Awesome, not awesome.
#Awesome
“Using just the language in millions of old scientific papers, a machine learning algorithm was able to make completely new scientific discoveries…Using just the words found in scientific abstracts, the algorithm was able to understand concepts such as the periodic table and the chemical structure of molecules. The algorithm linked words that were found close together, creating vectors of related words that helped define concepts. In some cases, words were linked to thermoelectric concepts but had never been written about as thermoelectric in any abstract they surveyed. This gap in knowledge is hard to catch with a human eye, but easy for an algorithm to spot.” — Madeleine Gregory, Reporter Learn More from Vice >
#Not Awesome
“.The current flow of fake news and propaganda already fools too many people, even as digital platforms struggle to weed it all out. AI’s ability to further automate content creation could leave everyone from journalists to brands unable to connect with an audience that no longer trusts search engine results and must assume that the bulk of what they see online is fake. More troubling, the ability to weaponize such tools to unleash a tidal wave of propaganda could make today’s infowars look primitive, further eroding the civic bond between governments and citizens.” — Chris O’Brien, European Correspondent Learn More from VentureBeat >
What we’re reading.
1/ Government agencies are hopeful that machine learning can help authorities detect child sexual abuse photos online, but the technology has the potential to “mistakenly ensnare [people in] a federal investigation with great reputational harm.” Learn More from The New York Times >
2/ One professor argues that America’s open society will provide many advantages over China’s authoritarian political system when it comes to shaping the global order around artificial intelligence. Learn More from Bloomberg >
3/ The act of introducing machine learning systems into all aspects of our society is forcing us to have a conversation about fairness that was long overdue. Learn More from Harvard Business Review >
4/ The Supreme Court rules that it is not illegal to train algorithms on copyrighted material — potentially setting the precedent for scenarios like “creat[ing] an algorithm that could write songs like Ed Sheeran because I had trained it on his songs” to be seen as legal in the eyes of the court. Learn More from Towards Data Science >
5/ Google strikes a deal with the second-largest hospital system in the US to store and analyze data on millions of patients that could be use to more quickly identify medical conditions. Learn More from The New York Times >
6/ AI should be able to automate the most mundane tasks for doctors, hopefully saving their time and preventing burnout. Learn More from Brookings >
7/ The talks of AI replacing doctors is likely overblown — we should instead expect to see AI systems play a complementary role alongside them. Learn More from Scientific American >
Links from the community.
“Why do so many startups claim machine learning is their long game?” submitted by Samiur Rahman (@samiur1204). Learn More from Hacker News >
“Uber CEO backtracks after calling Saudi murder of Khashoggi “a mistake”” submitted by Avi Eisenberger (@aeisenberger). Learn More from Axios >
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