Takeaways from Data Natives 2019

Let's Talk About Data

In a recent post, I shared the outcome of interviewing Data Native's Managing Director, Elena Poughia. That's us above. :) Thanks to NBT, I got to accompany some our data scientists there. Afterwards, I collected conference impressions because I felt a certain call-to-action: If we are to achieve a new level of ‘data literacy’, we must make data and AI part of public discourse. In short, data affects us all — whether we are aware or not. I see the Data Natives conference (#DN19) as a big part of a necessary push to get people discussing and grappling with data, so here's what I learned. Hope it's relatable!

What struck me personally about DN19 was the diversity of angles on data: from ethics involved in AI, visualizing data and investing in AI startups, to other areas where data will impact — for example, our work environments.

• Data Scientists continue to be in high demand as organizations struggle to make sense of, and often monetize, data. Along with developers, data scientists will face new ethical challenges and must be prepared accordingly. A panel on the ethics in AI (shown below) indicates that “ethics starts where policy ends,” meaning that we have to equip people to respond well to the challenges that data presents. A good example where this matters is when startups take a “move fast, and break things” approach. In that case, ask yourself: “Is this data inclusive enough for current deployment?”

• We also should acknowledge that biased data is everywhere, and for that, we need proper data collection from a broader spectrum of people. Presenter Vince Madai from Charité (shown below) pointed out the technological fact that if there’s bias in data input, the same bias is present in data output. Companies who are smart enough to take care of data ethics can challenge this to their advantage, creating new products that run counter to this and leveraging them as unbiased.

• When visualizing data, presenter Adam James recommends deeply considering your goal: Is is to explore (find something out), analyze (detect the frequency of a trend), or presentation (tell a story)? Consider your audience’s motivation and level of knowledge when presenting data and avoid creating what Edward Tufte famously termed as “chart junk.”
• A panel of investors interested in AI and moderated by Mali Baum (shown below) indicated that “even a beautiful AI algorithm doesn’t matter unless the data is verified behind it.” They stressed that one of the key features of AI will be blockchain integration. This is because in order to utilize data to make informed decisions, you need access to real-time, actionable and trusted data. Furthermore, your algorithms should be scalable.

• A panel on the future of work, featuring Catherine Bischoff from Factory Berlin among other forward-thinkers (see below), urged the audience to consider how automation will take away menial tasks and free up time for creativity. This means you should be thinking less about job titles and more about skills you want to learn and teach. They encouraged us to learn, break, and reinvent the rules. The panel discussed how best to coach remote workers, and communicate clearly across diverse channels of communication — like conveying emotion and leadership on Slack.

Check out the interview with Managing Director of Data Natives, Elena Poughia, here! Thank you for reading.