We are living in a world where Data has acquired immense importance. It is the biggest wealth anyone can have. It is also the biggest and best investment anyone can make. Data is going to be the enabler for whatever you want to do in the future. Data, by itself, is not a new phenomenon. It has always been there in various forms. People used to look at excel sheets at the end of every week/month/quarter to get a retrospective.

However, till the past few years, its real value was confined mostly to the boundary of labs. With the technological advances over the past few years and technologies like cloud being made available to consumers, it has taken a completely different meaning.

Technology has been changing very fast and with it, more and more data is becoming available.
We generate more data every day than the previous day. We can safely say –

• Data has never been generated so fast till date …
• Data will never be generated so slow ever …

The above statements will remain true pretty much in the future as well.

All this data is very valuable. Some folks say data is the new oil. Whether it is or not is debatable.

It surely is very very valuable just like Oil …  but it’s different from Oil – in the sense … it is not a resource which reduces on being used. As a matter of fact, using data results in generation of even more data. Every industry now uses data and data has also created industries:

• Data Processing
• Data Analytics
• Data Security
• Data Compliance
• Data Protection
• Data Mobility
• Data Privacy
• Data Collection – being some of them.

Each of these domains face ever increasing challenges due to the 4 V’s of data viz. Data Volume, Data Velocity, Data Veracity, Data Variety. While we will continue to see various companies trying to solve multiple challenges in each of the above areas, some things that are common across the board are:

• Data Ethics
• Data Privacy and
• Data Security

Everyone agrees with this, but very few people think about these when building a product.

None of the above can be an afterthought. They have to be an inherent part of the product itself and should be a part of the product development process.

Unfortunately, there is very less awareness about this where it matters the most – the mindset of every engineer. It has to be a part of the mindset of each engineer who is working on the product.

How do we achieve this?

We all learn technologies, but how many of the technical courses (minus the courses explicitly meant for say security) actually teach or even make the students aware of the above aspects?

Simple questions like  –

• Is the code I am writing fool proof?
• Can someone inject any code in the code I have written?
• What would be the consequence if that happens?
• How do I respond in case of such a scenario?

These and similar questions should be inserted into the minds to anyone who is learning any technology which would be used to build a product. This would be a step in the right direction and will make people aware of these principals. In this blog series, I will try to address some of the above principals so stay tuned and let me know your thoughts in the comments below.

In our last blog, we got an overview of various ways in which we can look at Data. We will start looking at one of the angles which is very important and becomes very very critical as data keeps increasing – Data Ethics. More specifically, we will look at it from the perspective of products being developed for ‘Data’ When we look at various products that are being developed around the ‘Data’ focus, we need to be aware of the fact that data is also just like technology. It is a boon to mankind, but if used in a wrong manner, it can be very dangerous. We see businesses ask for information that has nothing to do with how you are interacting with them.

For example – there is a case, where, to unlock a trading account of an individual, a company is forcing the user to provide all possible personal information including his/her current income.

In another case, a telecom giant is luring customers into getting phone numbers of their choice with just a single button. The user just has to click – “Proceed”. What the users miss is the fine print below this button – which says that the individual clicking the button gives permission to the telecom company to share all the information about the individual to anyone and everyone. Worst still – there is no way where the user can deny this permission and move forward. There was also a case of an event management company – which had a clause in the agreement in fine print which gave rights for video recording and all the copyrights of recording the event to this company without even the host getting to know about the same.

Companies like Facebook and Cambridge Analytica are fighting legal battles due to the manner in which they have used the data that they have access to. There are numerous such incidents happening around us in our daily life. Randy Newman’s lyrics – “It’s a jungle out there” fits very aptly in today’s data-context.

How do we survive in this ever-expanding jungle?

It’s up to us – those who are building the product – to ensure that we use the data in the right manner. Most of the times, while building the product, the focus is on the user experience, the technologies being used or even on the problem it is solving. While this focus makes perfect sense from a business perspective, how many times do we think about the “User” being the central focus?

