Article by: Suman Nambiar, Head of AI Practice at Mindtree

The range of technologies that comprise artificial intelligence (AI), including natural language processing-driven bots, machine learning (ML) and deep learning, along with robotic process automation (RPA), are changing the ways in which business is done across a number of industries, from insurance, to legal and financial services, through to retail, travel, hospitality and transportation.

The impact of AI on these particular industries is hard to overstate. What we are seeing here across the board is far more than a trend. These technologies are revolutionising and re-inventing these industries in ways that go far beyond just automation – they are speeding up and reshaping existing business processes, while enabling new ones that were not possible earlier. Similarly, as some job roles disappear, many others will be created to help train, explain and sustain these algorithm-driven business processes.

Rarely a day goes by without a new story hitting the headlines relating to the impact that AI is having on specific industries or particular businesses. The range of opinions, from hype and excitement about the technology’s possibilities, to fear and apprehension about its negative impact on society, is evidence that AI is fast becoming one of the most misunderstood technologies of our time.

AI boosts efficiency in the legal profession

A recent story suggested that British legal firms can improve their efficiency by 50% by using the latest AI technologies available on the market. This bold proposition was made by a virtual data room provider called Drooms, who say that the legal sector has been considerably slower than many others in terms of adopting new methods of automating business processes, due to its conservative nature and inherent scepticism. While the hype around AI can be deafening at times, this often obscures the fact that enterprises are seeing real benefits from using these technologies, which are maturing rapidly.

As the area of Language Comprehension and Idea Learning progresses, driven by advances in deep learning, we see increasing potential for using AI in the legal industry. AI can help identify risks in contracts; flag up compliance issues across complex contracts; enable much quicker, more intelligent search of documents based on concepts rather than keywords or strings and even estimate the probability of legal actions succeeding or failing. A lot of these technologies are already out there – legal firms who experiment and adopt these ahead of the curve will see benefits in productivity and speed that outstrip their peer group.

Where threats to hourly billing models are concerned, firms that use these tools to improve the quality of advice and service to their clients are more likely to see the benefits in greater client loyalty. Furthermore, they will be in the best position to take advantage of the new kinds of jobs that the advent of AI will throw up, where clients will need expert advice to help them understand issues like agency, accountability, fairness and decision making in an algorithm-driven world.”

From business efficiencies to more exciting, personalised retail and travel experiences
The rapid growth and business adoption of AI is transforming lives and businesses globally, by helping companies to automate previously routine and monotonous tasks and by offering consumers a choice of much-improved, personalised experiences and services across the world.

When it comes to industries such as retail and travel, for example, it’s vital that businesses adopt the latest technologies to recognise and respond to the needs, wants and desires of their consumers. That’s why retailers and travel companies have been ahead of the curve over the last decade when it came to web and mobile e-commerce innovation. Amazon, AirBnB and Uber have completely changed the nature, perception of and consumer expectations around retail, hospitality and transportation.

While these companies have been using AI at the heart of their business for a while now,
other retailers and travel companies are discovering how to harness it to predict consumer preferences, to personalise services and stores, to complete bookings and sales and to address even unstated customer service needs.

In travel, for example, there are a number of opportunities for AI to help improve the customer experience. Firstly, biometrics and facial recognition technologies can remove the time-consuming need for documents to be checked at regular steps of a journey. Secondly, machine learning models can help predict consumer preferences at a granular level, enabling enterprises to construct a ‘360-degree view’ of the consumer in real-time, which then enables them to create hyper-personalised product and service offerings. The impact on conversion rates and customer loyalty can be transformational for the enterprise that implements these. Next, conversational apps and voice-driven virtual assistants are offering time-poor travellers a more personalised way to interact with organisations, to make bookings or to get specific information to meet a need in a particular time and place.

There are many more opportunities – automated social media analysing tools can provide travel companies with real-time insight into how their customers are feeling in a given situation and help companies to offer instant solutions to any problems their customers might be facing due to traffic problems, flight cancellations or one of the many other variables that can cause travel issues. And of course, predictive machine learning algorithms are transforming demand planning, operations, marketing and back-office operations across the entire enterprise.

