation. Ignoring it or running from it is not a good idea. It must be carefully and thoughtfully embraced, keeping in mind its dangers and limits. Many of the new jobs it will create have yet to be invented. The past several decades of job creation may provide a hint of what might come. In the 21st century, we have seen an explosion of designers, for example, like web designers and fashion designers. We have also seen a high demand for people who can organize events and exhibits. There has been a massive increase in physical and occupational trainers. New careers have developed for social media managers, analysts, and content providers and for podcasters and podcast producers. The list could go on. There is no question that new opportunities and jobs will resemble the past, but will also be impossible to predict today. AI should not be feared, but it should be understood, managed, and regulated.
Views and opinions expressed here are those of the authors, and do not necessarily reflect the official position of Columbia School of Professional Studies or Columbia University.
About the Program
The Columbia University M.S. In Sustainability Management program offered by the School of Professional Studies in partnership with the Climate School provides students cutting-edge policy and management tools they can use to help public and private organizations and governments address environmental impacts and risks, pollution control, and remediation to achieve sustainability. The program is customized for working professionals and is offered as both a full- and part-time course of study.
Key Applications, Challenges Of Artificial Intelligence In Respiratory Care
Io Hui, PhD, researcher at The University of Edinburgh, discusses how artificial intelligence (AI) is being applied in respiratory care for both clinicians and patients.
Artificial intelligence (AI) can be used in respiratory care for patient triage, chest x-ray categorization, and patient self-management, but regulatory and ethical challenges remain, says Io Hui, PhD, researcher at The University of Edinburgh in Scotland.
Hui is also the chair of mHealth and eHealth for the European Respiratory Society.
This transcript was lightly edited.
Transcript
Can you discuss the use of some of the key AI technologies used in respiratory care?
In respiratory care, we have different uses of artificial intelligence, mainly in 2 categories. One is dedicated for the clinicians, and then another one is dedicated for the patients.
For the clinicians, we can use artificial intelligence to triage patients into different hospitals, and from primary care to secondary care, for example. We can also use artificial intelligence to categorize different chest x-rays; this is another example for the clinicians.
For patients, of course, we are focused on the patient self-care and self-management. So, it means, first comes first, we can use artificial intelligence to educate patients and provide them sufficient information so that the patients can interact with the artificial intelligence together to learn more about asthma or COPD, for example. And then, of course, the artificial intelligence, nowadays, can also support clinicians to look after patients around their inhaler technique. So, for example, when an asthma patient is using their inhaler, the artificial intelligence can adjust, and then can advise the patients around whether they are using good technique or not a good technique at all.
And of course, another example, last but not least, we are actually using artificial intelligence to collect real-time patient data with the environmental data altogether, to advise the self-management daily routine in that sense. So, for example, advise them to reduce or increase their inhaler dose in that way.
What are some key challenges of integrating digital technologies into real-world respiratory care settings?
This is a very good question. As [someone with] an engineering background, I would say that the first key challenges are actually very far into the technology process. For example, when we're trying to collect the real-time data from the patients, the Wi-Fi connection is one of the key things that we are going to consider in most cases, because there are set zones in different areas that we can set for the Wi-Fi adopter and then receiver in that sense.
And then another thing is around the regulations, that kind of stuff. So the regulation thing we find a little bit difficult when we are deploying the artificial intelligence just because when the artificial intelligence is involving the patient decisions and also around the advising of the medications, it means that it has to be regulated under the Artificial Intelligence Act in the [European Union], and then somehow we have to make sure that the feature will match what the regulations would like us to do in that sense. But artificial intelligence just evolves very quickly, so it means that once we have evaluated one version, we don't have time to evaluate for the second version. So that is one of the challenges over there.
And then there are other challenges around the data collection, again, because we ask patients to give us the data in real-time. There are 2 ways to do it. One way is to have these smart devices or smart sensors to collect the data automatically from the patients, which is okay, because you are not asking patients to plug in the data by themselves. So it means that you don't have the missing data problem in reality. But again, because this is a passive, automatic data collection, it means that it falls back to the problem around the Wi-Fi and also the equipment as well.
