The evolution of artificial intelligence is growing at a rapid rate with a faster-developing capability. AI is helping with the extensive research by academia and industry with shorter training time for systems increasingly giving better results. AI is becoming practical for many tasks, including image recognition, recommendation systems, and language translation. Many systems are designed for these tasks and are producing excellent results.
Most AI systems are trained to perform a single task, and that too under specific circumstances. They need to adapt better to new environments or new tasks. However, the models of AI and robotics are improving daily, and they have shown promising results in many applications. This can also help in changing the face of warfare with the help of AI and robots.
AI and Robots in Warfare
When it comes to the nature of war, you must have noticed the change in the scenario since the end of World War 2. There have been significant changes in the battle lines, and it is difficult nowadays to identify the terrorists who can easily blend in with the civilians. There are special drones made that are undetectable to the eye, and ballistic missiles can now be launched from 500 miles away.
Maintaining an active-duty army necessitates a considerable expenditure due to the growing lethality of conflict. A US soldier’s recruitment alone costs $15,000; the annual cost of treating an injury is roughly $2 million. We seek to ascertain whether computational agents and artificial intelligence can lower those human expenses (AI).
AI will rule the next major conflict! Who wins will be decided by faster, more robust, and more accurate robots. However, these battles have the potential to be indisputably and unprecedentedly devastating, possibly to the point of a worldwide technological collapse. A workable solution might involve robots that can comprehend their context and deal with novelty in an open environment. However, such cutting-edge technologies shouldn’t end up in the hands of the dishonest or the malicious.
Since World War II, robotics (or other intelligent agents) have been used in combat. Many early robots (like the Soviet tele-tanks or the US “Aphrodite” drones) were either useless or merely useful for specific tasks. The Central Intelligence Agency’s use of the MQB-1 Predator drone in the 1990s marked the beginning of the widespread usage of robotics in military operations (CIA).
Military operators often identified improvised explosive devices and other kinds of danger. At such a time, they rely on past experiences to recognize subtle cues like uneven soil texture or a missing vehicle. In certain situations, robotic agents will be far more effective on the battlefield if an agent can assist soldiers in identifying dangers via contextual data.
What are conflict contextual constructs?
Experts have presented a few soldier variables known as contextual conflict constructs. Let us discuss those variables in detail.
Paralinguistic variable
Usually, military operations occur under noisy and stressful circumstances. Under such conditions, speech recognition is highly inaccurate. Focusing on acoustic or paralinguistic features reduces complexities that adversely affect linguistic features, like speaking in different languages or dialects and having different accents and pitches.
Demographic variable
Studies have shown that it is easier to accept robot partners when robots possess human-like traits. Hence, it is crucial to understand how robotic agents interact with human teammates in future human-agent teams. Robotic agents could help determine whether a soldier is overreacting or playing it safe using metrics such as personality type, age, and gender.
Visual variable
For the vision field of a computer, a dominant approach toward scene recognition is object-based. The object information is sometimes degraded due to the peripheral vision and distance, shadows, and illumination when it comes to real-life scenarios. The video clips on the battlefield will not be stable for a robotic agent. It must identify the context while parsing through jittery image data due to gunfire or explosions. Robotic agents will be expected to identify a scene despite low spatial frequency quickly.
Physiological variable
A robotic agent can rely on the soldier’s emotions to determine if the situation requires intervention. The agent will need to act if a squad of soldiers is distressed. Many studies have focused on predicting physical and emotional stress in combat settings. It will be adequate to predict and monitor the stress levels of a soldier and an agent.
Wrap Up
Undoubtedly, artificial intelligence will be used in future military applications. It can be used in various contexts to increase productivity, lighten user burden, and work more quickly than people. Its ability, explicability, and resilience will improve thanks to ongoing research. The military cannot ignore this technology. Even if we don’t use it, our competitors undoubtedly will, so we need to be able to strike and take down their AI in war.
The appeal of this rising technology must be resisted, though. Giving weak AI systems control over crucial choices in contentious domains creates the potential for terrible outcomes. Right now, important decisions must still be made by humans.
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