Artificial Intelligence poses challenges; what industries can do to adapt to new technology

Revolutions do not always follow a linear timeline. They can be sporadic and unpredictable. NITI Aayog’s roadmap for national Artificial Intelligence (AI) Program hopes to bring on one such revolution. The allocated Rs 3,073 crore will spearhead work on fifth generation technology startups like artificial intelligence, machine learning (ML), Internet of Things (IoT), 3D printing and blockchain. The magnanimity of effort can be gauged by the almost doubling the fund for the program. Atal Innovation Mission can give 10 crore to start-ups that fit the criteria. 200 crores is allocated in 2017-18. India is now ready to take the AI assisted leap of faith, with pre-meditated outcomes for before, during and after the leap.

The oncoming revolution has go through mountains of paperwork, maze of data silos and murky data lakes before the AI can begin to make sense of the haphazardness that is India. Let’s tackle some of the important questions when it comes to these futuristic technologies.

Where do we stand?

The next generation of technology is seeing exponential growth. The overall picture is blurry though, due to the extremes we need to be navigating. To crunch some numbers, according to Tracxn, there are more than 200 AI based start-ups in India. In a March-June 2017 Capgemini survey of nearly 1,000 companies in India with revenue of over $500 million, around 58 percent have gone beyond pilot and test projects and adopting the technology at a larger scale. The number of Internet users in India is expected to reach 500 million by June 2018, it’s the second largest online market in the world. At 160 m users of WhatsApp, we are having a generation of people who skipped any computer learning and straightaway became mobile consumers of internet.

Around 99 percent of India’s population - a staggering 1.19 billion records - has Aadhaar, which is the world’s largest biometric ID system. It is also India’s first foray into scaled up technology that has no precedent. And this is precisely why the Aadhaar comes with its own set of unique challenges.

The first challenge is how much of your data is personal? Does a collection of retinal scans and finger print breach a right of privacy? Aadhaar is mandatory for one service after another - phone numbers, ration cards, bank accounts, income tax filing. All of the interlinked data will be available to government to garner insights using AI. Later, when in the larger scheme of things, this data will be linked to hospital records, land records, purchases, this could be made visible or sold to interested parties, legally or illegally.

The second challenge is of course, security. It is impossible to create a non-hackable system. Aadhaar opens up a minefield of security lapses, where the hacked data can be used by personal or professionals to cause great harm to a person or society. As pointed out by media, there have been lapses in the past wherein the data is leaked or sold or hacked into. Government needs to make stricter laws and plug in loopholes when it comes to Aadhaar data.

The third and yet unseen challenge is the moral implications of using AI, because there is no universal right or absolute wrong in this case. Every case differs from the other. This is the most difficult challenge of all, because there is limited data to study the new scenarios that will be originating when AI will be using countrywide data to garner insights. Let’s take the case of linking Aadhaar to medical records. In times of disasters, natural or manmade, floods, fires, train accidents - fingerprint identification and medical history of a patient available to a medical profession will be the factor determining life and death. Analyzing the cases of particular diseases in a specific region, will there come a point when AI will be able to predict epidemics before they break out?

Websites and apps query people if they are willing to share crash data with developers to better the systems over a period of time. Will hospitals give out similar consent forms to people if they are willing for their data to be used in analyzing patient records by AI to look for insights that have escaped the human eye.

Personal data is a double-edged sword. Enterprises and governments can make use of data for a variety of scenarios when it helps people, but cases of blatant misuses will also be flaring up in huge numbers. Medical records of employees helps an organization in times of emergency care for employees with heart condition or diabetes. But can be used for discriminating against employees that have a medical condition of social stigma like mental health issues or AIDS.

Major challenges for industries for using AI?  What needs to be done for adapting AI in industries?

Create secure, usable, scalable data

Data is the smallest and the most important unit of an AI system. AI is all set to revolutionize manufacturing, transport, healthcare, finance and retail to name a few. But, the biggest problem in India across industry verticals is the severe paucity of usable data. We need to create a system to convert records on paper to create data lakes for ML to take over from humans. ML will start to analyze data and then an AI enabled system learn by itself and provide actionable insights. The mindset needs to shift from find and fix mentality to preventive maintenance.

