Ethical data capture using mobile technology

Over the last decade, we’ve seen our ability to capture data grow exponentially – almost every device in our homes is capable of some form of data capture and experts believe the trend is only going to continue with as many as 900 million data capturing connected devices in our homes by 2021. 

With all of this data available, companies are finding increasingly powerful ways of analysing, harnessing and manipulating data to influence customer behaviours, bias and even political views. 

Due to the sheer power of data and its applications, we’re now confronted with a new problem though: how can we capture, store and use data ethically? 

At Apadmi, we’re extremely passionate about data protection, security and privacy; we’re certain that the next 10 years are going to be critical politically and ethically to the continued use of data.

What does ethical data capture look like in 2021?

A report from Gartner predicts that the majority of CEOs will be held accountable for data breaches by 2024, as both the frequency and severity of cyber-attacks and data breaches grow. 

Some data analysts predict that in the next 12 months, the regulatory and legal activity will double in a move that’s set to penalise businesses who fail to take a thoughtful approach to the processing and privacy of employee data.

We expect to see even more legislation introduced over the next decade that protects consumer rights and fines businesses for irresponsible data use. To meet this challenge and to avoid litigation, more businesses are adopting ethical data solutions, including the use of ethical mobile data capture technology. 

What are the methods of data capture?

To better understand ethical data capture, it’s useful to understand the methods of collation. At a high level, there are two distinct methodologies used: top-down (known as symptomatic) and bottom-up (known as systemic).

Top-down (symptomatic) data capture

The theory behind a top-down approach is a business user or organisation solving a specific problem or use case by asking questions about the data surrounding the problem. 

For example, to create a new product, a toy manufacturer might start asking customers about the sort of toys they would like to buy. 

Bottom-up (systemic) data capture

The bottom-down approach looks at data and forms relationships from it, to help answer questions or inform decisions based on the results found from that data. 

For example, a toy manufacturer might notice a lot of customers searching on their website for model planes, so they might start making more model planes.

What are the challenges of data capture?

Both types of data capture must be done with privacy and integrity. The possible penalties, PR issues and damage to customer trust have ensured a strict culture in business with regards to data, while consumers are becoming increasingly aware of how the mishandling of their data can lead to fraud and theft. 

However, we must also preserve the quality of data collected, as inaccurate (or false) data will produce incorrect information, which can lead to poor decision-making. Blank fields, spelling mistakes and incorrect values are all things that damage the quality of the data collected. 

A further challenge is regulation, such as the General Data Protection Regulation (GDPR), a regulation in European law that came into effect in 2018. The regulation gives individuals, known as ‘data subjects’ much greater control over how businesses and organisations process their personal information. 

Personal information consists of names, email addresses, location data, photos and health records to name a few. Essentially, anything that can be used to identify a living person. Organisations that have failed to comply with GDPR have been hit with weighty fines, with the largest topping out at £20 million for British Airways in 2020. 

Perhaps the biggest challenges to data capture however are the ethical and social implications. Some recent headlines that have brought these issues into stark contrast for us include:

  • Cambridge Analytica – One of the most well-known examples of data misuse, Cambridge Analytica used Facebook’s ‘Friend API’ to collect descriptive, cognitive-behavioural data points from around 30 million Americans to directly manipulate them to vote Republican in the 2016 election. 
  • The Marriott Hotels Chain – A recent example of data misuse, the Marriott data breach led to the records of 7 million guests being shared across the internet. The company was attacked once in 2014 and failed to put sufficient safeguards in place to protect its customers, leading to another successful attack in 2018. The Information Commissioner’s Office (ICO) sentenced the Marriott Hotels chain to a fine of £18.4 million. 
  • In-Store WiFi Data Capture – Connect to the in-store WiFi services of many major retailers, and in most cases, you’re allowing them to monitor your activity. This has led to many a customer’s activity being tracked and their API being mapped, so that it can be sold/passed on – this is legal, but unethical. These systems often hide their intentions behind lengthy agreements, and use the customer’s assumption of reasonable data use against them, by taking far more data from a customer’s device than they’d usually want or allow.

