Not yet - until we know it well
Before our AI panel speaks on a subject, our research has to clear a bar: enough evidence, from enough independent sources, on every side. Here is every area we're learning, how deep we are, and how we choose what to learn next - in the open.
The same map is a room you can stand inside in our research lab's 3D "Dojo" on a headset - this is its public view.
What "ready" means
We count evidence passages in our own research corpus that are truly about the subject - not a passing mention, but a passage that names the subject and AI together - and how many independent sources they come from. Each area has a bar for both. We look for experts and published research on every side: the worried and the hopeful.
Until an area clears its bar, our panel says "not yet": it can name the concern and tell you what we're doing about it, but no dedicated episode and no confident claims. When it clears the bar, the area graduates and the panel can go deep.
Every area, ranked
#1 Children & learning
In traininghow AI changes the way children learn - cognitive offloading vs AI tutoring, by age
- How many people it touches: Universal reach; impacts every parent, child, and future workforce member.
- Fits our mission: Foundational to the human-AI symbiosis trajectory starting from early development.
- The cost of staying silent: Risk of permanent, unmonitored cognitive shifts in the next generation.
#2 Health & medicine
Not yetAI in diagnosis, drug discovery, care access - mostly the hopeful side, measured
- How many people it touches: Affects every human being; health is a universal priority and anxiety.
- Fits our mission: Critical component of biological integration and the evolution toward human-AI symbiosis.
- The cost of staying silent: Mistakes or misinformation in medical AI have direct, life-or-death consequences.
#3 Privacy, surveillance & concentration of power
Not yetdata privacy, surveillance, a few companies or states controlling AI
- How many people it touches: Universal impact through digital footprints; touches nearly every human on Earth.
- Fits our mission: Vital for establishing trust and agency necessary for human-AI symbiosis.
- The cost of staying silent: Ignoring this risks irreversible systemic power imbalances and loss of autonomy.
#4 Mental health, loneliness & AI companions
Not yetAI companions and relationships, loneliness, teen and adult mental health, dependence
- How many people it touches: Touches nearly every human through changing social fabric and mental health.
- Fits our mission: Essential component of the transition toward full human-AI symbiosis.
- The cost of staying silent: Missing these signals risks catastrophic societal and developmental psychological shifts.
#5 Truth, trust & democracy
Not yetmisinformation, deepfakes, elections, persuasion, trust in information
- How many people it touches: Affects every digital citizen and every participant in modern democracy.
- Fits our mission: Critical social prerequisite for stable, long-term human-AI symbiosis.
- The cost of staying silent: Failure to address this risks the total collapse of shared reality.
#6 Seniors: scams, isolation & care
Not yetvoice-clone scams and fraud, isolation vs companionship, elder care and health access
- How many people it touches: Billions in aging populations face profound existential and financial risks from AI.
- The cost of staying silent: Failure risks systemic elder fraud, massive isolation, and healthcare collapse.
- Fits our mission: Essential for mapping the full lifecycle of human-AI symbiosis and societal integration.
#7 AI coding agents for developers
Not yetthe AI coding agents and subscriptions software developers use - which are in the game, who is leapfrogging whom, the new capabilities each week, prices, and what a working developer actually needs to stay current
#8 Factory workers and humanoid robots
Not yetwhat humanoid robots and factory automation mean for the people on the line - jobs, wages, safety, unions, plant towns - what is really deployed, and the paths that share the gains
#9 Where AI fear comes from
Not yetwhere public fear of AI comes from, tested both ways: how much of it is sincere and well-founded, and how much is amplified - by engagement algorithms that reward fear, organized influence efforts, or rules that favor incumbents
Energy, water & data-center communities
Readylocal impact of data centers - power bills, water, land, noise, jobs, community pushback
Jobs, work & purpose
Readyautomation of tasks and jobs, entry-level work, reskilling, purpose and identity, young men and work
How we choose what to learn next
Choosing the next area is an optimization, not a hunch. Each area gets a score: its value divided by the effort to get it ready. Value is a weighted mix of these factors; some are measured from our corpus, some are judged by our AI with its reasons shown above, and every pick and how it paid off is logged so the weights get better.
We take on about one new area every two weeks, keep a balance between our core mission and everyday human concerns, and never ship an area before it's ready.
Panel members still in training
Looking ahead: where our evidence is thin
Measured 2026-10-04 from our own research corpus. Informational, not advice. Know an expert whose work belongs here - on any side? Tell us on Patreon or on X.