In July 2016, Georgia Tech professor Ashok Goel hired Jill Watson, a teaching assistant for the spring semester. Jill was great at online student interactions, answering questions and was nominated as an outstanding assistant by students. The difference between Jill and other assistants? Jill is a chatbot. Her DNA is based on an open source platform (with pre-fed customized data) developed specifically to handle an enormous amount of students posts on the forum. And thus began an interesting new phase in one of the most respected sectors in the world – the education sector.

In India too, personalized digital learning platforms, new learning models delivering customized knowledge and flipped classrooms are finally dismantling the “one size fits all” approach towards student learning and education. Learning is becoming immersive (inside and outside the classroom); spurring creativity, critical thinking and meaningful real-world experiences.

Technological disruption is revitalising the education industry, enabling both students and teachers to strengthen their skills and knowledge to adapt to the new requirements of a 21st-century work force. These are exciting times to be an educator and a student.

But, the growth is disparate and still rudimentary. Understandably so for a country like ours with widespread geographical, cultural, gender and financial differences. Coupled with limited infrastructure, the dream of a truly literate India has a long time coming. There is a wide gap between expectations and reality both in terms of physical infrastructure and technological adoption.

While the government and academia work on improving the former, the latter has the power to really turn things around. What it needs in that endeavour is a solid data led backbone. Educational institutions today hold large amounts of data collected from online applications, classroom exercises/testing and student surveys. Social media too provides a rich source of information to capture student learning styles, preferences, concerns, reactions and perceptions.

This unstructured but valuable resource can be effectively analysed for insights to boost student achievement, increase faculty and staff productivity and improve operational effectiveness via better financial management and streamlined operations.

On a student level, the right utilisation of data sets will provide educators with real-time feedback on students’ performances, strengths and weaknesses. Data analytics can track student learning curves based on learning style and capability. Teaching techniques can accordingly be altered based on student pace and skill level, further augmented with technology innovations. If we can Dial in a Doctor, why not a teacher?

On a national level, a central repository can help make better decisions for the entire sector. The ball has already started rolling with the Digilockers and the National Repository of Open Educational Resources (high-quality digital content in local languages). The next step would be to make data accessible to institutions and academia alike – so that they can build customised techniques basis local and individual differences.

However, this is not a small undertaking. Challenges include low awareness, an absence of a data driven, insight – oriented culture, availability of uniform data sources and the apparent cost associated with data mining. Greater efforts are needed to adopt data management and infrastructure backbone for informed decisions, increased efficiency and greater accountability.

One of the foremost ways to address these issues is to increase collaborative efforts between educational institutions and data management enterprises. India must invest in a strong technology backbone, focused on hardware and software development across schools and higher education institutions. Educators need be trained to integrate technology in their pedagogy for effective learning.

But is the future of education solely dependent on technology? While data is set to move the educational landscape, educators are also working incessantly to build a sustainable and meaningful education system for all. The future will be about putting students first – with an innovative new curriculum focused on real-world needs, class design revamps for greater collaboration, rehashing educator roles and harnessing big data and artificial intelligence. The global conversation on innovative education is growing much louder and the urge to get rid of antiquated education systems has never been stronger and we should definitely not sit this one out.

There are tremendous growth opportunities for big data and analytics in the education sector. The Digital India drive can catalyse such initiatives by creating an enabling environment across the country.

Therefore, as we adapt to the needs of a 21st-century workforce, the sector needs a robust infrastructure background with measured approaches to manage life critical, business critical, real time, and mobile data. Backed up with investment, coherent strategies, and top-notch human talent, it’s now time to change the education sector with data.

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Artificial intelligence (AI) is developing quickly. Apple’s intelligent personal assistant, Siri, can listen to your voice and find the nearest restaurant; self-driving cars have become a reality, and IBM’s quiz contest-winning AI model ‘Watson’ is now being deployed to improve cancer treatment. While researchers and experts continue to exploit and harness AI’s “revolutionary” potential, the celebration could be premature. Microsoft chatbot on Twitter transformed into a Hitler-loving, incest-promoting robot in 2016; Wikipedia edit bots have repeatedly engaged in feuds over editing pages; and two chatbots on popular messaging application QQ in China were taken offline after they went off-script last week. Recently, Facebook also had to shut down one of its AI systems after the chatbots allegedly developed their own language. However, the social media giant clarified that its AI system had not gone rogue and the programme was closed as it could not have brought any benefit to the company.

As the instances of AI machines going awry grow, experts and researchers in the field of artificial intelligence have cautioned that the technology is incomprehensible. “Artificial intelligence is, of course, going to be unpredictable. Any really complicated controller can behave in unexpected ways. We’ll always have to be careful about what aspects of our lives we put into the “hands” of artificial intelligence. We’d want to vet these things really well before handing life-or-death tasks over to them — like driving, to give just one topical example,” said Michael Graziano, a neuroscientist and author of the book Consciousness And The Social Brain.

