Many of you are aware that I keep track of [[IMPORTANT QUESTIONS]] in @RoamResearch. Here's a thread of questions I'm actively interested in and exploring. If you have any thoughts on any of them, feel free to respond directly to that tweet! What questions guide your learning?
Behavior is generally a function of the interaction between who a person is and what their context is. What person-side factors should be taken into account when trying to influence behavior, and how does that interact with what BeSci knows about contextual influences?
When do people search for information, what do they search for, and how do they search for it?
How might we best understand evidence and interpret that evidence to make future decisions?
What's the best research methods to better understand dynamic people in their dynamic environments? RCTs may not always be best.
How do online communities form and thrive? What are the behaviors of the members within them, and how do they interact with each other?
Can complex systems and chaos be structured to consistently produce unexpectedly positive outcomes? How can a network of people be designed towards the same purpose?
What might be a better incentive structure for applied behavioral science to encourage open reporting and mutual learning beyond just the publishing of successful case studies?
What different thinking styles can I adopt for what different sorts of problems, and how might I practice them? What situations would be forcing functions for effective thinking so that I can intentionally place myself into them?
What are the points where you want the user to be involved with the decisions, counterweighted by the friction of asking? More broadly- how much agency should we allow users and in what situations?
What is value, psychologically, and how do you get people to internalize value so they don't just value it in concept, but deeply desire and work towards it?
What causes people to adopt goals that they didn't already have?
What processes can I create to systematically generate creative insight and identify blind spots?
How can we tell when users will place a significant amount of effort into learning an application rather than just giving up at the first sign of difficulty? #onboarding
What is the role of pre-existing user mental models in app adoption and retention of the user, and how can those mental models be updated by the UX/product design?
What are the conditions where our values are or aren't an effective predictor of our behavior? Is this domain specific? What are meaningful ways to look at individual differences within a specific population?
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Feel free to reach out if your app is losing users bc they aren't accomplishing their goals.
Informed by behavioral science, game design, & a career helping over a dozen cos w/ continuous onboarding, I'm pretty good at improving adoption & retention through product decisions.
Start here and open new tabs with reckless abandon:
My trick is focusing on user goals, guiding the user involvement required to succeed, measuring / responding to success, failure, and progress, all through lenses and interventions inspired by what I've seen from behavioral scientists and game designers.
Odds are higher than I'd like that we lose Twitter, so please fill this out to stay in touch.
I don't have a newsletter or anything atm, but if I start one, or migrate to another social platform, I'll be sure to reach out so you can join me over there ❤️
I met the love of my life, made many friends, found community, clients, research opportunities, and jobs all through Twitter. I'll stick around as it goes down, but seeing the effect the leadership is having on the morale and lives of the people who built it is making me doubt.
Notion’s new AI functionality is interesting because it’s mindblowing to many while simultaneously trivial to anyone who’s played with the GPT-3 playground. Probably just a few prepackaged prompts triggered by buttons with some special effort towards using Notion formatting.
Here are some more examples of things you can do within GPT-3. It's not hard, you just need to play with it. At the top, you'll generally have a prompt that gives it a character and a scenario (sort of like improv). Then tell it what you want it to do
Notion's integration with GPT-3 is simultaneously awesome and uninspiring.
I say it's uninspiring because it doesn't take advantage of Notion's functionality or user workspace data at all. It seems to really just be prompt templates as buttons with no personalization.
Quick and dirty video on how to use GPT-3 playground to generate structured data automatically to paste directly into Tana.
In this case, I give it a list of birds, tell it what fields I want for each of them, and then GPT-3 will fill them in and format.
.@cazza42 uses @tana_inc to help her with birdwatching. I thought to myself, maybe she wants to record some data about each of the bird species, but that might take a lot of manual work. GPT-3 can do it for her!
If you click on this template link and make an account with @OpenAI, you can try it out! Just give it a different set of birds. Try it with pokemon, dogs, create monsters for your DnD campain... beta.openai.com/playground/p/q…
Love this! @reneedefour uses a bunch of fields here too… that may be useful to you, but remember that fields are optional prompts, not chores! When I tag a #gift, I have fields for who it’s for and whether I’ve given it already or not.
Can be as low or high friction as you want. Here you'll see two ways I captured a gift idea for Ally and both will show up with a LINKS_TO search. LINKS_TO is a wildcard field, and will pull up any relationship to nodes that reference "Ally."
Here's something a bit fancy - you can add this search directly to the #person supertag, so every person has a query for gift ideas that reference them. By putting PARENT in the value for the field, you make the live search dynamic.
Every user being verified as human would be valuable to Twitter as a public good. That's not visceral to individuals. One of the problems with verification as a paid service is that most people aren't worried about impersonation, so don't experience the pain directly.
I don't like the idea of making Twitter "pay to play" by charging for reach. Fortnite, one of the most profitable games in the world, never sells players an advantage against other players... it's all cosmetic, self-expression stuff. Game itself is free.
Generally agree with the thrust of this vid that Twitter could gain greater profitability by researching what's worth paying for... most people don't need to care about impersonation. Many top creators want better analytics, better API access, etc.