Here at The Signal, we believe that the world is better off when people use data to make decisions. So, for the Thanksgiving holiday, we gathered the most memorable interviews with innovators who have used their expertise in product, design, and analytics to incite positive change – on their team, in their country, and across the globe.
Read the advice, insights, and ethos of those leading the charge to address the most pressing issues of our time, including:
Former Appleite Daniella DeVera joined Code for America – the so-called ‘peace-corps for nerds’ – because she wanted to create the ultimate user experience at the scale of the United States. With user-centric design, her team built products that reduce stigma, overcome language barriers, raise awareness, and ultimately bring food security to the more than two million people in California who didn’t know where their next meal would come from.
As a systems analyst for the United Nations, CJ Hendrix spent many sleepless nights working in tents in Ethiopia and Eritrea collecting, cleaning, and standardizing humanitarian data that would eventually become the foundation of the Humanitarian Data Exchange. Used by NGOs, authorities, and aid workers in over 200 countries and territories around the world, the data repository his team built generates the intel needed to deploy the right resources to right people and provide relief in crises.
Entrepreneur Mina Radhakrishnan left Silicon Valley to start her own company after realizing that echo chambers don’t produce good products – and often hinder the creation of great ones. During her time working at tech giants like Google and Uber, Mina came to see diverse product teams as an incredible force for innovation, with the potential to improve the lives of people who wouldn’t otherwise benefit from advancements in technology.
Curious about we’re reading at The Signal this holiday season?
Signal contributor and our customer marketing expert, Christine Deakers recommends The Happiness Hack by Ellen Leanse: For product leaders, most days are zeroed in on figuring out how to build habit-forming apps and websites. But some of the most creative solutions are found when you take a step back. This holiday season, reboot your product POV by reading what Nir Eyal calls, “a user’s manual for the brain.” Apple and Google alum Ellen Leanse shares advice on how to manage your mind to benefit your life and the things you strive to create.
Signal writer Emi Tabb recommends Kid Inventors Tell All, a video from The New York Times’s Sussanah Kemple: Many of the experts we feature on The Signal speak to the importance of user empathy when it comes to building products with staying power. But being constantly bombarded by the twenty-four-hour news cycle can strip us of emotional energy we need to connect with others and the challenges they face. For a fresh approach to user empathy – and some renewed hope for the future – watch these young inventors talk about their approach to building products with love.
Mixpanel’s website manager Katie Herbst recommends Spotify’s Discover Weekly: How machine learning finds your new music on Hackernoon: What music lover doesn’t appreciate a completely personalized playlist, refreshed each week? In this article, Sophia Ciocca takes a (very) deep dive into the secret sauce behind Spotify’s Discover Weekly playlists that get delivered straight to your headphones every single week. Spoiler alert: it’s data. And a lot of it.
Signal writer Jordan Carr recommends AI Versus MD: What happens when diagnosis is automated? by Siddhartha Mukherjee from The New Yorker: Machine learning, deep learning, AI – it’s all cool, cutting-edge stuff. But how far along we’ve gotten with these technologies is often overstated. We’re not going to get self-driving cars next month, and the robots aren’t going to steal all of our jobs and/or kill everyone. There is one place in particular, though, that machine learning has a chance to make an enormous positive impact – and soon: the field of medicine. Back in April, the author of The Emperor of All Maladies explored the way that machine learning is going to affect the field of radiology. He tempers his conclusion, but it’s hard not to be excited about a future where neural networks work side by side with medical professionals to get more diagnoses right and save lives.