going to be swimming here for a bit..
you come too.
– – –
from reinventing hollywood series:
– – – –
jan 2015 – tech
interview (via this tweet):
instead of focusing on what/how.. can we focus on why
8 min – lots of focus on success – career ness – hiring ness
9 min – creating a population of problem solvers.. how: meta level – highly predictable/changeable.. ie: working memory/attention/long-term memory – strong predictors of life outcomes… meta-cognition: how you reflect.. mindset/personality: important work from duckworth/dweck… creativity… et al… predictable to life outcomes.. grades…
12 min – my approach to world.. very large data sets.. i apply algorithms.. none of which are robot proof… things that are typically modeled by others.. ie: can’t give it to you in a notebook.. so what parents model for kids.. rather than directive behavior (more negatively associated).. it’s what you model (not as dictator) is what brings success to your kids..
15 min – big differentiator.. focus on process in sciences.. you gain from role models/mentors… skills i could learn anywhere
uni is not a great predictor of future outcome… ir: comp sci from stanford.. less than a predictor than a phd in anything from anywhere… best comp sci school in the world..not a predictor.. but the kind of person… study elongated degree.. were more creative problem solvers.. ie: phd in english from anywhere more predictive than ba in comp sci from stanford
18 min – huge focus on predicting success in the hiring world…
interesting that this is paired with nature of a human in the future.. seems so not our potential..
19 min – keeps giving enormous data base – ie: millions of people… but what if the data you’re looking at .. could be irrelevant.. to systemic change we need/crave…
22 min – expression of sentiment – via tweets – as predicable. much less about skill set.. but rather their engagedness/passion/motivation is the real clue
24 min – on these skills not being novel…. not coding/stats…. those are tools.. not core predictors… but rather – non cognitive skills.. meta learning… universal across all domains… predictive in 3-5 yr olds… fascinating in education to look and see i have no idea what 3-5 yr olds will become.. but if they sustain these soft skills… to adult hood.. they will be successful..
26 mi – on these skills – 21 cent – same as 17th cent… how general/human these skills are
27 min – how do people get better at problem solvers… so her company… we wanted to completely rethink what ed is.. prospect about producing happy/healthy/productive people…
muse gives these daily: 1\ drawing when i want to share it 2\ audio when i want to share it 3\ single question a day… – gives a prediction of success in future
and we send single message today to parents,…. ie: here’s the one thing you can do as a parent to have kids get more successful…
put this into tech is complex… listening to child.. giving text message to the parent…
app chip ness
31 min – a simple system that can infer about a young child.. than send a message to facilitate that.. all delivered through sms
33 min – future of ed – what muse does.. as you’re grading.. muse gives insight – ie: don’t/do give harsh feedback… so that grading/feedback is more useful.. – muse humanizes the art of being a prof.. how to motivate people better.
wasting tech .. no?
spot on tech capability – yet caught in a cycle of perpetuating not-us ness.
36 min – ai of future is not ai .. artificial intell. but rather augmented intell…
37 min – over next 20-30 yrs.. what we think of as what it means to be human will fundamentally changed..
hoping we wake up.. and it’s less about career.. and more about eudaimonia..
so much good she’s saying.. hope she is open – to all of us – to getting to real us ness..
mar 2016 –
Resolving Tensions Between Individual Privacy and National Security (video – 1.5 hr)
feeling like in movie – groundhog day – cindy cohn
on not solvable.. so need to find a balance… – jane
perhaps it appears not solvable.. because we’re trying to fix it in an assumed box.. ie: what data are we focusing on.. what data are we letting people spout.. ps in the open et al
59 min – on big data techniques… law enforcement have a lot more info on us than they ever have… – cindy
just wrong info… our focus is off.. based on fear.. rather than living.. (ie: rather than self-talk as data)
We’re live with #WhatsNowNY! Watch here: https://t.co/SpH9LepudG @CapgeminiAIE
Original Tweet: https://twitter.com/reinventnet/status/942900625854967808
dec 2017 – gershenfeld brothers (neil, alan, joel cutcher).. live – on new book – designing reality
Preparing for the Third Digital Revolution: Fabrication
We’re in the early stages of the Third Digital Revolution and few people understand what’s about to hit them. The first two digital revolutions – in computers and communications – transformed the world, but the next revolution in fabrication is poised to make an even bigger impact
pete: about new book designing reality by 3 brothers – published nov 2017[https://www.amazon.com/Designing-Reality-Survive-Digital-Revolution/dp/0465093477]
told about all above stuff.. ie: class of make whatever you want.. i was asking how to do digi fab.. they were asking why.. which was personal fab
1000 labs.. that’s how many cities in world..
