Artificial intelligence and nuclear war have been fiction clichés for decades. Today’s AI is impressive to be sure, but specialized, and remains a far cry from computers that become self-aware and turn against their creators. At the same time, popular culture does not do justice to the threats that modern AI indeed presents, such as its potential to make nuclear war more likely even if it never exerts direct control over nuclear weapons.

Russian President Vladimir Putin recognized the military significance of AI when he declared in September that the country that leads in artificial intelligence will eventually rule the world. He may be the only leader to have put it so bluntly, but other world powers appear to be thinking similarly. Both China and the United States have announced ambitious efforts to harness AI for military applications, stoking fears of an incipient arms race.

In the same September speech, Putin said that AI comes with “colossal opportunities” as well as “threats that are difficult to predict.” The gravest of those threats may involve nuclear stability—as we describe in a new RAND publication that outlines a few of the ways in which stability could be strained.

Strategic stability exists when governments aren’t tempted to use nuclear threats or coercion against their adversaries. It involves more than just maintaining a credible ability to retaliate after an enemy attack. In addition to that deterrent, nuclear stability requires assurance and reassurance. When a nation extends a nuclear security guarantee to allies, the allies must be assured that nukes will be launched in their defense even if the nation extending the guarantee must put its own cities at risk. Adversaries need to be reassured that forces built up for deterrence and to protect allies will not be used without provocation. Deterrence, assurance, and reassurance are often at odds with each other, making nuclear stability difficult to maintain even when governments have no interest in attacking each other.

In a world where increasing numbers of rival states are nuclear-armed, the situation becomes almost unmanageable. In the 1970s, four of the five declared nuclear powers primarily targeted their weapons on the fifth, the Soviet Union (Beijing, after its 1969 border clashes with the Soviet Union, feared Moscow much more than Washington). It was a relatively simple bilateral stand-off between the Bolsheviks and their many adversaries. Today, nine nuclear powers are entangled in overlapping strategic rivalries—including Israel, which has not declared the nuclear arsenal that it is widely believed to possess. While the United States, the United Kingdom, and France still worry about Russia, they also fret about an increasingly potent China. Beijing’s rivals include not just the United States and Russia but India as well. India fears China too, but primarily frets about Pakistan. And everyone is worried about North Korea.

In such a complex and dynamic environment, teams of strategists are required to navigate conflict situations—to identify options and understand their ramifications. Could AI make this job easier? With AI now beating human professionals in the ancient Chinese strategy game Go, as well as in games of bluffing such as poker, countries may be tempted to build machines that could “sit” at the table amid nuclear conflicts and act as strategists.

Artificially intelligent machines may prove to be less error-prone than humans in many contexts. But for tasks such as navigating conflict situations, that moment is still far off in the future. Much effort must be expended before machines can—or should—be relied on for consistent performance of the extraordinary task of helping the world avoid nuclear war. Recent research suggests that it is surprisingly simple to trick an AI system into reaching incorrect conclusions when an adversary gets to control some of the inputs, such as how a vehicle is painted before it is photographed.

But AI could undermine the foundations of nuclear stability through means other than providing advice to strategists. Sensors and cameras are increasing in number throughout the world; AI’s growing ability to make predictions based on information from these disparate sources may cause nations to worry that the missiles and submarines they depend upon for assured retaliation will become vulnerable. During the Cold War, the superpowers sought crippling “first-strike” capabilities, but this was a perilous strategy—each superpower became convinced that the other might launch a disarming strike against it. With retaliation prevented, whoever struck first would gain a huge advantage. Thus the chances of accidental nuclear war were greatly increased. Such challenges are even more fraught in today’s world. More states are nuclear-armed—and AI technology might lend extra credibility to threats against nuclear retaliatory forces.

In the coming years, AI-enabled progress in tracking and targeting adversaries’ nuclear weapons could undermine the foundations of nuclear stability; that is, nations may question whether their missiles and submarines are vulnerable to a first strike. Will AI someday be able to guide strategy decisions about escalation or even launching nuclear weapons? Such capabilities are off in the distance for now, but the chance that they will eventually emerge is real—as is the need to understand, right now, how AI could reshape the world’s approach to nuclear stability.

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Day after day we read in our news media, and hear on the radio or TV, these two letters: “AI” meaning ARTIFICIAL INTELLIGENCE. What do we really know about AI?

Let’s begin with a dictionary definition:

AI is the theory and development of computer systems able to perform tasks that normally require human intelligence. It is exhibited by machines which mimic “cognitive” functions that humans associate with other human minds, i.e. making  machines behave in ways that would be called intelligent if a human were so behaving.

