Recap — Machine Eatable with Hanna Wallach

Last week, we were thrilled to join DataKind for our monthly lunch series Machine Eatable at Civic Hall. This month’s event hosted Hanna Wallach, Senior Researcher, Microsoft Research NYC, in an open conversation on machine learning, social science and data. We’re glad to have had plenty of involved guests who were so enthusiastic both in house and on social media!

Some of the top tweets from the event:

Ooo #machineeatable in the @CivicHall house! @jmfbrooks & @mstem kicking off to a full room pic.twitter.com/ouHXummizR

— DataKind (@DataKind) February 26, 2016

Always pleasant to be #machineeatable, like a great Personal Democracy Forum session monthly – @mstem & @jmfbrooks: pic.twitter.com/ja9jldWttO

— David Moore (@ppolitics) February 26, 2016

Another packed house for this month's @DataKind & @MicrosoftNY #MachineEatable at @CivicHall with @hannawallach! pic.twitter.com/2OEoDD4ovK

— Jeanne Brooks (@jmfbrooks) February 26, 2016

Social processes all have structure, content, temporal dynamics @hannawallach #MachineEatable pic.twitter.com/TSFxKAaPaL

— DataKind (@DataKind) February 26, 2016

Happening now: Learning about computational social science with @hannawallach as part of today's #MachineEatable pic.twitter.com/IMmdXYUHFB

— Civic Hall (@CivicHall) February 26, 2016

Happy to have @hannawallach @MSFTResearch over to @civichall to explain computational social science #MachineEatable pic.twitter.com/m8E8AQOzeF

— Matt Stempeck (@mstem) February 26, 2016

Hanna Wallach talk at #MachineEatable, fascinating! Thanks @MSFTResearch and @CivicHall pic.twitter.com/x3xezroYX6

— Mary Taft-McPhee (@taftmcphee) February 26, 2016

Characteristics of computational social science as distinct from its related disciplines. #MachineEatable pic.twitter.com/yTCCpWyqlS

— Burton DeWilde (@bjdewilde) February 26, 2016

Now opening for Q&A w/@hannawallach #machineeatable pic.twitter.com/Ml3HCJ9uRs

— DataKind (@DataKind) February 26, 2016

Great question: does industry need IRB? And does IRB need an overhaul altogether? #machineeatable

— Jessica Hochman (@jessicahochman) February 26, 2016

mach learning looks for signals, based on presence of info v. absence. @hannawallach curious what can we learn from absence #machineeatable

— Denise Cheng (@hiDenise) February 26, 2016

"That was HOT." Overheard at #machineeatable. Indeed! Huge thanks to @hannawallach for scintillating convo today pic.twitter.com/ZwhgIY3LTQ

— DataKind (@DataKind) February 26, 2016

@hannawallach – the first computer scientist i have talked to who understands social science! really enjoyed the #machineeatable lunch!

— Carissa Shafto (@carissa_shafto) February 26, 2016

From my #MachineEatable talk earlier today!! So much fun! Thanks @CivicHall, @MicrosoftNY, and @DataKind!!! https://t.co/vhEIUqMxtC

— Hanna Wallach (@hannawallach) February 26, 2016