The two iconic entrepreneurs, Facebook CEO Mark Zuckerberg and inventor Elon Musk, are locked in a bitter tussle over the use of artificial intelligence. In 2014, addressing students at MIT, Musk likened AI to “summoning the demons”. “AI is a fundamental existential risk for human civilisation, and I don’t think people fully appreciate that,” he had said. Calling for oversight in 2017, Musk stated, “We need to be proactive about regulation instead of reactive. Governments couldn’t afford to wait until a whole bunch of bad things happen.” Responding to Musk’s remarks, Zuckerberg, on July 23, called his comment “irresponsible”. “I think people who are naysayers and try to drum up these doomsday scenarios — I just don’t understand it. It’s really negative and in some way, I actually think it is pretty irresponsible,” said Zuckerberg.

Two days later the war of words got ugly, with Musk tweeting, “I’ve talked to Mark (Zuckerberg) about this. His understanding of the subject is limited.” However, Musk isn’t the only one who takes a grim view of AI. Aaron M. Bornstein, a Princeton neuroscientist, believes that AI may worsen inequality and oppression. “More likely, and it is already happening — the ways humans use machine learning, it will worsen existing inequality and oppression by making it seem objective, and harder to overcome,” said Bornstein.

If AI machines are tipped to take over the important aspects of human life eventually, can experts instil values and human-like motivation in them? Michael Graziano, who is researching on engineering consciousness in AI, believes that AI can be made conscious. “The mind is something migratable to artificial devices. The technology is moving in that direction rapidly. A really convincing version, like Data, the android from Star Trek, might be beyond our lifetime, but that sort of thing and more will inevitably come,” said Graziano.

Oxford philosopher Nick Bostrom holds a diametrically opposite view. He argued, “We cannot blithely assume that a superintelligence will necessarily share any of the final values stereotypically associated with wisdom and intellectual development in humans: scientific curiosity, benevolent concern for others…” Facebook’s suicide prevention AI system had failed to prevent people from taking their lives in India. Two cases of live-streaming of suicide were reported in India after Facebook deployed AI in January to avert cases of suicide.  “Using AI to identify people who are thinking about suicide, and then reaching out to them, may be very helpful. But even if it helps to some degree, for some people, it obviously won’t solve the whole problem, so you’ll always be able to point to some spectacular tragedies. Communication technology seems to enable certain kinds of behaviours. I don’t think giving emotions to AI would make any obvious difference to that effort, at least not right now. Human beings are good at emotions, and yet not very good at suicide prevention,” said Graziano.

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“Technology is a useful servant but a dangerous master,” said Norwegian Nobel Laureate Christian Lous Lange more than a century ago. As companies pin their hopes on chatbot and artificial intelligence (AI) technologies, the big question the world is facing today is whether these neural machines would turn out to be friends or foes of the human race. While AI-powered chatbots are doing superbly when it comes to data analytics, facial recognition, voice recognition and cognitive comprehension, the next big frontier is to prepare them for “real-life” conversions with people. A daunting task, indeed. Microsoft’s AI chatbot “Tay” ran into trouble last year when Twitterati began slamming the “innocent” but with racist and offensive comments. Launched as an experiment to engage people through “casual and playful conversation”, Tay was soon taken off Twitter. “Bob” and “Alice” — two bots created by Facebook — were switched off last month when the team at Facebook AI Research (FAIR) found that the duo defied human-generated algorithms and started communicating in their own language.

According to the Facebook team, while the idea of AI agents inventing their own language may sound alarming for people outside the field, it is a well-established sub-field of AI. “You can call these experiment times as many companies are piloting chatbot initiatives. Fortunately, we’ve already seen some successful use cases that can deliver business and customer value. Chatbot and AI technologies will definitely evolve and have more use cases than today,” Xiaofeng Wang, Senior Analyst with global research firm Forrester, told IANS. “But whether it would be friend or enemy really depends on how we use it. As chatbots need to have a human-escalation protocol, any new technology application should be under control with careful planning and disciplined execution,” she suggested. According to Tamara Gaffney, Principal Analyst with Adobe Digital Insights, advances in technology always go through phases and we are currently in the failure phase.

“Most chatbots are based on simple-decision trees, sourcing siloed and incomplete data to provide answers. Users are mostly disappointed with any sort of complicated interaction but AI bots will improve dramatically because of the failures we encounter today,” Gaffney noted. Companies today are increasingly looking to rewire their DNA to adapt to the buying habits of digital customers and innovative technologies like AI and chatbots are helping them create immersive brand experiences.”Intelligent bots will transform every facet of industry and dramatically improve the customer experience. Chatbot apps with natural language processing (NLP) are expected to become the norm by 2018 and will dominate brand interactions by 2020, ushering significant changes within the enterprise ecosystem,” Mitesh Agarwal, Vice President-Solution Consulting, and CTO, Oracle India, told IANS.