This leads to asking what is Human Intelligence (HI), the definition of which is very controversial. An op-ed statement in the Wall Street Journal appeared in a 1995 with 52 researchers agreeing to define HI as a very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience. It is not merely book learning, a narrow academic skill, or test-taking smarts. Rather, it reflects a broader and deeper capability for comprehending our surroundings — “catching on,” “making sense” of things, or “figuring out” what to do.

We all have been given IQ tests, purported to measure the level of our Intelligence; however, if we are to accept the above definition of HI it must be questioned if a machine with AI will ever actually comprehend its surroundings — “catch on,” “make sense” of things, or “figure out” what to do.

Today, much of routine technology such as optical character or face recognition is excluded from AI. Companies such as Google’s Deepmind are attempting to develop programs which can learn to solve any complex problem without needing to be taught how, but their engineers admit they are suffering from painfully slow progress. In contacting academia, I have been told the primary goal of IT is to produce a machine which is able to perform any intellectual task that a human can do.

This may be achieved when our present binary digital computers are replaced by super-efficient, super-fast computers using quantum bits instead of transistors. I do not truly understand the technology, so I must take this on faith! But if this goal is achieved, it would mean that a robot-soldier would react to a life-threatening situation in combat as a human soldier would react.

Members of academia have presented tests machines would need to pass in order to be classified as having human-level AI. Scientist Alan Turing’s test is one: A machine and a human both converse sight unseen with a second human, who must evaluate which of the two is the machine. If the human expressed strong anger or sadness, the machine would need to respond in kind. More recently in Tokyo, a research team is trying to create an AI program that has enough smarts to pass Japan’s most rigorous university entrance exams.

Computers already show superhuman performance at many tasks, however they are not called Intelligent. Fool’s gold seems to be gold, but isn’t; AI seems to be intelligent, but isn’t yet.

Yes, people should be concerned about the future of AI, however ARTIFICIAL INTELLlGENCE (AI) should not be used to describe self-driving vehicles and the many super-high-speed computing unintelligent machines of today!

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“Success in creating effective AI could be the biggest event in the history of our civilisation. Or the worst. We just don’t know,” said Professor Stephen Hawking at this week’s Web Summit in Lisbon.

Along with many benefits, said Hawking, artificial intelligence (AI) brings many “dangers, like powerful autonomous weapons, or new ways for the few to oppress the many”.

The physicist called for new regulation to ensure humanity could prevent AI from threatening its existence. 

“Perhaps we should all stop for a moment and focus not only on making our AI better and more successful, but also on the benefit of humanity,” he added.

Hawking is not the only luminary from the science and technology world to have warned about the future of AI.

We should all “be very careful about artificial intelligence”, Bill Gates said earlier this year. “If I had to guess at what our biggest existential threat is, it’s probably that. With artificial intelligence, we’re summoning the demon.”

In recent months, there have been headlines about killer robots and about automation replacing human workers, but also about algorithms that help diagnose cancer, and the successful development of self-driving cars.

“Some scholars argue it is the most pressing existential risk humanity might ever face, while others mostly dismiss the hypothesised danger as unfounded doom-mongering,” says Motherboard’s Phil Torres.

So should we be worried about the spread of AI? And what we can do about it?

The reaction to AI

A YouGov survey last year of more than 2,000 people found that public attitudes towards AI vary greatly depending on its application.

Some 70% of respondents were happy for intelligent machines to carry out seemingly menial jobs such as crop monitoring – but this fell to 49% when it came to household tasks, while only 23% would be happy for robots to perform medical operations. And a mere 17% were comfortable with the idea of so-called sex robots.

One of the primary worries about AI is its impersonal nature.

In August, Tesla and SpaceX CEO Elon Musk, along with 115 other AI and robotics specialists, signed an open letter urging the UN to recognise the dangers of lethal autonomous weapons and to ban their use internationally.

According to the Human Rights Watch organisation, the US, China, Israel, South Korea, Russia and the UK “have been investing in developing weapons systems with decreasing levels of human control in the critical functions of selecting and engaging targets”.

Steven Finlay, author of Artificial Intelligence and Machine Learning for Business, believes that autonomous armed robots that can track and target people, using facial recognition software, are just around the corner.

AI and robotics are advancing so quickly that within years, wars could be fought with autonomous weapons and vehicles, reports The Guardian.

Regulate or exterminate?

AI regulation is one answer to the problem.

“A healthy modern democracy requires ordinary citizens to participate in public discussions about rapidly advancing technologies. We desperately need new policies, regulations, and safety nets for those displaced by machines,” says The Nation’s Katharine Dempsey.

Elon Musk agrees. Back in 2014, he said: “I’m increasingly inclined to think that there should be some regulatory oversight, maybe at the national and international level, just to make sure that we don’t do something very foolish.”

Arguably, the greatest worry is that machines may become better at making decisions than humans, enslaving humanity to automated decision-makers and whoever controls them.