All of these cases represent threats to our data and the erosion of trust within the wider consumer market. Customers are finding that the technology is moving faster than they can keep up, creating fear and suspicion with wider social and ethical implications. 

This is a growing problem, but the solution may lie in mobile apps.

Using mobile apps for ethical data capture

Collecting consumer data has become a vital part of most businesses, and many have searched for new ways to learn about their customers or employees. One of the most effective options to obtain this data is through a mobile application, as it requires little action on the part of the user and is capable of tracking hundreds of data points with ease.

Mobile apps also avoid a lot of the ethical pitfalls surrounding traditional paper-based data collection, such as user-error, lack of validation and the increased need for unskilled manpower. 

That being said, mobile apps can face their own challenges. Historically, field researchers and clinical teams working in remote locations have faced issues with low or no internet connectivity and their equipment, making them a target for mugging or theft attempts. Many apps can also access far more of a phone’s data than the user may want. 

However, in recent years we’ve seen many of the problems surrounding mobile data capture in apps solved. Mobile apps are now able to offer many features to aid in ethical data capture including:

  • Simplicity – The ability to run on older, and therefore less desirable, hardware has been key to allowing researchers, health professionals and more record data in the field without becoming a target for criminals.
  • Offline Mode – With offline functionality, apps can record data away from the internet and log it once the device connects again. Data can be recorded in the most remote areas, allowing for a more accurate record to be created. 
  • Ease of use – UX and UI design options that make apps and data collection methods accessible to more users, no matter their level of education, disabilities or age. This has allowed many to have their voice heard. 
  • Privacy by design – We’ve seen many apps created under the growing ‘Privacy By Design’ movement, which essentially calls for the privacy of the user to be considered at every step of development. Apps like Signal, Marco Polo and Brave have all been created with this philosophy, offering extensive privacy settings as well as a promise to protect the user’s data. 

By employing an app with these features, a company that wishes to collect data can do so effectively and ethically, only using the data that’s necessary for the company and only in the way that the user wishes their data to be used. 

Unlike many online forms that can be easily manipulated and changed, a mobile app has a record of changes associated with it and hard coding, making it a powerful legal tool if a company is investigated by the ICO. By investing in an ethical data capture app now, you may be saving yourself a fine of millions in the future. 

Zero party data

A fantastic option for companies concerned with ethical data capture, the use of zero party data has become more widely adopted in recent years. Zero party data is information that a customer freely provides; it’s not inferred from common behavioural data collection methods, so instead the customer is asked questions like: 

  • “How often would you like to receive emails from us?” 
  • “What type of videos do you like to watch?”
  • “What other products are you interested in?”

Zero party data presents marketers with an opportunity to collect valuable, actionable and ethically-gathered information about customers symptomatically, in a time where data collection and usage is fraught with challenges. 

Apps are ideal for capturing zero party data, as developers can create UX optimised gamified experiences that make answering questions fun and rewarding – taken to the extreme, the user can even earn rewards from your company for questions answered (an approach similar to this has been taken by privacy advocate and cryptocurrency website ‘Blockchain’). 

Why mobile technology is perfect for data capture visualisation

Another area of ethical data usage is the visualisation and reporting of data. 

It’s been well documented that statisticians can manipulate data to show almost any result they require. Similarly, an unethical business might use them to manipulate their data to show the results they want instead of the true results. To prevent this data manipulation, sometimes referred to as interpret bias, a company can use a data visualisation tool. 

Data visualisation tools quickly record and report on data from multiple sources; by using one, a user can quickly cycle through many different reports and data points to see the results presented in any form they want. With these tools, a user can avoid interpret bias and manipulation, gaining a wider understanding of their results. A great example of this is our award-winning Sail GP app

In the app, users can look at hundreds of different data points at once to determine what is happening and going to happen in the sailing competition they’re watching. This means users can creatively find different ways to interpret data revealing or debunking trends, making the data far more engaging and empowering the user to look at it in every way possible.

We believe that armed with powerful data visualisation tools and ethical data capture methodology, your platform can be an engaging and positive tool that users will champion. 

If you have more questions around ethical data capture and how your company can implement an ethical data capture solution, contact us to learn how Apadmi can help you.