And whether at the end of the day, after we have collected the data, what will be the approach to make sure that the data is accurate, and also the advice is accurate at the back end as well. So these are the challenges, and a lot of people would like to say that, "Oh, the interoperability would be another challenge," just because, for example, in the [United Kingdom], we have different vendors to support the platform in the hospital and primary care and secondary care practices. So within those platforms, we have different protocols and we have different ways to collect data and store data. So how could we make sure that the data can flow between primary care, secondary care, and tertiary care in a fluent way? So that is another challenge.
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Top 10 Artificial Intelligence (AI) Applications For Military Use In ...
In this article, we will be taking a look at the top 10 artificial intelligence (AI) applications for military use in 2024. You can skip our detailed analysis on the AI industry and directly head to the Top 5 Artificial intelligence (AI) Applications for Military Use in 2024.
Global AI Market Growth and Impact: Projections, Opportunities, and Challenges Through 2030The global artificial intelligence (AI) market was estimated to be worth $515.31 billion in 2023 by Fortune Business Insights. By the end of 2030, the market is predicted to have grown at a compound annual growth rate (CAGR) of 21.6% and reach $2.02 trillion.
The AI industry's growth is fueled by the increasing adoption of AI applications, partnerships, and government investments, particularly in sectors like healthcare, retail, banking, and manufacturing. The healthcare sector, an early AI adopter, has seen significant improvements in diagnosis and treatment accuracy. A 2023 Skynova survey found that 80% of U.S. Small business owners are optimistic about AI's role in their operations. A Semrush study of 2,600 businesses revealed that 67% use AI for content marketing and SEO, with 78% reporting satisfaction. AI-driven SEO improved results for 65% of companies, and 93% of marketers review AI-generated content before publication, focusing on EEAT principles for quality.
AI is increasingly seen as a crucial technology for addressing complex challenges across industries. In healthcare, AI is used for diagnostic imaging, personalized treatment plans, and predictive analytics, which can save the U.S. Economy approximately $150 billion annually by 2026. The global economy stands to benefit significantly from AI, with projections suggesting that AI could contribute roughly $15.7 trillion by 2030. However, this technological advancement also poses challenges, such as potential job displacement, with estimates indicating the loss of 85 million jobs but the creation of 97 million new ones, resulting in a net gain of 12 million jobs worldwide.
The United States is a leader in the AI market, capturing over 51.1% of the global market share. This dominance is attributed to the country's advanced technological infrastructure and high adoption rates across various sectors. AI is projected to increase the U.S. GDP by approximately 21% by 2030. The AI software segment held the largest market share in 2022, constituting over 39.3% of the AI market, with deep learning capturing over 35.0% of the market share.
Lockheed Martin and Northrop Grumman: AI Advancements and Financial Performance in Q2 2024Lockheed Martin Corporation (NYSE:LMT) and Northrop Grumman Corporation (NYSE:NOC) are two major American military contractors actively involved in developing artificial intelligence (AI) technologies for defense applications. Lockheed Martin Corporation (NYSE:LMT) has collaborated with IBM's subsidiary, Red Hat, to address AI and data-sharing challenges for the U.S. Department of Defense. This partnership aims to support the military's transition to more distributed forces and mobile equipment. Financially Lockheed Martin Corporation (NYSE:LMT) reported net sales of $18.1 billion for Q2 2024, marking a 9% increase year-over-year.
However, net earnings slightly decreased to $1.6 billion from $1.7 billion in the previous year, resulting in diluted earnings per share (EPS) of $6.85. The company's Aeronautics division reported net sales of $7.28 billion, reflecting a 6% increase driven by the F-35 and F-16 programs. The Missiles and Fire Control segment saw a 13% rise in net sales, reaching $3.1 billion. Rotary and Mission Systems experienced a 17% increase, with net sales totaling $4.55 billion. Meanwhile, the Space segment had a modest 1% increase in net sales, amounting to $3.2 billion. The company raised its full-year guidance, projecting net sales between $70.5 billion and $71.5 billion, with EPS expected to be in the range of $26.10 to $26.60.
