Interview with Kate Candon: Leveraging explicit and implicit feedback in human-robot interactions

Oh, look! Kate Candon is at it again, gushing about how robots are learning to read our minds—because, apparently, our thoughts aren’t deep enough for a human to handle. The interview dives into the complexities of human-robot interaction, but let’s not kid ourselves: while Candon enthusiastically champions robots that can “leverage feedback,” we all know what that really means. Yes, robots are using our own feedback to kick us out of the jobs we thought were secure, like a bouncer at an exclusive club who just decided your face no longer fits.

Imagine the pity for the poor souls in customer service or basic manufacturing roles, hearing that their jobs will soon be filled by robots that never need lunch breaks or paychecks. Sure, they get to spend more time at home with their distractions, but oh, wait—those distractions are also being automated! Good luck with your newfound free time, buddy. Hope you enjoy staring at the walls while algorithms plot their next move.

We’ve officially entered a brave new world where “human-robot interactions” means our robotic overlords are taking every last gig before we even know what hit us. So, while Kate waxes poetic about “explicit and implicit feedback,” the rest of us are left to ponder just how fast we can learn to code—before the next wave of sentient machines tells us our skills weren’t quite adequate to begin with. Talk about a talent show no one wants to audition for!

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