Welcome to our first ever Machine Learnings letter 🙂
We took the time to go back through all of our previous articles to pick out the 7 most read/clicked posts by our community over the past 294 days.
How technology endowed with creative intelligence changes the way companies generate and distribute content.
Source: AI Is Already Entertaining You
Created by Seoul based artistic duo Shinseungback Kimyonghun, ‘Animal Classifier’ is an AI trained to divide animals into arbitrary classifications to foreground the imperfections and edge cases in classification systems.
Artificial Intelligence and the fourth industrial revolution has made some considerable progress over the last couple of years. Most of…
The creative reach of the individual is expanding.
I would like to suggest that machine learning can help us to simplify design tools without limiting their expressivity, without taking creative control away from the designer.
Source: Rethinking Design Tools in the Age of Machine Learning – Medium
Even brilliant algorithms need thoughtful design.
Business process redesign and better training are important, but better use cases – those real-world tasks and interactions that determine everyday business outcomes – offer the biggest payoffs. Privileging smarter algorithms over thoughtful use cases is the most pernicious mistake I see in current enterprise AI initiatives. Something’s wrong when optimizing process technologies take precedence over how work actually gets done.
Source: AI Won’t Change Companies Without Great UX – HBR
“By making our code and data open-source, we are inviting feedback and conversation about CivicScape in the belief that many eyes make our tools better for all,” the company writes on Github. “We must understand and measure bias in crime data that can result in disparate public safety outcomes within a community.”
Our shoddy thinking about the brain has deep historical roots, but the invention of computers in the 1940s got us especially confused. For more than half a century now, psychologists, linguists, neuroscientists and other experts on human behaviour have been asserting that the human brain works like a computer.
Once we have AIs doing work for us, we’ll need to invent new jobs for humans who are testing the AIs’ results for accuracy and prejudice. Even when chatbots get incredibly sophisticated, they are still going to be trained on human language. And since bias is built into language, humans will still be necessary as decision-makers.
Hyper-intelligent algorithms are not going to take over the world for these five reasons.