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Artificial Intelligence and the Future of War
There could be no more consequential decision than launching atomic weapons and possibly triggering a nuclear holocaust.
Kennedy faced just such a moment during the Cuban Missile Crisis of 1962 and, after envisioning the catastrophic outcome of a US-Soviet nuclear exchange, he came to the conclusion that the atomic powers should impose tough barriers on the precipitous use of such weaponry.
With artificial intelligence, or AI, soon to play an ever-increasing role in military affairs, as in virtually everything else in our lives, the role of humans, even in nuclear decision-making, is likely to be progressively diminished.
Rather than focusing mainly on weaponry and tactics aimed at combating poorly armed insurgents in never-ending small-scale conflicts, the American military is now being redesigned to fight increasingly well-equipped Chinese and Russian forces in multi-dimensional (air, sea, land, space, cyberspace) engagements involving multiple attack systems (tanks, planes, missiles, rockets) operating with minimal human oversight.
“The major effect/result of all these capabilities coming together will be an innovation warfare has never seen before: the minimization of human decision-making in the vast majority of processes traditionally required to wage war,”
“In this coming age of hyperwar, we will see humans providing broad, high-level inputs while machines do the planning, executing, and adapting to the reality of the mission and take on the burden of thousands of individual decisions with no additional input.”
Ordinarily, national leaders seek to control the pace and direction of battle to ensure the best possible outcome, even if that means halting the fighting to avoid greater losses or prevent humanitarian disaster.
Yes, remotely piloted aircraft (RPA), or drones, have been widely used in Africa and the Greater Middle East to hunt down enemy combatants, but those are largely ancillary (and sometimes CIA) operations, intended to relieve pressure on US commandos and allied forces facing scattered bands of violent extremists.
To ensure continued military supremacy, he added, the Pentagon would have to focus more “investment in technological innovation to increase lethality, including research into advanced autonomous systems, artificial intelligence, and hypersonics.”
As General Paul Selva, vice chairman of the Joint Chiefs of Staff, told Congress in 2017, “It is very compelling when one looks at the capabilities that artificial intelligence can bring to the speed and accuracy of command and control and the capabilities that advanced robotics might bring to a complex battlespace, particularly machine-to-machine interaction in space and cyberspace, where speed is of the essence.”
Aside from aiming to exploit AI in the development of its own weaponry, US military officials are intensely aware that their principal adversaries are also pushing ahead in the weaponization of AI and robotics, seeking novel ways to overcome America’s advantages in conventional weaponry.
As the fighting intensifies, however, communications between headquarters and the front lines may well be lost and such systems will, according to military scenarios already being written, be on their own, empowered to take lethal action without further human intervention.
Advocates of the new technology claim that machines will indeed become smart enough to sort out such distinctions for themselves, while opponents insist that they will never prove capable of making critical distinctions of that sort in the heat of battle and would be unable to show compassion when appropriate.
However, strategists worry that, in a future hyperwar environment, such systems could be jammed or degraded just as the speed of the fighting begins to exceed the ability of commanders to receive battlefield reports, process the data, and dispatch timely orders.
As a report from the Congressional Research Service puts it, in the future “AI algorithms may provide commanders with viable courses of action based on real-time analysis of the battle-space, which would enable faster adaptation to unfolding events.”
Incoming data from battlefield information systems would instead be channeled to AI processors focused on assessing imminent threats and, given the time constraints involved, executing what they deemed the best options without human instructions.
Keep in mind, then, that the very nature of such a future AI-driven hyperwar will only increase the risk that conventional conflicts could cross a threshold that’s never been crossed before: an actual nuclear war between two nuclear states.
Such a danger arises from the convergence of multiple advances in technology: not just AI and robotics, but the development of conventional strike capabilities like hypersonic missiles capable of flying at five or more times the speed of sound, electromagnetic rail guns, and high-energy lasers.
