Norm Judah is the Chief Technology Officer of Worldwide Services at Microsoft, focussing on technical strategy, innovation, technical communities, knowledge management, and the development of technical people.

His team supports Microsoft Worldwide Services strategically, setting product and technology direction, driving technical readiness and quality assurance in the field. In an interaction with BusinessLine , Judah touches upon the impact of constantly changing technology and the challenges it presents to policy makers in the future.

A lot of technologies currently used, including Microsoft’s have not been designed keeping in mind usage patterns of developing markets. When will this change?

As our CEO (Satya Nadella) has articulated, the focus would be around cloud and mobile-based solutions. Business and consumer experiences are going to rapidly change the way people think about interacting and productivity. India, for us, has always been a place where we did research, develop software for our global requirements.

For example, we recently launched Skype Lite application designed for Indian mobile users in seven languages, which will be integrated with Aadhaar by June. Skype was first built on PC platform but in India it needs to be designed keeping in mind the mobile phone and bandwidth requirements. Henceforth, we will see products developed for unique markets (like India), which can also be taken to other similar markets.

How does Microsoft see India’s efforts to transform digitally?

The steps taken are positive. According to our recent survey, digital transformation in education revealed that problem solving, collaboration and digital literacy are among the top skills required by students to adapt to future workplaces and for teachers it was about transformation in teaching and learning experiences. Only 31 per cent of educators in the K12 schools surveyed in India believe they have the knowledge to make the most of the available technology and require tools to drive personalised teaching, manage online classrooms, content and assignments and collaboration among students on projects.

We have partnered with Andhra Pradesh government by applying machine learning tech to analyse where the school drop-out rates are high, predict those drop outs and take preventive action. This solution has been taken to 10,000 government schools across the State and has produced six lakh predictions.

Similarly, with ICRISAT, we tested a new sowing application to help farmers achieve the best sowing time depending on weather conditions. This showed a 30 per cent higher average in yield per hectare. During the pilot, farmers were sent advisories through SMS in Telugu.

In a country of India’s size, wouldn’t large-scale automation be disastrous?

We are trying to teach machines to learn so that they can do things which are mundane or repetitive for humans. Like Nadella has said, automation should not be at the expense of humans but, in turn, help them.

In today’s technology world, the future seems to be now. We see the work of people like Arthur C Clarke, Ray Kurzweil or Issac Asimov has already come to life. What next?

If we look back a year or two back even that pace of change is slow in comparison to what we envision going forward.

Take the example of our HoloLens technology. What we find interesting is that to develop an app using HoloLens, the developer should have knowledge beyond writing codes.

The developer should have knowledge of audio, video, gaming etc. and this new generation of applications demand a different knowledge set in developing software. Ultimately, one has to remember that using tools such as HoloLens, a 3D view of a building or a vehicle can enhance the collaborative working process rather than only using it as a wow factor.

Another sector which is transforming rapidly due to technology is automotive and transportation. Previously, a car was rubber and steel, now it a computing machine on wheels comprising video cameras, radar, and other processing points.

So when all these things come together, imagine the kind of challenges that it presents. For example, how can a vehicle differentiate between a dog and a pothole? This is where machine learning comes in.

Algorithmic and deep learning processing will have to come together and it will be the way forward.

It does open up questions around privacy and security?

Yes. There may be instances where a company may choose not to process or store driver’s licence information. In other cases, there will be a need to store it. This has to be done with consent from a user.

Regulatory policies around the world seem to be lagging as can be noted with Uber’s showdown in different geographies...

Policy was always thought from a technology point. They were set around what features could be used or what kind of stuff can be accessed.

Now, take the case of a driverless car. In case of an accident who is accountable? Is it the mapping company? Is it the car company? Or the company that designed or integrated the software? Or the camera maker? This mandates policy makers to think ahead and be constantly agile in their policy making decisions.

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