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Page 82 of 107

Rip it Up and Start Again

presented by Simon Bendall

So, why am I doing this? Rip it Up is such a rich resource, espe­cial­ly in the ear­ly years. Nothing else was real­ly doc­u­ment­ing pop cul­ture, let alone the nascent alter­na­tive cul­ture that was start­ing to boil up. The pre­vail­ing atti­tude in the main­stream media of the day seemed to be that pop music was kid’s stuff.

Talking About Visual Thinking

presented by Chris McDowall

Sometimes I think about these sorts of work­ing graph­ics as a sort of men­tal scaf­fold­ing. In the act of ren­der­ing data, or draw­ing our thoughts, we assem­ble a con­struct to hang oth­er con­cepts from. So it’s a con­struct that can be extend­ed or mod­i­fied or dis­as­sem­bled and turned into some­thing new.

Douglas Rushkoff WebVisions Portland 2016 Keynote

presented by Douglas Rushkoff

Google just has to grow. It has to keep grow­ing. But Google grows at its own per­il. Google grew so much that what hap­pened? It out­grew Google. Google had to become what? Alphabet. Now what is Alphabet? Alphabet is not Google. Alphabet is a hold­ing com­pa­ny. So Google’s new busi­ness as Alphabet is to do what? It’s to buy and sell tech­nol­o­gy com­pa­nies. So, once a com­pa­ny becomes just too big to flip any­more, it becomes a flip­per of oth­er companies.

What Our Algorithms Will Know in 2100

presented by Ed Finn, Lee Konstantinou

A lot of the sci­ence fic­tion I love the most is not about these big ques­tions. You read a book like The Diamond Age and the most inter­est­ing thing in The Diamond Age is the medi­a­tron­ic chop­sticks, the small detail that Stephenson says okay, well if you have nan­otech­nol­o­gy, peo­ple are going to use this tech­nol­o­gy in the most pedes­tri­an, kind of ordi­nary ways.

What Should We Know About Algorithms?

presented by Ed Finn, Ian Bogost, Jennifer Golbeck

When I go talk about this, the thing that I tell peo­ple is that I’m not wor­ried about algo­rithms tak­ing over human­i­ty, because they kind of suck at a lot of things, right. And we’re real­ly not that good at a lot of things we do. But there are things that we’re good at. And so the exam­ple that I like to give is Amazon rec­om­mender sys­tems. You all run into this on Netflix or Amazon, where they rec­om­mend stuff to you. And those algo­rithms are actu­al­ly very sim­i­lar to a lot of the sophis­ti­cat­ed arti­fi­cial intel­li­gence we see now. It’s the same underneath.

What Do Algorithms Know?

presented by Ed Finn

The Tyranny of Algorithms is obvi­ous­ly a polem­i­cal title to start a con­ver­sa­tion around com­pu­ta­tion and cul­ture. But I think that it helps us get into the cul­tur­al, the polit­i­cal, the legal, the eth­i­cal dimen­sions of code. Because we so often think of code, and code is so often con­struct­ed, in a pure­ly tech­ni­cal frame­work, by peo­ple who see them­selves as solv­ing tech­ni­cal problems.

Behind the Screen: The People and Politics of Commercial Content Moderation

presented by Sarah T Roberts

When I asked my peers and my pro­fes­sors if they’d ever heard of this type of work, two things hap­pened. The first thing is that they said no, they had­n’t. The sec­ond thing they said, which is prob­a­bly what you’re think­ing, is, ​“Well, can’t com­put­ers do that?” And in fact the answer to that is no.

The War Inside: How Will the Human Body be Enhanced for War?

presented by Andrew Herr

I want you to imag­ine the abil­i­ty to take a few drops of some­one’s blood, to com­bine that with some cog­ni­tive and some phys­i­cal test­ing, and to be able to fig­ure out where that per­son is going to be most effec­tive in your military. 

Holding To Account

presented by Anil Dash

I’m glad those social net­works pro­vide those ser­vices. I think it’s impor­tant for the dia­logue to hap­pen that way. But it can’t be the only way for us to have pub­lic dis­course. Online, we only have these spaces that are owned by pri­vate com­pa­nies. We don’t have pub­lic parks.

Page 82 of 107

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