How Big Data and AI are transforming financial services and insurance

It’s easy for modern consumers, travellers or holidaymakers to see and understand these latest AI-led developments in travel and retail, but what about in other industries. How, for example, is AI changing financial services and insurance?

The phenomenon of digitalisation, the spread of the Internet and particularly mobile computing over the past 20 years has resulted in the availability of enormous amounts of data, particularly in the financial and insurance domains, which is feeding the AI revolution.
It is almost impossible for humans to navigate this immense bank of data, let alone try to draw any meaningful insights from, or patterns in the data and that is exactly where AI comes in. Insurance companies, banks and financial services businesses are increasingly turning to automation, AI and machine learning-powered predictive analytics tools that use self-learning algorithms to continuously evolve with new data points and user analysis.

A great example here is Mindtree’s recent partnership with Tookitaki, a predictive analytics platform that demonstrably assists banks and financial services companies help businesses to make better decisions, faster and more efficiently. This particular partnership is enabling customers to save millions in security alerts and reconciliation management.

The insurance industry has also been cautious about adopting these technologies, but there is increasing awareness of the areas in which AI can make an immediate impact to the business. We see increasing adoption by insurers across different technologies, including robotic process automation (RPA), chatbots and personal/virtual assistants, machine learning, deep learning and natural language processing (NLP).

These technologies are helping insurers learn more about gaps in customer needs, in addition to cutting the costs to the customer and servicing their personal needs and requirements better than ever before. For example, Mindtree’s own conversational chatbot, MACAW, helps to provide quotes for life insurance products using Skype messenger and we have also developed a highly advanced ‘sales bot’ for use in the automobile insurance industry.

We’re also exploring the use of deep learning-driven computer vision algorithms, from areas like ‘reading’ forms with combinations of printed and handwritten text for faster forms processing, to assessing and rating automobile damages automatically based on submitted images for faster claims processing.

Machine learning models for fraud detection have of course been in operation for quite a few years; now they are also incorporating the ability to ingest unstructured data such as social media feeds to create more accurate predictive models.

As we’ve seen, the use of AI technologies is a reality today across different industries and enterprises. It is helping companies predict better, make better and faster decisions, serve their customers better with more personalised products and services, make routine processes faster and more efficient and unlock value in ways that were not possible before. It’s time to start using these in your business as well.

source: http://www.intelligentcio.com/eu/2018/06/25/data-and-artificial-intelligence-for-innovation-and-transformation/

The US and China are leagues ahead of any other country when it comes to AI technology. And it’s because they know how to prioritize their own programs. Rather than waste time discussing the dangers of AI with the UN, or crafting global policy, the two countries have become AI nationalists.

Artificial intelligence research was a dying field just a decade ago. Now, AI companies like Google and Baidu are among the richest in the world. Fortunes have changed for the industry, thanks in no small part to a political environment treating AI research like general purpose software development.

This environment has allowed Google and Facebook, for example, to become global leaders in AI development – and a couple of the richest companies on the planet. Unfortunately it’s also a climate in which a company like Cambridge Analytica can exploit big data with, seemingly, few repercussions. Let’s not forget Google, Microsoft, and Amazon have all come under fire lately for helping the government develop projects that employees consider unethical.

Because the US ignores globalist calls to discuss international AI policy, and has none of its own, we’re left to trust that big tech companies and the federal government have our best interests at heart and will hold themselves accountable without laws or policies.

When US Congress members questioned Facebook CEO Mark Zuckerberg over the Cambridge Analytica data scandal, several showed they didn’t fully understand what had happened. And that’s a problem, because it makes it seem like the lack of policy comes from a place of ignorance.

AI expert Ian Hogarth says:

If a disproportionate amount of those people can be found in the US, and politicians still can’t be bothered to come up with common-sense policies governing the development of AI, there’s little hope they will until they’re reacting to something bad.

In China, the government has a different – but equally nationalist – approach: the nation’s people exist in a near-total surveillance state. Algorithms determine who can use public transportation or purchase goods. Facial recognition cameras are used throughout the nation’s cities, including by police wearing special glasses. China, like the US, shows no apparent interest in developing global AI policies.