A lack of such a focus results in situations resulting in a lack of trust in the product. There’s an old saying: “It’s easier to ask for forgiveness than permission.” That is exactly what a lot of corporations seem to be following. What a lot of them don’t know is – even companies like Google have had to deal with the fallout one way or another.

As a company, it is comparatively easy to deal with a fallout as businesses can get away with financial penalties or other tangible fallouts. However, are we, as a society, ready to deal with such approach? Every user shares data with a business with an implicit assumption that he will get an appropriate benefit or ROI on it. The user trusts the business to keep the data confidential and to use it only for the purposes it is meant for. Any business model basically is a model of trust. What happens once this trust is broken?

There is no easy way to rebuild the trust. The easiest way to not breach the trust would be to make sure every person who is a part of a business treats the data that a business collects – as your own data. Any data scientists or engineers working on the product will then surely give a thought to how their own data can be abused – before making use of it in the product.

There are certain rules which if followed, can help you treat the collected data as your own data and thus ensure that the business remains trustworthy and causes no harm to the society while still achieving their own goals.

These rules are the so called 5 C’s:

• Consent
• Clarity
• Consistency
• Control
• Consequences

In the next blog, more about these 5 C’s…

Today, more and more data is getting generated every day. Along with this, the ability to analyse data is also being pushed beyond limits. With increasing ability to analyse data there is an increase in risk for collected data. That data which was not revealing anything earlier, all of a sudden starts revealing huge amount of information.

Most of the times, the data collected is provided by people who expect to be gaining something out of providing the data. The expectation is that the data provided would be responsibly used – not shared, not maliciously used. They would even expect that the data is appropriately destroyed after the intended use of the same.

This, essentially is a model based on trust where the data provider trusts the data consumer. It is of utmost importance for the consumer to ensure that the trust is not broken. Anyone developing a product based on data should ensure that the data is being treated as if it is his/her own data. The question we need to understand is – why would the provider share the data?

The answer to this question is something very very critical for the entire industry – It is because the provider trusts the consumer. How do you establish this trust? Merely saying “You can trust me” is not going to establish any trust.

There has to be a well-defined agreement between the provider and consumer about how the data would be collected, stored, accessed, used/including shared as well as destroyed.

How many times have we clicked on “I Agree” button to move forward? How many times do we actually read such agreements? Even if someone reads these agreements, is it worded such that it gives information in  manner which is easily understood by the reader? Most of these agreements are ‘binary’ i.e. they consumer specifies certain condition to use the data and expects the provider to either agree/disagree. If you disagree, you are not able to use the services of the consumer. In a huge number of scenarios, the user does not have an option to disagree – for example, when I go to the hospital for treatment of a patient, do I have any option to say a ‘no’ to any of the forms that I am given to sign? It could have conditions like –

• They can share my data with insurance providers who can start calling me
• They could share my data with pharmacies
• They could be forcing me to buy medicines from a particular vendor

The hospital can use my data for any of such purposes. I have only 2 options – either to agree and get the patient treated, or to let go off treatment for my near and dear ones.

Does this establish a trust? ride-sharing apps need to collect location information about drivers and passengers to ensure the service is being delivered.

This makes sense in the moment of using the app. However, if the applies consent agreement allows location data to be collected regardless of whether or not the driver or rider is actually using the app, a user may be passively providing their location information without being actively aware of that fact. In such cases, the application may be inferring things about that passenger is interest in various goods or services based on the locations they travel to, even when they’re not using the app.

Given that location data may be moving through mapping APIs, or used by the app provider in numerous ways, a user has little insight into the real-time use of their data and the different parties with whom that data may be shared. For users of the ride-sharing app, this may cause concern that their location data is being used to profile their time spent outside the app information that could be significant if, for example, an algorithm determines that a driver who has installed the app is also driving with a competing ride sharing provider. Without clear consent agreements, interpretation of where data moves and how it is used becomes challenging for the user and can erode the trust that their best interests are being served.