Similarly, Northrop Grumman Corporation (NYSE:NOC) is heavily invested in AI, focusing on autonomous systems, including aerial and ground vehicles, and intelligent sensors. The company is a key partner in the Department of Defense's Joint All-Domain Command & Control (JADC2) strategy, which integrates AI to enhance military operations. Northrop Grumman has developed the X-47B autonomous aircraft under a DARPA contract, which has achieved milestones like autonomous takeoff and landing on aircraft carriers and mid-air refueling.
These advancements demonstrate the potential for autonomous aircraft in military operations. Financially, Northrop Grumman Corporation (NYSE:NOC) reported a revenue of $10.2 billion for Q2 2024, which is a 7% increase year-over-year, surpassing estimates of $10.017 billion. The company's GAAP EPS was $6.36 in Q2, reflecting a 19% increase from the previous year's $5.34. Net earnings were $940 million, up 16% from $812 million in Q2 2023. All four segments of the Northrop Grumman Corporation (NYSE:NOC) reported higher sales in Q2: Aeronautics Systems generated $2,963 million, reflecting a 14% increase. Defense Systems reported $1,513 million, up 7%. Mission Systems saw a 5% rise in sales to $2,773 million, while Space Systems experienced a 2% increase, reaching $3,573 million. The company invested $1.8 billion in capital expenditures and approximately $3 billion in R&D. It also increased dividends by 10%.
While we acknowledge the potential of NOC as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns, and doing so within a shorter time frame. If you are looking for an AI stock that is more promising than NOC but that trades at less than 5 times its earnings, check out our report about the cheapest AI stock.
READ ALSO: 17 Latest AI News and Analyst Ratings You Should Not Miss and 33 Most Important AI Companies You Should Pay Attention To.
Pixabay/Public Domain
Our MethodologyHere is the list of the top 10 artificial intelligence (AI) applications for military use in 2024 according to our research.
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10. Predictive MaintenancePredictive maintenance is a critical application of artificial intelligence (AI) in military operations which is aimed at enhancing the reliability and efficiency of military equipment and systems. Predictive maintenance uses AI algorithms to analyze data from various sensors installed on military equipment. This analysis helps in predicting when a component might fail, allowing for proactive maintenance scheduling. A Deloitte report mentions that predictive maintenance can increase productivity by 25%, reduce breakdowns by 70%, and lower maintenance costs by 25%. The Government Accountability Office (GAO) has noted that the US Department of Defense (DoD) spends about $90 billion annually on maintenance and is working on implementing predictive maintenance to improve readiness and reduce costs.
9. Transportation and Casualty CareTransportation and casualty care are among the top applications of artificial intelligence (AI) in the military for 2024. AI significantly enhances military transportation by optimizing logistics, reducing costs, and managing the efficient movement of resources and troops. It also aids in the development of autonomous vehicles for future military use. In casualty care, AI supports medics by analyzing medical data and providing treatment recommendations, though human oversight remains crucial due to AI's limitations in handling life-and-death decisions.
In the field of combat casualty care, innovative AI solutions are making a significant impact. The Automated Ruggedized Combat Casualty Care (ARC3) system, developed by Charles River Analytics, assists medics by diagnosing injuries, monitoring patients, and offering treatment guidance when immediate evacuation isn't feasible. This system empowers medics to make informed decisions under challenging conditions. Similarly, the Ensemble Prediction for Combat Casualty Care (EPIC3) mobile app, also from Charles River Analytics, employs machine learning to predict life-threatening injuries and provides step-by-step treatment instructions through a user-friendly interface. Tailored to the user's skill level, EPIC3 enhances medics' decision-making capabilities in critical situations.
8. Military LogisticsMilitary logistics involves managing supply chains, transportation, and maintenance to keep forces equipped and ready. AI applications in military logistics include predictive maintenance, where systems like the Autonomic Logistics Information System (ALIS) for F-35 jets forecast and prevent equipment failures, thereby cutting downtime and costs. AI also optimizes supply chain management with real-time data analytics and predictive insights, enhancing resource allocation and logistics efficiency by over 20%.
