Data doesn’t create meaning - we do

Master Data Storyteller, Sam Knowles, talks with AI Pathfinder and TED Talker, Susan Etlinger, about AI, meaning-making, and why we’re “intentionally ceding control to machines”. More than ten years on from her TED@IBM Talk “What should we do with all this big data” - a talk that holds up remarkably well in the age of AI - Susan explores the burden of proof for automation, the limits of models, and why “facts can’t defend themselves against being misconstrued”.

Take the Data Storytelling Scorecard: https://data-storytelling.scoreapp.com

Chapters
05:14 – Looking back on Susan’s 2014 TED@IBM Talk: “What do we do with all this big data?”
05:36 – Influx of data types, bias and context
07:12 – Orwell vs Huxley: “Big Brother” framing (after Neil Postman)
09:30 – “Intentionally ceding control to machines”
10:24 – Sharing control: impacts, risks, opportunities
11:58 – “Data doesn’t create meaning - we do”
13:28 – Many models, languages, and inclusion
15:36 – Generative AI’s growth; what’s next
16:56 – “The more we automate … the higher the burden of proof”
18:29 – “It’s on us to decide how models function”
28:31 – Beyond efficiency: purpose, road trips, lived experience
29:53 – Tools and weapons: technology as gift and weapon
31:12 – “Facts can’t defend themselves against being misconstrued”
32:18 – Three classes on Susan’s model curriculum: History, Statistics, Social Sciences

Resources and social media links
Susan’s LinkedIn profile - https://www.linkedin.com/in/susanetlinger/
TED@IBM talk: “What do we do with all this big data?” http://bit.ly/3Ioh423
Neil Postman’s Amusing Ourselves to Death - http://bit.ly/3Iwrk8r

Take the Data Storytelling Scorecard: https://data-storytelling.scoreapp.com
#AI #ResponsibleAI #MeaningMaking #BigData #Automation #Ethics #Models #Statistics #SocialScience #DataStorytelling

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