The major barriers to storing data digitally is a lack of trust and time and the inertia to shift from existing systems. Digital data is not considered secure, real estate for example. You have to get a stamp paper to to a registrar and get the documents in your name. For smaller transactions too, a paper bill is preferred over an email. A majority of all our transactions are physical - cash for receipt. We need a simplified, encrypted digital transaction system that is easy to adopt. Government departments - legal, transport, medical, educational - carry majority on their transactions on paper, creating silos after silos of static, non-usable data. The existing data is not centralized, creating a disorganized data maze that is impossible to navigate. The digital revolution needs to first start creating organised, usable, accessible data.

Repesentational image. Artificial Intelligence. Reuters

Repesentational image. Artificial Intelligence. Reuters

Create the ecosystem to train AI professionals

Around 4000 positions in the field of AI are vacant in India due to insufficiency of talent. Kelly OCG India reported that India would see a 60 percent rise in the demand for AI and ML professionals by 2018. It’s difficult for Indian companies to attract talent from outside the country.

The educational institutes need to be scale up and be better equipped for the changing demand for new technologies. A change in curriculum as well as opening new colleges, specifically dedicated to higher studies in the fields of Machine learning, Big data, Cloud computing is the need of the day. We need to start to develop in-house talent to cater to the exceeding demand for skilled professionals.

Wadhwani Institute for Artificial Intelligence, India's first research institute dedicated to developing artificial intelligence solutions for social good was inaugurated in February 2018. Private-public-government partnerships will ensure knowledge centers for advanced studies, this in turn will create an in-house talent ready to be absorbed in the fast developing AI ecosystem.

Online courses in AI and Machine Learning from industry leaders like Andrew Ng on Coursera are very helpful to companies that are want their workforce to upskill and stay relevant.

AI is not a magical cure for all problems

Every industry has specific requirements where the use of AI can help tremendously. Be it manufacturing, healthcare, education, transport: every vertical gains from the use of AI. An enterprise needs to have an understanding of timeline of the solution, resources allocated for it, financial implications and the fact that AI doesn’t always have a tangible ROI. AI can give results, there is a timeline of training the solution to be able to derive actionable insights. The learning curve is often steep.

NLP is another roadblock as availability of natural language processing in any Indian language is scarce. Indian english contains words spoken colloquially and often has a mix of some words in people’s mother tongue. Going by the success of HDFC bank’s chatbot, OnChat, the feat is not impossible to pull off. OnChat can effectively process a mix of Hindi and English and converse with customers to transact for bill payments, mobile recharges, booking travel etc. It has also garnered 160% month on month growth, garnering 2.4 million messages.

Start-ups can provide faster and more efficient solutions for AI projects as opposed to larger corporates

India has a great scope for start-ups that work in AI space. Due to the small size of a team of dedicated resources involved with a project, there is better co-ordination - the UI/UX designers, Architects, developers, data scientists and the client. Smaller team also means shorter turn-around time for agile requirements of the client. The absence of a defined protocol and time-taking processes leads to a fluid work environment where the client can work closely with the team working on the AI solution.

Innovation is the name of the game

There are many start-ups in India creating chat-bots, financial solutions and medical scan solutions. But what will really give Indian companies an edge if they are able to crack uses of AI for Indian population and it’s different requirements.

A NLP chatbot that can converse across different languages in India will make life simple for millions of Indians that do not know english. Using AI to recognize handwriting across different languages in India will simplify data entry and help in creating a clean data lake for the whole country. Currently, most websites support roman keyboard, alienating millions of Indians. Something as simple as allowing people make rail bookings on the mobile app, filling forms in their native language will simplify life for rural India.

AI can create a transparent system and bring on a revolution in agriculture. Providing real time selling price of crop across nearest markets, providing a cost-analysis of transport to farther market for selling or prediction for market rates in the coming weeks/month, route-map for nearby storage units can all be fed into a centralized system and provided to farmers. Peer to peer discussions, best practices, weather updates, tractor rentals - there is a lot that an AI-enabled solution for India can achieve.

The start-ups in India are fully aware of the shortcomings and work with it to evolve AI solutions that are India ready.

Take that AI enabled leap of faith

India is a developing nation where we are still struggling with poverty and with providing food and shelter and fulfilling basic needs of being a human being. But, in prioritizing food and shelter, we haven’t put our dreams on hold. We dream.

So, the question is, are we, as a country, ready for AI?

The answer is a complex, ‘we don’t know’. But we are not going to find out, unless we go ahead and do it anyway. Time to consult our AI solution and take that AI enabled leap of faith.

(The writer is Co-founder and CEO of Integration Wizards. Views expressed are personal)


Updated Date: Mar 15, 2018 17:49 PM

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