AI-powered cloud services, such as those used by the U.S. Army in partnership with IBM, streamline data processing and decision-making. Additionally, AI-driven driverless vehicles are being explored for autonomous resupply missions, improving safety and ensuring timely delivery of supplies in challenging conditions. The U.S. Department of Defense's Joint Artificial Intelligence Center (JAIC) leads AI integration in military logistics, focusing on scalable applications to boost efficiency and effectiveness. Concurrently, the Army Materiel Command, led by Gen. Ed Daly, is incorporating AI into logistics to enhance timeliness and efficiency, aiming to provide support that aligns with the "speed of relevance" for mission success.
7. Smart WeaponsSmart weapons use AI to improve precision, decision-making, and efficiency in military operations, reducing human intervention and enhancing overall effectiveness in modern warfare. One of the most notable implementations of AI in smart weapons is the U.S. Department of Defense's Project Maven. It processes video data to enhance target recognition and battlefield awareness. In 2020, it successfully identified and targeted a decommissioned tank at Fort Liberty, coordinating with the HIMARS system for a precise strike, showcasing AI's effectiveness in real-time combat.
6. Decision Making (Strategic, and Tactical Battle Management)Artificial intelligence (AI) is increasingly being integrated into military operations, significantly enhancing decision-making processes at strategic, operational, and tactical levels. At the strategic level, AI helps analyze complex data sets to identify patterns and trends, aiding in rapid response to threats and long-term planning. It can simulate scenarios and predict outcomes, improving strategic decision-making through exercises like war gaming.
Operationally, AI optimizes logistics, manages supply chains, and coordinates troop movements by processing real-time data from sources such as satellite imagery. It also enhances cybersecurity by detecting and responding to threats, and protecting military communications and information systems. For instance, Mckinsey highlights that AI-powered logistics solutions can reduce operational costs by up to 15% and improve delivery efficiency by 25%. Here's a revised version with a more structured approach:
Tactically, AI plays a crucial role by providing real-time data analysis and threat assessment, which supports decision-making in scenarios such as drone operations and autonomous vehicle navigation. AI enhances situational awareness through the integration of data from multiple sensors, offering a comprehensive view of the battlefield.
In a related development, Tesla plans to invest $1 billion in its Dojo supercomputer by the end of 2024. This investment is part of Tesla's broader strategy to advance autonomous driving capabilities. Overall, Tesla's commitment to AI and autonomous driving is substantial, with plans to surpass $10 billion in cumulative investment by the end of 2024.
5. Threat AssessmentAI systems in threat assessment integrate vast amounts of data from multiple sources, such as satellites, sensors, and intelligence reports, to provide real-time situational awareness and predictive insights. AI-based threat assessment systems enhance military operations by integrating data from satellites, sensors, and other intelligence sources to provide comprehensive situational awareness. These systems detect anomalies and potential threats in real time, enabling rapid responses and improved operational readiness.
Autonomous surveillance systems, including AI-driven drones and unmanned aerial vehicles (UAVs), gather real-time intelligence on potential threats and enemy movements. The market for AI in defense and security is expanding rapidly, with an estimated valuation of $10.6 billion in 2023 and projected to reach $39.1 billion by 2023, growing at a CAGR of 9.5%. Additionally, AI is crucial for cybersecurity, as it monitors networks for unusual activities and potential cyber threats, allowing for preemptive measures to safeguard sensitive information and infrastructure. The global cybersecurity market, which heavily relies on AI technologies, was valued at $190.4 billion in 2023 and is forecasted to grow to $298.5 billion by 2028, representing a CAGR of 9.4%.
4. Intelligence, Surveillance, and ReconIntelligence, Surveillance, and Reconnaissance (ISR) is one of the top applications of artificial intelligence (AI) in military. AI-powered ISR (Intelligence, Surveillance, and Reconnaissance) systems utilize advanced technologies like computer vision, machine learning, and autonomous platforms to analyze extensive imagery and video data. These systems enhance target identification, tracking, and object recognition. For example, AI can process data from various sources, including social media, to improve situational awareness.