AI-based systems are already replacing many jobs. For example, some AI machines can spot skin cancer as accurately as a human doctor, Wired reports.

Many of our choices are already influenced by AI, via websites such as Amazon and Facebook. Algorithms determine the content we see online, and make recommendations about everything from what we watch on TV and where we eat to who we date.

“What makes this scenario so dangerous is that it isn’t being planned by some overarching master intelligence or machine overlord,” says Steven Finlay. “We are creating the very technology that could lead to our demise.”

A change for the better?

It’s not all doom and gloom.

“I’m optimistic that we can create an inspiring future with AI if we win the race between the growing power of AI and the growing wisdom with which we manage it, but that’s going to require planning and work,” physicist Max Tegmark, author of Life 3.0: Being Human in the Age of Artificial Intelligence, told Motherboard.

While Tegmark advocates regulation, he argues that there also needs to be a focus on the upside to using AI. “If people just focus on the downsides, they get paralysed by fear and society gets polarised and fractured,” he concludes.

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The risks and rewards of machine learning and artificial intelligence (AI) are topics of discussions in nearly every industry circle. Whether it’s the promise of cars that not only drive themselves but collectively learn how to drive more safely or the looming threat of apocalyptic war driven by the race for AI supremacy, AI is clearly dominating rhetoric around the heart of man-and-machine interactions.

However, no technology evolves in a vacuum, and it’s always valuable to evaluate the driving factors leading to widespread change. In the case of AI adoption and deployment, we should remember that other factors are both enabling and driving the change we see today. Like every other technical revolution, the use of AI technology is becoming more prominent because not only is the technology there to support it, but it is clearly an idea whose time has come.

Simply put, machine learning and AI, in general, will become commonplace in our lives because we need them to be. There is simply too much information, moving too quickly, for humans to process and understand. We are already data rich and information poor. And that trend is clearly set to accelerate as the digitalization of industries and life in general proceeds at a breakneck pace. AI offers the promise of handling all that information for us and extracting insights that we would never have the time or capacity to see for ourselves.

Alongside development of the capability to process massive amounts of data in innovative ways, there exists another technical revolution whose time has also most definitely come — the internet of things (IoT). In fact, I strongly believe that these two foundational changes in the way we use information technology are tightly coupled, perhaps far more tightly than is readily apparent today.

If AI offers the promise of processing immense quantities of data in ways that we can’t, then IoT provides the very tangible mechanism for generating that raw data in ways we might not expect. The deep integration of smart devices in our society, our workplaces and our bodies will not only create business and social insight, it will offer the understanding of complex behaviors in ways that quite possibly only AI machines will be able to comprehend.

There’s little doubt that businesses are already seeing the impact of the first wave of AI and machine learning. Perhaps more telling, there is already an emerging trend of AI development “following the data” in order to accelerate the capability to deliver human-machine interactions and insight based on the availability of more of those very same interactions.

However, it’s IoT that could really deliver the data in sufficient volume to both power and drive the promise of AI — with traffic volumes already climbing into the zettabyte range.

We stand on the brink of fruition of two technical revolutions that are, in reality, one and the same. And the two halves of this revolution will feed one another: The more information IoT can provide, the more quickly AI will develop and the greater its potential impact. The more AI advances, the more value it provides in the capacity to process information. This will drive a desire to gather more and more information about more of the world and therefore open the opportunity for IoT to become even more pervasive and valuable in its role as data collector. For organizations, governments and societies that can harness this virtuous spiral, there is almost unlimited opportunity — the possibility to gain greater insight into everything from global weather patterns to treatment of infectious diseases to building hyper-efficient cities.

Information is the lifeline of businesses and the currency of the future, and the capacity to handle that information (to gather it and process it) will be what creates the new mega-enterprises of the next two decades. Business leaders who have the ability and courage to bring together the power of IoT and AI to chart a course for their organizations will have the power to leave their competition in the dust and to dominate new areas of industry even before their competitors know the opportunity exists.

The way we think about and use technology is going to change, and it will change in ways that very well may not be definable today. The pace of digitalization is accelerating and will continue to do so, driven by the speed of business and the power of information. We are reaching a tipping point at which the twin revolutions of AI and IoT will fuse to become a data surge that will shape the next century and beyond. The future, as it so often does, belongs to the bold — and it is arriving very quickly.

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Every single day, millions of dollars are being spent in call centres simply to answer repeated questions, thousands of times over and over again. Let us see how AI is going to affect IT service management.

In this age of artificial intelligence, managers at all levels need to accept that a significant chunk of their jobs might be done better and more efficiently by machines. Researchers conducted surveys and found that managers at all levels spend bulk of their time in administrative tasks, such as making schedules or writing reports. These are the very tasks that are most likely to be automated in the near future. In fact, some companies have already made improvements by transitioning these tasks to AI.

