Building High-Impact Networks on the hello, Human Podcast
by Elizabeth Mitelman, Aug 19, 10:42:35 am
Our podcast, hello, Human, offers an open forum to discuss the latest topics in artificial intelligence (AI) and how it’s being applied in the real world. We talk with not only the pioneers of AI, but also those who are putting AI to work transforming businesses, finding novel solutions to age-old problems, and advancing what humans can accomplish.
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Episode 10 - Building High-Impact Networks
In episode #10, we talked with Beatrice Zatorska, CEO & co-founder of Smart Tribe, a platform that connects academics and industry professionals. Beatrice has almost 20 years experience spanning market research, consulting, technology, and startups. Prior to co-founding Smart Tribe, she helped launch two AI and machine learning startups.
We started by digging into the importance of high-impact networks in today’s hyper-connected world. Networking success requires will and skill more than an outsized personality, which means anyone can build and benefit from a high-impact network. Beatrice, with Smart Tribe, capitalized on network value in bridging the gap between academia and industry. The company’s platform uses AI to facilitate the connections necessary so these two communities can solve problems and break down silos.
“I think we know how to network as people,” Beatrice explained on the podcast. “Right from the beginning of our lives, this is the art of networking. When we were children, we found friends—that’s networking. As adults, we find partners for life, build families—that’s networking as well. Then we’re building career networks, friendships, and so on. We’re networking through life all the time. What I see currently, the network effect and the power of networks, is wonderful.”
Specific Networks To Meet Specific Needs
From a technology perspective, Facebook and LinkedIn are two of the biggest networks for personal and professional connections, respectively. But, since those are broad, catch-all communities, future networks could be more focused to create deeper, longer-lasting relationships. That’s particularly true in professional networks, which Beatrice expects to transform into places to learn, teach, and create niche groups. That niche aspect is what makes Smart Tribe so successful.
“Many of our (members) don’t even have a LinkedIn account because they feel overwhelmed with the noise and the size of it,” said Beatrice. “But joining Smart Tribe, very often they say, ‘We’re not just joining a platform, we’re joining the movement, a mission. This is our place. We feel comfortable here.’”
A network designed for academics and scientists filled a specific networking gap. The basic needs are the same—making connections, asking and answering questions, soliciting advice—but for this type of community, it revolves around a unique set of challenges. Transitioning academics and scientists to industry roles is just one example, and it’s a traditional, legacy process that’s not easy to navigate. Another challenge is turning their interest in science into impact, but that’s also a tough road.
“About 80% of academics have to move out of university because there’s simply not enough space for them,” Beatrice added. “They have to find a place somewhere else, which is in industry. But also, with the complexities of technology transfer, researchers are not motivated to (start their own companies) because 75% or so of the royalties stay with universities. More and more scientists right now really want to have more impact on what’s happening around the world. Why are you becoming a scientist? Because you took the oath to make the world better. That’s why, apart from the fact that you’re very interested in what you’re doing, you want to make an impact.”
A Smart Community Asks Smart Questions
The combination of legacy processes, conflicting incentives, industry regulations, and other factors makes this type of networking an ideal challenge for AI, which is where Smart Tribe comes in. But, since the company is working directly with some of the scientists pushing the AI envelope, they’re apt to ask questions about trust and transparency. Questions around ethical AI are ones Beatrice knows well.
“Every day we’re getting better and better at the knowledge we’re harvesting from all the exchanges between people in science and technology,” she explained. “We’re getting more and more clever, but we have to be responsible for what we are doing. Big companies and new companies coming to the market in AI should have good leaders who take the responsibility of building ethical AI companies, which means being transparent with the users, honest, having integrity, not manipulating, and even giving control to the users of the algorithms.”