Unlike the US, however, the Chinese government is deeply involved in AI development and works with the country’s largest technology companies to develop local and global strategies for machine learning research and development. China dedicates billions to AI development and encourages companies to contribute to a state data library, among many other internal initiatives. It recognizes that it’s trailing the US – but the gap is closing.

Andrew Moore, Dean of Computer Science at Carnegie Mellon, says half of the papers submitted to big AI conferences come from China. A decade ago it was just five percent. And, globally, according to Hogarth, China was responsible for 48 percent of all AI startup funding last year.

Hogarth predicts AI nationalism is going to create global instability, he says “AI policy will become the single most important area of government policy.” His concern is that the US and China will effectively form a duopoly which will force other countries to either pick sides and choose a sponsoring parent-country, or band together in a sort of rag-tag group of spunky underdogs.

AI nationalism, for the US and China, seems to be paying off in the short term. But it seems irresponsible to assume there’ll be no consequences to developing cutting-edge AI without policies and development guidelines specific to that technology.

BEIJING — Anhui Provincial Hospital became China’s first intelligent hospital in August, using artificial intelligence-enabled systems to help doctors with medical diagnoses and treatment.

Four months later, the hospital, in Hefei, Anhui’s provincial capital, was renamed the First Affiliated Hospital of University of Science and Technology of China.

Yan Guang, the hospital’s deputy head and the man in charge of its intelligent transformation, said that when it launched an AI-enabled smartphone application in 2016, doctors and nurses were keen to use it.

Developed by iFlytek, an AI company based in Hefei, the system uses speech-recognition technology to type up medical records and image-recognition technology to help doctors read medical images.

“The users of the app, which is a tailored edition for the hospital, soon reached a satisfying number,” Yan said. “Then we found there were also nurses among the users, while the system was designed to serve doctors.

“Nice numbers are definitely not all we want. It is the doctors using the app who can help the system improve.”

He said he subsequently had to limit use of the app among nurses.

Doctors said the AI-enabled systems have made their work more effective and efficient, although there are still some problems to overcome.

Qi Yinbao said that in his first four years as a neurosurgeon at the hospital, beginning in 2013, he had to spend much of his time writing up patients’ medical records every day.

“I usually wrote them between surgeries, and very often would stay in the office after working hours to finish them,” he said. “Sometimes I found I forgot some important information and needed to go through all the print records of examination results to refresh my memory.”

With the app developed by iFlytek, Qi and the hospital’s more than 1,300 doctors now have speech-recognition technology to help them record their diagnoses.

Special dictionary

To open the app, Qi can log in with either a fingerprint or a combination of face and voice recognition. He then just speaks into his smartphone and the app types up the information precisely.

Because doctors use many professional medical terms, iFlytek engineers said they built a special dictionary to make speech recognition more precise.

“The system also features deep learning technology, which means the more doctors use the system, the more precise the results will be,” said Lu Xiaoliang, deputy general manager of iFlytek’s intelligent healthcare business.

Some senior medical specialists found typing up records on a computer tedious, so the hospital previously had to arrange an assistant for each of them.

“With AI technology, the senior experts can now also work alone well, saving a lot of human resources for the hospital,” Yan said.

Qi said the speech-recognition technology could help dentists even more, as they were not able to spare a hand to write up records when working on patients’ teeth.

“They just need to keep the speech-recognition function working,” Qi said.

The function also works on a computer with a microphone, but it keeps typing as Qi keeps speaking, even though some of the things he says have nothing to do with his diagnosis, and he needs to delete them when he ends the recording.

That could prevent a dentist from chatting with a patient to relieve their anxiety, because there would be too much information to delete afterward.

The results of certain examinations of patients are automatically entered into the app, allowing Qi to check them anytime, anywhere.

“In the past, before making ward rounds to the patients’ rooms, we were first offered many print records and then asked the patients about their health conditions and took notes before returning to the office to type on computer-based systems”, Qi said.

But part of the preparatory work can now be done ahead of time, even when a doctor is on a bus or subway train.

Yan said a more important feature of the system is that it can help doctors read medical images to speed up diagnosis and prevent misdiagnosis.

Take CT scans for example. A doctor could spend minutes reading a CT case, which usually consists of many－sometimes hundreds－of images, before making an initial diagnosis, but Lu said it takes less than a second for the AI system to do the same thing.