It was found that managers need to have the skill of judgement to succeed at work in this age of automation, which includes thinking creatively, data analysis, data interpretation, and developing strategy. Other skills that stood out as most important are social networking, coaching, and collaboration. These are the skills which will help managers stand out when AI take over the administrative tasks that managers perform today. Machines would never completely replace managers but they would give managers more time. So, the real priority for managers should be refocussing on the tasks that only humans can do using their creativity, collaborating attitude, empathising nature, and the power of judgement.

Machine v/s human

AI is very good at eliminating human error. Humans, many a times tend to deviate from standard defined processes which results in fatalities. Examples could be in various areas — a critical patient operated upon by a team of doctors may die because of a minor human error or pilots who have to take care of thousands of computations while the plane is flying, may cause the plane to crash. In such situations, a trained intelligent bot can take decisions which are as close to defined standards.

Let us try to understand why automation is being considered a threat to future jobs. It began with basic automation, wherein a particular manual task was programmed to be done by machine.The task when done by machine was completed faster and without any human error of course. This led to more automation of such menial tasks which resulted in improved efficiency; hence, the productivity of the entire organisation grew multi-fold.

Now with the evolution of technologies like artificial intelligence, machine learning and deep learning, machines can actually learn on their own and be taught to do more complicated tasks which are currently being done by humans.

IT Customer Support is one such domain wherein we can have intelligence bots well-trained with large sample datasets, who know how to respond to every kind of customer query or ticket. These bots are intuitive enough to adapt and improve themselves without human intervention. They become better with time.

Understanding IT service management (ITSM)

IT Service Management, also called ITSM, is the term used to refer to the implementation, managing and delivering of quality IT services in the best possible way to meet the needs of a business.

It ensures an appropriate mix of people, processes and technology are in place to provide value to a business. Essentially, ITSM is about value- it is about taking your resources, your capabilities and making something valuable for your business.

ccording to reports, global outsourced customer services market is projected to reach $84.7 billion by 2020. Another study, revealed that companies lose more than $62 billion due to poor customer service. Obviously, no company can afford to provide a not so good customer support.

Why AI is required in customer service

Every single day, millions of dollars are being spent in call centres simply to answer repeated questions, thousands of times over and over again. In other words, providing customer support is really an expensive task. A study on customer support market found the following:

1. Around 270 billion phone calls were made annually to call centres which cost around $600 billion.
2. One out of two incoming calls require escalation or go unresolved.
3. 61 percent of all calls could have been resolved with better access to information.

Entities involved in customer service

A customer support service has various entities involved and let us understand how AI is going to affect each one of them:

1. Agent: AI is going to recommend solutions, recommend classifications, help agent understand what the issue is, thereby making the agent smarter and provide the best reply to customer.
2. Customer: AI can deflect cases by answering questions such as what can be done on the website to help customers find the better solution. It can suggest how we can push the solution faster to the customer. AI clubbed together with chatbots helps in responding to customers queries faster and more accurately based on data analysis in real time.
3. Operations: With AI one can predict the close time of a customer issue, one can actually allocate the case to someone knowledgeable in that specific topic.

What AI has brought to customer service business

Following are some of the areas where artificial intelligence has proved to be very efficient: :

1. Increased customer satisfaction
2. Customer attrition reduction
3. Customer effort reduction
4. Higher customer service satisfaction level by agent
5. Reduced agent on-boarding time
6. Reduced cost per ticket
7. Improved business outcome
8. Reduced costs of service operations
9. Increased revenue

Companies improving customer service by using artificial intelligence

Let us take a look at a few startups working in automating the customer service process at various levels:

1. Neva.ai: Automates customer service and support using artificial intelligence and natural language processing
2. DigitalGenius: Brings practical applications of deep learning and artificial intelligence to customer service operations of large companies
3. IPSoft: Assists with service desk support, helps field engineers troubleshoot, and supports procurement
4. Next IT: Assists with customer service
5. Digital Reasoning: Scans up to billions of communications from thousands of traders to spot language patterns and identifies potentially fraudulent activity
6. Luminoso: Analyses customer feedback to propose product design changes; reviews how consumers feel about food items or grocery store experience

What future holds for ITSM

Artificial Intelligence is currently in a very early stage and has a long way to go for replacing human task force, but yes, it is moving steadily towards this and making huge progress across multiple domains.

Someone who is concerned about his/her career should start learning skills which would not get affected by automation. This involves the usage of human empathy — sensing the emotions of others — and the ability to think rationally and then come up with algorithms to solve problems.

We can sum up by saying that artificial intelligence is powerful but it is still artificial and does not have the natural powers that humans possess.

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