Such weaponry, though non-nuclear, when combined with AI surveillance and target-identification systems, could even attack an enemy’s mobile retaliatory weapons and so threaten to eliminate its ability to launch a response to any nuclear attack.
scenario, any power might be inclined not to wait but to launch its nukes at the first sign of possible attack, or even, fearing loss of control in an uncertain, fast-paced engagement, delegate launch authority to its machines.
5 Ways Artificial Intelligence May Affect Health Care in the Near Future and What That Means for You
Concepts that were mere science fiction only a couple of decades ago --like artificial intelligence (AI) --are quickly becoming commonplace.
machine learning algorithms are more accurate and faster than ever;and the cloud and the internet of things have made it possible for even small devices to access artificial intellgence'senormous capabilities.
Instead of blindly following a checklist, AI digital consultation systems have learned from millions of real case files to ask questions that are relevant to the particular patient.
With computer vision technology, systems can be trained to look at x-rays or other scans and apply deep learning to understand what images show.
In November, for example, the University of Rochester Medical Center announced that it was using tech from Aidoc, an AI radiology company, to help identify and prioritize critical cases so that urgent-care patients could be seen by a radiologist first, giving those patients the best of both worlds: AI and a doctor together.
Personalized medicine today is kind of a utopian buzz term: a health care approach where diagnoses and treatments are highly tailored to meet the patient’s personal and family history as well as his or her specific risk factors and genetics.
There have been robot solutions for surgery for years, including the advanced da Vinci system, that allows surgeons to take control of precision robotic equipment to perform minimally invasive procedures.
The Smart Tissue Autonomous Robot (STAR) can already suture stitches that are cleaner and more accurate than what a human surgeon can do;and early tests show the technology can also accurately remove a tumor with less damage to the surrounding tissue.
Earlier this year, health care cybersecurity vendor CyberMDX discovered a vulnerability in a popular syringe pump that could allow an attacker to take over the device and administer lethal dosages of medication.
Advanced cybersecurity solutions could use machine learning to understand normal network behavior and identify and block any anomalous activities that could indicate vulnerabilities or attacks.
AI In 2019 According To Recent Surveys And Analysts' Predictions
Artificial Intelligence (AI) is the talk of the world and it features prominently in predictions for 2019 (see here and here) and recent surveys by consulting firms and other observers of the tech scene.
Here are the key findings: Consumer adoption: “Smart speakers” lead the way to the AI-infused home of the future Smart speakers (e.g., Amazon Echo and Google Home) will become the fastest-growing connected device category in history, with an installed base projected to surpass 250 million units by the end of 2019.
With sales of 164 million units at an average selling price of $43 per unit, total smart speakers’ revenues will reach $7 billion, up 63% from 2018.
(Deloitte) Enterprise adoption: Timid first steps 47% of business executives say their companies have embedded at least one AI capability in their business processes and just 21% say their organizations have embedded AI in several parts of the business.
By 2020, the penetration rate of enterprise software with AI built in, and cloud-based AI development services, will reach an estimated 87 and 83 percent respectively.
24% said their enterprise-wide AI efforts were being led by an AI “center of excellence.” (PwC) 58% of business say less than one-tenth of their companies’ digital budgets goes toward AI and 71% expect AI investments will increase in the coming years.
(PwC) The three most popular uses for AI and machine learning are to increase efficiencies or worker productivity (51%), to inform future business decisions (41%) and to streamline processes (39%).
(McKinsey) While 88% of senior leaders polled agree machine learning or AI help their businesses to be more competitive, only 56% of organizations are currently utilizing these emerging technologies.
69% of respondents believe that machine learning/AI technologies are having a positive impact within theirindustry and 39% believe their organizations are getting the most value out of AI and machine learning.
There is no doubt that AI skills are on the rise, but some typically human skills that today cannot be replicated by machines have been growing almost as fast and are here to stay.
(LinkedIn) While ML is the largest skill cited as a requirement, deep learning (DL) is growing at the fastest rate from 2015 to 2017 the number of job openings requiring DL increased 35x.
- On 27. februar 2021
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