AI & Content Creation

For a very long time, people did not think of computers as creative, or original. To automate mechanical and repetitive tasks, sure, computers are fantastic, but for inspiration and creativity, surely this was the sole domain of humans?

With recent, big advances in artificial intelligence, this assumption is rapidly eroding.

Artificial intelligence is already being used in many areas of content creation. For example, Natural Language Generation (NLG) is being used professionally to automatically generate product descriptions and search keywords, create email and direct mail campaigns, and even write entire articles.

Alongside text-based content, an area of artificial intelligence called…

Using Natural Language Processing to identify topics within the academic literature around lockdown & quarantine


As the holiday season has passed, I’m sure there has been a lot of discussion around your dinner table with family and friends about the lockdown measures different countries have taken.

Similarly, across academic communities, there has been a great deal of research, discussion and debate.

Whether that be those academic fields that directly measure and influence the effects and decisions around public health and social measures, such as epidemiology, biostatistics and virology. Or those that indirectly measure the impact of such measures, such as economics, sociology and psychology.

With ever-increasing mountains of literature around COVID-19, it is difficult for…

The field of data science is no longer the new kid on the block it once was. “Data science” in its modern usage has been around since the early 2000s.

Many companies, of all sizes, now have data scientists trying to extract value from their data and help companies make better decisions.

What has changed is that, as a discipline, data science has matured. Many companies have gone from proof-of-concept mode to running multiple productionised machine learning models in a short span of time, with varying degrees of success.

A lot of the reason behind this success or failure is not having the most highly qualified data science talent, or having the most expensive, state-of-the-art tools and technology, but by organisational structure and team culture.

In this article, I outline…

Introduction: The Dawn of a New Governance Era

Data governance is certainly not a new concept — as long as data has been collected, companies have needed some level of policy and oversight for its management. Yet it largely stayed in the background, handled by IT and never seeing the light of day, as businesses weren’t using data at a scale that required data governance to be top of mind.

Yet in the last few years, it seems that data governance has shot to the forefront of discussions both in the media and in the boardroom as businesses take their…

If “Data Scientist is the sexiest job in the 21st Century”, then data quality is the least sexy aspect, but that doesn’t take away from its critical importance.

With growing investment around Artificial Intelligence and Machine Learning, and near-daily success stories in the news, organisations in traditional industries are investing in data science like never before.

However, many of these companies must deal with legacy systems, a lack of core data skills across their employees, and poor data quality.

The consequences of poor data quality can be enormous. In a research study published in MIT Sloan Management Review, companies are…

Jon Howells

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