Predict it. Copy it. Or Create it.

These are the three suggestions for anticipating the future as recommended by Dr. Rachel Schutt, ‎chief data scientist at News Corp.

Schutt’s team comprises data engineers, scientists, analysts designers — all of whom are able and even willing to cross-pollinate. The data head at the parent company of giants like Dow Jones and HarperCollins believes data products are key to any media organisation, but that the power eventually lies in the innovation — how ordinary methods like statistical linear regression can be applied extraordinarily.

Schutt shared her suggestions for anticipating the future with attendees at of the Big Data Media Conference, a joint venture of World Newsmedia Network (WNMN) and INMA.

  1. Prediction: This is a lot of what data scientists do. But there is a difference between predicting a one-off event like the weather, and predicting the behaviour of thousands of users.

  1. Copying the tech companies in Silicon Valley: It is easy to look at what they were doing five to 10 years ago and copy it to keep up. But, in fact, experimental infrastructure — which is what companies like Google, Microsoft, and Facebook have in place — is a concept has been going on for a while. For example, Diane Tang at Google nurtured and experimented with culture, even introducing a experiments counsel to help hone in on ideas. The Washington Post’s tools like Bandito are doing is great, Schutts said, but the company is also building on what tech companies did many years ago. And tech companies are doing what scientists like Ronald Fisher (an English statistician that died in 1962) did centuries ago.

  1. Create it: Don’t get caught up trying to keep up. Create your own paths, a piece of advice Schutts believes applies to even career paths. However, when creating the future, it is important to consider whether an innovation is actually creating value for the media company — or does it just sound cool?

Technology companies are doing several things at the moment that are of interest to media companies such as artificial intelligence, Virtual Reality, and user-leveling modeling. Natural Language Processing is one such experiment. It analyses natural human language as opposed to programming languages to help understand media. For example, when massive data or documents like the Panama Papers are leaked, NLP programmes would help see trends by analysing the words.

The words are the data.

Schutts concluded with multiple caveats to these approaches:

  1. Be wary of the fact that prediction can be causation.

  2. Be a data skeptic while doubling as an advocate.

  3. Technology and data are not the saviour. Good journalism is still key.

  4. Be accountable for your algorithms and know the impacts they could have on human behavior.

And all of these are bound together by the common thread: Be careful how you use this powerful tool that is data.