“Best of all, the system won’t get tired,” he said.

The AI-enabled system has helped interpret thousands of CT images, Lu said, and the accuracy for detection of lung nodules, one of the indicators of potential lung cancer, has reached 99.4 per cent.

To build the intelligent hospital, Yan said several AI-enabled systems have been launched since 2016 in co-operation with iFlytek and other firms, including internet giants Alibaba and Tencent.

“None of the systems can work perfectly, but in the long run they will improve over time,” he said. “The medical sector will inevitably become more intelligent, and we cannot miss the chance to lead the trend.”

The hospital has not paid iFlytek a penny since they began co-operating in 2016.

“They don’t need to,” said Chen Liang, an iFlytek employee who leads a team of more than 10 engineers working in the hospital. “It will be by learning from the hospital what they really need that we can develop better systems.”

Yan is prudent when discussing the potential of AI-enabled systems, but they are already helping to guide patients around the hospital and allowing it to link up with hospitals around the province.

Another example is work on an intelligent emergency medical system.

“Once you call the emergency centre for first aid, your health information, based on all of your hospital records, will be provided to the first-aid personnel in the ambulance and doctors at the hospital,” said Yan, who was in charge of the hospital’s emergency medical centre from 2004 to 2007.

All the necessary advice on tailored first-aid solutions will be given to the medical personnel through the AI technology and they will see the advice via a smartphone app, he said.

The hospital has invested millions of yuan in the project, just dealing with its own medical records, and Yan said expanding the practice will require more effort.

The provincial authorities have launched a plan to build personal healthcare profiles, which can be shared between hospitals, for every citizen, and the project is progressing well, he said.

Intelligent healthcare is becoming a trend in hospitals. Hefei has also established a municipal-level intelligent hospital and the provincial authorities plan to set up six more at the provincial level and at least 15 at the municipal level this year.

First standard

Gao Junwen, deputy head of the Anhui Provincial Health Commission, said there must be some standards hospitals can refer to.

To build an intelligent hospital, the USTC hospital released its own 47 pages of standards, which won recognition from the provincial authorities. “It is the country’s first official standard for intelligent hospitals, and the national standard is expected to be drawn up using this one as an important reference,” Gao said.

Yan said there should be standards for different levels of intelligent hospital. “A county level intelligent hospital can by no means be built with a standard for a provincial-level one,” he said.

A recent article in the journal Chinese Digital Medicine, which is published by the National Health Commission, said there are still some technical difficulties to overcome in applying speech-recognition technology in diagnosis and treatment.

Written by a team of doctors from the General Hospital of the Guangzhou Command of the People’s Liberation Army, the article said background noise and doctors’ accents could affect the accuracy of the recognition process.

Speaking about a patient’s health conditions in an office shared by several doctors also failed to protect the patient’s privacy, it said, adding that solving the problem requires more investment to rearrange doctors’ offices by, for example, giving them more private space.

As the intelligent healthcare business heats up, Lu said competition between companies is getting fiercer.

“Some of the firms act as if they can change the world overnight, while we believe making healthcare intelligent still needs great efforts to improve technology,” Lu said.

“In the past, say about two years ago, some medical experts were too cautious about the business while some others’ opinions on it were too negative.

“Nowadays, their understanding of the business is getting more rational－the current technologies are not perfect but they can be improved.”

He said the business is very reliant on government support, because the authorities are always very cautious about the healthcare sector.

The Terminator was written to frighten us; WALL-E was written to make us cry. Robots can’t do the terrifying or heartbreaking things we see in movies, but still the question lingers: What if they could?

Granted, the technology we have today isn’t anywhere near sophisticated enough to do any of that. But people keep asking. At the heart of those discussions lies the question: can machines become conscious? Could they even develop — or be programmed to contain — a soul? At the very least, could an algorithm contain something resembling a soul?

The answers to these questions depend entirely on how you define these things. So far, we haven’t found satisfactory definitions in the 70 years since artificial intelligence first emerged as an academic pursuit.

Take, for example, an article recently published on BBC, which tried to grapple with the idea of artificial intelligence with a soul. The authors defined what it means to have an immortal soul in a way that steered the conversation almost immediately away from the realm of theology. That is, of course, just fine, since it seems unlikely that an old robed man in the sky reached down to breath life into Cortana. But it doesn’t answer the central question — could artificial intelligence ever be more than a mindless tool?

