I’m coming to the conclusion that a key strength of the fedi is that AI/ML don’t fit since there’s no usage/addiction/advertising-based business model. Commercial enterprises can ramp up and develop super quickly while FOSS slowly follows to build sustainable alternatives. Your post makes me want to explore how to speed up FOSS in building and converging on those alternatives. Fedi TikTok for one sounds like it’d be a blast to build as does OPs idea.
I also like that we can use the very technologies that made products with features we dislike, to create features we like. If such a feature is an algorithmic feed, it doesn’t necessarily have to be created with the goal of maximizing engagement. It could, for example, be trained to maximize happiness or a broader sense of well-being, or connection, or purpose, or any/all of the good stuff that positive psychology has been showing again and again in study after study that makes humans flourish. Omg… what a dream…
Obligatory response to the impending “but happiness is subjective, and how do you measure it anyway”: Indeed, happiness is subjective, but so is, to an extent, the content that ‘engages’ people. And yet the algorithms that maximize engagement are out there, being deployed again and again in social network after social network. Not only that, but we as humans have developed sturdy enough models that reliable predict and affect peoples’ experience.
To name a few of the relevant people in the literature, there’s Mihaly Csikszentmihalyi, Sonya Lyubomirski, and Martin Seligman. They show that psychology can be used to understand how humans feel purpose and happiness, and that it can also be used to guide people into those directions. They use all kinds of methodologies, including my favorite, real time sampling through the experience sampling method. This is basically asking you at random moments throughout your day what you’re doing and how you feel (along with many other questions). This is asked to hundreds if not tens of thousands of people, and the resulting absurd amount of data can be used to create robust models.
Anyway, that’s not the point of my comment, but I figured it was better to be safe than sorry. My point was that it’d be amazing to have algorithmic feeds trained to make us flourish.
I’m coming to the conclusion that a key strength of the fedi is that AI/ML don’t fit since there’s no usage/addiction/advertising-based business model. Commercial enterprises can ramp up and develop super quickly while FOSS slowly follows to build sustainable alternatives. Your post makes me want to explore how to speed up FOSS in building and converging on those alternatives. Fedi TikTok for one sounds like it’d be a blast to build as does OPs idea.
I also like that we can use the very technologies that made products with features we dislike, to create features we like. If such a feature is an algorithmic feed, it doesn’t necessarily have to be created with the goal of maximizing engagement. It could, for example, be trained to maximize happiness or a broader sense of well-being, or connection, or purpose, or any/all of the good stuff that positive psychology has been showing again and again in study after study that makes humans flourish. Omg… what a dream…
Obligatory response to the impending “but happiness is subjective, and how do you measure it anyway”: Indeed, happiness is subjective, but so is, to an extent, the content that ‘engages’ people. And yet the algorithms that maximize engagement are out there, being deployed again and again in social network after social network. Not only that, but we as humans have developed sturdy enough models that reliable predict and affect peoples’ experience.
To name a few of the relevant people in the literature, there’s Mihaly Csikszentmihalyi, Sonya Lyubomirski, and Martin Seligman. They show that psychology can be used to understand how humans feel purpose and happiness, and that it can also be used to guide people into those directions. They use all kinds of methodologies, including my favorite, real time sampling through the experience sampling method. This is basically asking you at random moments throughout your day what you’re doing and how you feel (along with many other questions). This is asked to hundreds if not tens of thousands of people, and the resulting absurd amount of data can be used to create robust models.
Anyway, that’s not the point of my comment, but I figured it was better to be safe than sorry. My point was that it’d be amazing to have algorithmic feeds trained to make us flourish.