so let’s experiment in place w 1000 .. everyone playing.. ie: short bp
started fab academy.. @DigiFabAcademy
million is interesting #.. and # of computers .. # of towns on earth
bn stage… there’s a problem.. nearly universal.. to make machine that makes machine need electronic components.. so started studying digital materials not digital designs.. so can climb on structure they’re building
at rate of current projects.. 10-15 yrs each
tillion fab labs.. – # of objects.. if built me.. on the machine i showed you it would take (tons of ) years.. but if do it by biology.. 1 second
how to bootstrap civilization on mars
this is all great.. just not sure we need all this for world peace.. (seems perhaps this is why we’ve got a hold up w gershenfeld ness)
at point on curve there were winners/losers.. rest of story
trust niel about idea – science.. just don’t trust w society (labor and employment). i’m social science.. alan is humanities..
took a few weeks to set up camp.. took about 3 yrs to get social/institutional in place..
begs design for social.. ie: 2 convos as the day
imagine.. power of this tech.. what divides might this create.. we couldn’t find any social scientists or policy makers.. studying this.. we have a 2nd chance right now w fab
6 bn don’t even have foundation for powerful capabilities Neil showed..
joel: tech could reach them.. it’s social decisions keeping us..
back to Alan: fab literacy is almost like a meta literacy.. literacies on literacies to do what Neil shared.. so not just access.. need literacies.. also need an ecosystem.. key to ecosystem is mentors .. there are very few mentors in ecosystems..we need mechs for that
so.. let’s let that be our focus.. deep/simple/open enough
joel: part too is the platforms
joel: about jobs/employment.. look at fab ecosystem.. it’s not a workplace.. how to address in that it’s not a workplace.. moore’s law is a social construct.. fablab is distributed ecosystem.. how to have r&d stay ahead of boulder when don’t have single hierarchy to drive it..
alan: how to keep bad people from doing bad things
alan: how to set up so literacies needed are learned (paraphrase)
begs.. design for no train.. ie: simple enough.. based on curiosity.. what we already have in us
neil – on the barcelona fablabs.. wanting food bank more than fab lab.. pivot.. to make whole district as maker district.. a microcosm of brexit.. elections.. it all assumes work is something you don’t want to do to get money to get something you want.. fundamentally challenging what is work and what is money.
joel: embedded in your question is a market model.. what neil is suggesting is not a market model.. how do we think about rules of game for very diff world..
neil: it’s a mistake to focus too much on the widget much as i do
neil: been working on local micro energy
alan: making things is deeply human.. so can be a bridge across these divides
q: sounds a little naive.. so how would you fitting into the world in which we already exist.. joel: there is enormous econ interest.. this early stage we should be talking about assumptions..
neil: key.. 1\ nobody is pushing.. this doubling is people opting in.. 2\ as expanding.. anywhere labs are.. people use for art/play/business.. they are magnets for innovation.. so not.. rich places doing rich things and poor places doing poor things.. so.. we’re trying to keep up to the pull
alan: fablab takes you off screen into real world.. why you see so much joy in these fablabs
q: how do you teach people about this joel: pbl led to remake learning.. about 100 fablabs where pbl is happening.. on ground w people in neighborhood and part of ecosystem where learning is happening in diff way..
neil: diff between well being and work.. that’s what’s happening..
q: what have learned and what can we anticipate that can be negative in the last 35 yrs.. joel: that’s what the whole book .. the serious discussions.. a call to action on what you’re saying
right in front of you guys..
neil: once gets going.. trash goes away.. things building.. .can unbuild
pete: do you think we can achieve this in a way.. that’s going to be as profound as these last 2 revolutions.. neil: i’m not a social change activist.. but.. seeing 100 000 people so far.. i thought the tech road map i showed you was hard.. what i neglected was.. we tried to work w non profits.. tech road map is doing fine.. the thing i hadn’t accounted for.. need to really reinvent.. find innovators to make new kinds of orgs..
a nother way as infra
alan: wondered what would be like if we had a sister..