Victor Tangermann, The Birth of Alexa, Photoshop, 2018

That BBC article set out the terms — that an AI system that acts as though it has a soul will be determined by the beholder. For the religious and spiritual among us, a sufficiently-advanced algorithm may seem to present a soul. Those people may treat it as such, since they will view the AI system’s intelligence, emotional expression, behavior, and perhaps even a belief in a god as signs of an internal something that could be defined as a soul.

As a result, machines containing some sort of artificial intelligence could simultaneously be seen as an entity or a research tool, depending on who you ask. Like with so many things, much of the debate over what would make a machine conscious comes down to what of ourselves we project onto the algorithms.

“I’m less interested in programming computers than in nurturing little proto-entities,” Nancy Fulda, a computer scientist at Brigham Young University, told Futurism. “It’s the discovery of patterns, the emergence of unique behaviors, that first drew me to computer science. And it’s the reason I’m still here.”

Fulda has trained AI algorithms to understand contextual language and is working to build a robotic theory of mind, a version of the principle in human (and some animal) psychology that lets us recognize others as beings with their own thoughts and intentions. But, you know, for robots.

“As to whether a computer could ever harbor a divinely created soul: I wouldn’t dare to speculate,” added Fulda.

There are two main problems that need resolving. The first is one of semantics: it is very hard to define what it truly means to be conscious or sentient, or what it might mean to have a soul or soul-function, as that BBC article describes it.

The second problem is one of technological advancement. Compared to the technology that would be required to create artificial sentience — whatever it may look like or however we may choose to define it — even our most advanced engineers are still huddled in caves, rubbing sticks together to make a fire and cook some woolly mammoth steaks.

At a panel last year, biologist and engineer Christof Koch squared off with David Chalmers, a cognitive scientist, over what it means to be conscious. The conversation bounced between speculative thought experiments regarding machines and zombies (defined as those who act indistinguishably from people but lack an internal mind). It frequently veered away from things that can be conclusively proven with scientific evidence. Chalmers argued that a machine, one more advanced than we have today, could become conscious, but Koch disagreed, based on the current state of neuroscience and artificial intelligence technology.

Neuroscience literature considers consciousness a narrative constructed by our brains that incorporates our senses, how we perceive the world, and our actions. But even within that definition, neuroscientists struggle to define why we are conscious and how best to define it in terms of neural activity. And for the religious, is this consciousness the same as that which would be granted by having a soul? And this doesn’t even approach the subject of technology.

“AI people are routinely confusing soul with mind or, more specifically, with the capacity to produce complicated patterns of behavior,” Ondřej Beran, a philosopher and ethicist at University of Pardubice, told Futurism.

“AI people are routinely confusing soul with mind”

“The role that the concept of soul plays in our culture is intertwined with contexts in which we say that someone’s soul is noble or depraved,” Beran added — that is, it comes with a value judgment. “[In] my opinion what is needed is not a breakthrough in AI science or engineering, but rather a general conceptual shift. A shift in the sensitivities and the imagination with which people use their language in relating to each other.”

Beran gave the example of works of art generated by artificial intelligence. Often, these works are presented for fun. But when we call something that an algorithm creates “art,” we often fail to consider whether the algorithm has merely generated sort of image or melody or created something that is meaningful — not just to an audience, but to itself. Of course, human-created art often fails to reach that second group as well. “It is very unclear what it would mean at all that something has significance for an artificial intelligence,” Beran added.

So would a machine achieve sentience when it is able to internally ponder rather than mindlessly churn inputs and outputs? Or is would it truly need that internal something before we as a society consider machines to be conscious? Again, the answer is muddled by the way we choose to approach the question and the specific definitions at which we arrive.

“I believe that a soul is not something like a substance,” Vladimir Havlík, a philosopher at the Czech Academy of Sciences who has sought to define AI from an evolutionary perspective, told Futurism. “We can say that it is something like a coherent identity, which is constituted permanently during the flow of time and what represents a man,” he added.