Early adopters and AI start-ups are hopeful that chatbots will unleash a new wave of technology.”AI-powered chatbots are essentially meant to reduce manual labour and cut down tedious tasks that humans performed hitherto. With AI, automation, IoT and experimentation riding high, one can argue these are probably the best times in technology as the innovation is expected to touch every industry vertical,” noted Suman Reddy, MD, Pegasystems, India. Some experts, however, are wary of AI-driven chatbots and their future. Famed theoretical physicist Professor Stephen Hawking, Tesla CEO and SpaceX founder Elon Musk, philanthropist Bill Gates and ex-Apple founder Steve Wozniak have raised fears that humans, who are limited by slow biological evolution, could be superseded by AI in the near future.In the ongoing spat with Facebook CEO Mark Zuckerberg, Musk recently tweeted that Facebook founder’s understanding of AI is “limited”. Zuckerberg, on the other hand, calls himself an optimist when it comes to AI.

According to experts, where AI comes into the picture is when it can build its own algorithms by analysing patterns in large volumes of data, as long as there are good learning sets. Combine that with the power of automation (‘bot’ification) and the knowledge available on the Internet, and we can harness enormous capabilities.”However, ‘general intelligence’ is still a far-reaching goal for AI. The fancy digital assistants in our smartphones (Apple Siri, Google Assistant, Microsoft Cortana, Samsung Bixby, etc) can book an appointment, give you weather, play music and so on. But ask a general question and they would open a browser and show search results at best,” explained Rajesh Kumar, Delivery Head (Retail, CPG and Manufacturing), Mindtree. For Prakash Arunachalam, Chief Information Officer (CIO), Servion, we have to look at the technology from a broader point of view.

“We will definitely see conversations expand and become deeper and mature over time and will not be limited to data analytics or search through knowledge bases alone,” Arunachalam told IANS.The change will probably be in two phases. In the first phase, it would happen between customer and enterprise or customer and device.”In the second phase, we will start to see this change in enterprises and employee interactions with systems too, following natural conversations,” Arunachalam added.
For Gaffney, the term chatbot will probably disappear soon.”Our most likely method of mass access to AI bots will be via voice interaction. We would allow AI bots to evolve to levels beyond and to a degree that human conversations themselves will evolve because of the AI bots,” the Adobe analyst told IANS.

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Have you ever thought about what the future holds for us? Self-driven cars, automatically-curated Netflix queues, and an intelligent home that auto sets the temperature are some of the things that come to mind. It is no secret, then, that artificial intelligence (AI) will impact us in myriad ways as technology progresses.

A recent study by research firm Gartner found that over 55% of forward-looking organisations are either already investing in AI, or have plans to do so by 2020. This is a clear indication of the importance of this phenomenon, one that is bound to impact decision-making for businesses. By looking at current trends that are driving growth in customer experience, one can identify topical innovations and where they are bound to be powered by AI.

Look at popular consumer brands like Uber, Airbnb, Amazon, and Dropbox. They manage to support a growing list of customers that is in millions, every day, every hour and every minute. It is virtually impossible to staff enough people to handle each and every query, clarification or problem raised by such a massive cluster of customers. AI is the answer to the problem, for it delivers solutions using machine and deep learning.

While it is hard to predict how exactly AI will influence our lives, the changes it will bring about in customer experience can be predicted. This can be done by studying the emerging patterns.

Rise of the chatbot
Chatbots can deliver personalised communication by assessing patterns. As interactive platforms, they can manage many basic functions hitherto managed by humans. That will free up precious time of support agents, allowing them to apply their minds to more important functions. Automating most processes through bots also gives a company an image of being forward-looking and technology-oriented. Chatbots can also provide immense scope for companies to improvise and learn consistently about their own customers.

Multichannel to the rescue
With the rising number of communication platforms available today, how does a company choose one over others? AI presents potential for delivering personalised communication options for customers. Email, social media, chat, phone, etc. are some communication options today. The important point to note is, different customers have different preferences in the way they would like to interact with a company. Take, for instance, a millennial who is likely to prefer chat or social media as their preferred channel. But the older generation is likely to choose a telephone call or email. AI has the potential to learn these preferences and intuitively manage them for a company, thereby saving precious time and monies.

AI helps streamline processes better by directing a customer to a chatbot to respond to basic queries from a customer, and then escalate them to email or a phone call if required. Such engineered smart processes can help deliver better customer satisfaction and, not to mention, free up agents’ time in the process.

Agile responses
AI has the capability to quickly solve problems. Automated services can deliver quick turnaround time by providing easy-to-understand responses for most basic queries, thereby optimising agents’ time to manage more critical issues. Machine learning can also provide customers with assistance and advice on how to prioritise and handle an issue more effectively. This inherent quality of AI to streamline customer support by analysing patterns and delivering human-like responses to queries is advantageous both for customers as well as agents.

We live in a world that is constantly changing. A growing number of new-age companies demand new-age solutions to help keep pace with customer needs. The customer, on his part, is also transitioning and expects brands to relate to him and provide custom experiences. Customers across the world today have access to social media and on-demand TV, which is different from the offerings available a few years ago. To stay relevant, companies can rely on feedback and learning from their existing customer interaction and keep improving it through AI.

That said, one thing is for sure. AI, which was a speculation till five years ago, is now a reality and here to stay.

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