A notable real-world application is seen in the Ukrainian war, where AI tools assist in translating and analyzing intercepted communications. This use of AI speeds up intelligence analysis, allowing military personnel to focus on the most critical information.
Financially, there is substantial investment in AI for military applications. The U.S. Department of Defense (DOD) is significantly funding AI research and development to maintain technological superiority. The Department of Defense's fiscal 2024 budget request includes $1.8 billion for AI and machine learning to boost decision-making and enhance unmanned systems. Similarly, China is investing heavily in AI to modernize its military capabilities by 2035.
3. Combat SimulationCombat simulation is one of the most significant applications of artificial intelligence (AI) in military operations which offers transformative potential in training and operational preparedness. Combat simulations play a crucial role in military strategic planning and training. They allow US military analysts to explore potential outcomes of conflicts with nations like Iran, Russia, and China, providing insights into strategic implications and logistical challenges without real-world risks. These simulations offer a virtual battleground for testing various strategies and understanding the consequences of different scenarios.
The U.S. Army employs AI-driven simulation software to create virtual combat environments that closely mimic real-life scenarios, tailoring training exercises to individual needs. Companies like Sentient Digital, Inc. Are developing advanced AI military training software that uses reinforcement learning to improve combat readiness. Additionally, generative AI has advanced military simulations by producing realistic imagery and adaptive scenarios, enhancing both realism and challenge in training programs. The global market for AI in military applications is experiencing significant growth. According to Market.Us, the AI military market is projected to grow at a compound annual growth rate (CAGR) of 12.4%, reaching a value of USD 24.7 billion by 2032, up from USD 7.9 billion in 2022.
2. CybersecurityAI in cybersecurity is implemented through various techniques, including anomaly detection, predictive analytics, and automated response systems. The U.S. Department of Defense (DoD) has integrated AI into its cybersecurity operations to enhance protection for critical infrastructure and sensitive data. AI tools are employed to continuously monitor networks, detect anomalies, and respond to cyber incidents in real-time, helping to defend against espionage and cyberterrorism.
Secondly, DARPA's Cyber Grand Challenge aims to develop autonomous systems that can detect and patch software vulnerabilities without human intervention. This initiative showcases AI's potential to automate cybersecurity tasks traditionally handled by humans. Lastly, Project Maven which is also known for its drone surveillance applications, also uses AI for cybersecurity. It leverages machine learning algorithms to analyze large datasets and identify potential security threats and vulnerabilities.
1. Autonomous Vehicles (Drones, Ground Vehicles, and Vessels)Autonomous vehicles, including drones, ground vehicles, and vessels, represent one of the top applications of artificial intelligence (AI) for military use in 2024. In the modern battlefield, autonomous vehicles are revolutionizing military operations. Drones that are also known as unmanned aerial vehicles (UAVs), are at the forefront, enhancing intelligence, surveillance, and reconnaissance (ISR) missions. These drones can form swarms that work together like insect colonies, efficiently sharing information and coordinating actions for tasks like target identification and battlefield assessment.
On the ground, autonomous ground vehicles (AGVs) are making their mark. These AI-powered machines tackle dangerous terrains and perform logistical support and reconnaissance roles with minimal human oversight, easing the burden on soldiers. In the maritime domain, autonomous vessels—both surface and underwater—play crucial roles in surveillance, mine detection, and anti-submarine warfare. They operate in hostile environments, providing vital data and maintaining a strategic presence. AI enhances their decision-making and data-processing abilities, crucial for maritime security.
The U.S. Military is heavily investing in these technologies. Drone swarms are being developed for coordinated ISR missions, while autonomous ground vehicles are improving logistics and reconnaissance. Similarly, autonomous vessels are enhancing maritime operations. The market for these unmanned vehicles is booming, expected to hit $100 billion by 2025, with drones making up the largest share.
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Disclosure. None: The Top 10 Artificial Intelligence (AI) Applications for Military Use in 2024 is originally published on Insider Monkey.
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