Baby On Circuit Board

Jenn Sydeski guests. We chat about babytech, and how the proximity of a parent's "village" has dissipated over millennia... only to transform into an omnipresent digital collective.
(1:29) Mitch introduces Jenn Sydeski, Founder of Connect Wolf. She speaks to prior advancements in mommy autonomy that not only replaced the need for non-stop in-person vigilance, but also helped distribute the communal parenting load from people to objects and algorithms. (7:43) We talk specifically about Jenn's product and vision, wherein she explains how her long-term goal of solving for affordable & equitable healthcare is currently being manifested through her first product, which uses a complex system to deliver the kind of simple peace of mind parents desire, yet hesitate to entrust to others. The argument made here lies in deploying tools that enhance and expand the power of parents. Mitch ties it back to all the micro-movements moms make throughout the day to manage their children, and how progress has shifted even those small movements from transportation to communication. (11:35) We examine the babytech market, why it's so lucrative, and what challenges it presents. Not surprisingly, the conversation turns to the time deficit of working families, as women went into the white collar workforce and met an environment that expected the same full-time dedication it was already abusively squeezing out of the current labor force. (17:51) Mitch switches hot take horses midstream thanks to Jenn's insights. His original argument was that innovation requires the destruction of sacred traditions, ergo parenting only progresses when we stop acting as if it's beyond judgment. The revised argument infers that experimentation (mutation, if we want to call it that) is also a requisite for innovation, and as such, the pursuit of reducing parenting to a quantified and optimal state is inherently flawed. Jenn is well ahead of Mitch and cites evidence of different parenting styles yielding equally beneficial outcomes. We both trace the talking points to modern-day artificial intelligence research, wherein so much of the effort to optimize a function results in overfitting or otherwise impractical programs.