Havlík suggested that rather than worrying about the theological aspect of a soul, we could define a soul as a sort of internal character that stands the test of time. And in that sense, he sees no reason why a machine or artificial intelligence system couldn’t develop a character — it just depends on the algorithm itself. In Havlík’s view, character emerges from consciousness, so the AI systems that develop such a character would need to be based on sufficiently advanced technology that they can make and reflect on decisions in a way that compares past outcomes with future expectations, much like how humans learn about the world.

But the question of whether we can build a souled or conscious machine only matters to those who consider such distinctions important. At its core, artificial intelligence is a tool. Even more sophisticated algorithms that may skirt the line and present as conscious entities are recreations of conscious beings, not a new species of thinking, self-aware creatures.

“My approach to AI is essentially pragmatic,” Peter Vamplew, an engineer at Federation University, told Futurism. “To me it doesn’t matter whether an AI system has real intelligence, or real emotions and empathy. All that matters is that it behaves in a manner that makes it beneficial to human society.”

“To me it doesn’t matter whether an AI system has real intelligence… All that matters is that it behaves in a manner that makes it beneficial to human society.”

To Vamplew, the question of whether a machine can have a soul or not is only meaningful when you believe in souls as a concept. He does not, so it is not. He feels that machines may someday be able to recreate convincing emotional responses and act as though they are human but sees no reason to introduce theology into the mix.

And he’s not the one who feels true consciousness is impossible in machines. “I am very critical of the idea of artificial consciousness,” Bernardo Kastrup, a philosopher and AI researcher, told Futurism. “I think it’s nonsense. Artificial intelligence, on the other hand, is the future.”

Kastrup recently wrote an article for Scientific American in which he lays out his argument that consciousness is a fundamental aspect of the natural universe, and that people tap into dissociated fragments of consciousness to become distinct individuals. He clarified that he believes that even a general AI — the name given to the sort of all-encompassing AI that we see in science fiction — may someday come to be, but that even such an AI system could never have private, conscious inner thoughts as humans do.

“Siri, unfortunately, is ridiculous at best. And, what’s more important, we still relate to her as such,” said Beran.

Even more unfortunate, there’s a growing suspicion that our approach to developing advanced artificial intelligence could soon hit a wall. An article published last week in The New York Times cited multiple engineers who are growing increasingly skeptical that our machine learning, even deep learning technologies will continue to grow as they have in recent years.

I hate to be a stick in the mud. I truly do. But even if we solve the semantic debate over what it means to be conscious, to be sentient, to have a soul, we may forever lack the technology that would bring an algorithm to that point.

But when artificial intelligence first started, no one could have predicted the things it can do today. Sure, people imagined robot helpers à la the Jetsons or advanced transportation à la Epcot, but they didn’t know the tangible steps that would get us there. And today, we don’t know the tangible steps that will get us to machines that are emotionally intelligent, sensitive, thoughtful, and genuinely introspective.

By no means does that render the task impossible — we just don’t know how to get there yet. And the fact that we haven’t settled the debate over where to actually place the finish line makes it all the more difficult.

“We still have a long way to go,” says Fulda. She suggests that the answer won’t be piecing together algorithms, as we often do to solve complex problems with artificial intelligence.

“You can’t solve one piece of humanity at a time,” Fulda says. “It’s a gestalt experience.” For example, she argues that we can’t understand cognition without understanding perception and locomotion. We can’t accurately model speech without knowing how to model empathy and social awareness. Trying to put these pieces together in a machine one at a time, Fulda says, is like recreating the Mona Lisa “by dumping the right amounts of paint into a can.”

Whether or not the masterpiece is out there, waiting to be painted, remains to be determined. But if it is, researchers like Fulda are vying to be the one to brush the strokes. Technology will march onward, so long as we continue to seek answers to questions like these. But as we compose new code that will make machines do things tomorrow that we couldn’t imagine yesterday, we still need to sort out where we want it all to lead.

Will we be da Vinci, painting a self-amused woman who will be admired for centuries, or will we be Uranus, creating gods who will overthrow us? Right now, AI will do exactly what we tell AI to do, for better or worse. But if we move towards algorithms that begin to, at the very least, present as sentient, we must figure out what that means.

source: https://futurism.com/artificial-consciousness/