Data for Good: Using Data to Save the Planet

Data for Good: Using Data to Save the Planet

The topic of climate change is a big one these days. In the wake of the recent, devastating super-storms like Harvey, Irma, and now Maria, the focus on it becomes even more acute. And while we are not here to debate whether or not climate change is a thing, I do think a discussion about how data can inform policies and initiatives is one worth having. I believe data can change the planet. And here’s why.
At a recent Talk Data to Me event, I attended a session entitled “Data Meets Climate.” During the session, the presenters and moderators discussed the role of data in assessing climate change. It’s no surprise to anyone that scientists use data. But how they use data needs to change.
See, traditionally, scientists looked at data as a way to see progress. They analyzed historical reports and data points to determine the advances we’ve made in preserving our planet. And they use data to assess the changes we should make to drive even bigger impact. But what we’re seeing today is that traditional data is no longer enough.
Scientists need to look beyond traditional data to uncover insights. Why? Because insights help them identify different scenarios to solve and avoid. They also provide evidence and understanding of how we are changing (or in some cases, failing to change) and how those insights can lead to better decisions. That’s where a different type of scientist – the data scientist – comes in.
Data scientists know how to scale insights in a way that most regular scientists do not. They can look beyond the data points in front of them to see the big picture of what is – and what’s possible. And to truly affect climate change, traditional science and data science must intersect. It’s all well and good to set goals for how to impact climate change. But without data – and more important – insights,  it’s difficult to make the case for change and to achieve these goals.
By using technologies such as machine learning and artificial intelligence, both traditional and data scientists can see beyond human capacity. These technologies allow us to look at a massive amount of data and glean true insights in ways we never could before.
Further, new initiatives – such as data philanthropy – introduce ways for (data) science and business to come together to drive even greater impact. Businesses gain data through a donation, but it is their responsibility to ensure that they use the data to make an impact. That’s the moral piece of it. But it’s also where innovation can thrive by empowering organizations to explore the data, collaborate around it, and find new ways to drive change.
Clearly, data can drive great opportunity for environmental science. And there are massive efforts already underway that are making an impact. But it’s up to us to continue to advocate for investments in data to further drive change for the good of our planet. How will you use data for good?

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