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Last week, US-based suicide prevention nonprofit Crisis Text Line published research on the words that indicate a high risk of suicide when used in text messages. While humans tend to watch for emotional cues such as ‘sad’ or ‘desperate’, Crisis Text Line used machine learning to identify the words ‘Excedrin’, ‘Ibuprofens’, ‘800mg’, and the pill emoji as most likely to indicate an acutely suicidal person. Using this model Crisis Text Line is able to identify 86% of the highest-risk individuals, and move them to the front of the line to receive active support.

Here are two takeaways for using tech for good:

Humans are biased. And those biases lead to poor, or unfair, decisions. Increasingly, consumers are looking to organizations to deploy technology – AI and algorithms – to help identify and correct human bias. This example shows the power of that approach to do real good; by better identifying the SMS words likely to indicate a person at risk of suicide, Crisis Text Line’s research could save lives. See also how recruiters are using arobot for unbiased interviewsor how this digital tool can check forgender bias in TV and movie scripts. Of course, when it comes to bias the situation is far from simple; we all know thatstructural biases can be encoded within algorithms, too. So the key challenge for you:where could human or algorithmic bias be leading to poor or unfair decisions within your organization? And what can you do to change that?

One surprising finding in the Crisis Text Line research? The pill emoji is a key indicator of a person at high risk of suicide. We tend to associate emoji with fun, informal or playful communication; in this case it’s anything but that. Of course, the communications of most brands pale in significance when set against the mental health work of Crisis Text Line. But this finding is still a powerful reminder to ask yourself: do you understand, and speak, the language of the people you are seeking to engage with?What new ways to serve your customers could you unlock if you were present in the communications channelstheychoose, and spoke the language they speak?

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