What do we mean by data ethics
There is no single definition of what ‘data ethics’ means. However at a high level, it is about the application of value judgements and a moral prism to the way data is used.
Although many of the concepts are based on personal data laws they extend beyond personal information, and encompass principles borrowed from human rights legislation and philosophy.
What’s driving the data economy?
Advanced analytics can make sense of the vast array of data harvested from our internet and social network activity as well as from emerging technologies such as chatbots and artificial personal assistants. They can help businesses optimise their processes and supply chains, and market and price their products and services. They are also used to determine financial credit and predict crime.
5G connectivity will ramp up internet bandwidth and, along with rapid improvements in sensor technology, will turbocharge the Internet of Things, autonomous systems and robotics, AI and consumer devices.
At the same time, new technologies are being developed that massively increase our ability to process data.
Which use the principles of quantum mechanics to perform multiple calculations at once, could be a million times faster than traditional processors.
Data ethics… is similar to the dawn of the environmental movement. We are beginning to wake up to the downsides of this amazing resource called data that everybody loves to compare to oil or gold.
There are well-defined legal obligations that relate to the use and protection of data, particularly when that data identifies an individual.
However, technology is developing so fast that law and regulation – despite authorities’ best efforts – is often one step behind. As a result, many businesses are starting to develop ethical frameworks to govern their decisions around data use. Rapid developments in our ability to collect and analyse data offer huge potential for business.
But just because we can do something with data, it doesn’t necessarily mean we should. These ethical frameworks go beyond compliance and ensure companies stay ahead of regulatory developments and build consumer trust. While much of the debate centres on personal data, it is important to understand that it goes further than this. Machine learning algorithms for example can be put to unethical or irresponsible use, despite being trained to ‘think’ on anonymous data.