Better Knowledge for a Hopeful Future | Interview with William Ammerman

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Alexander Ferguson 0:00
In our last video technologists and author William Ammerman spoke about the dangers of the modern era of digital marketing, and how protecting ourselves requires a deeper knowledge of new technologies. In our third and final video Emerman walks us through some of the terms we’ve heard many times in the media, but might not totally understand, he then gives us a hopeful story of how these technologies can be used for the public good.

William Ammerman 0:23
An algorithm is a set of instructions, let’s be very, super clear about that. It’s a set of computer instructions, you might follow an algorithm in your morning ritual of turning the alarm off and getting up out of bed. Now, that is an algorithm of sorts, you reach over there, the alarm goes off, you reach over, you turn off the alarm, lay there for a few seconds, you swing your feet out of bed, sit on the edge of your bed for a second you stand up, every step in that process could be recorded as kind of a step by step procedure. Another way to think about algorithms is that they work together, they work reciprocally, they interact with one another great example. There was an auction at Christie’s where they auctioned off this piece of artwork, and I think it’s sold for something like $40,000. And it was a painting painted by Gann algorithm. And this algorithm really took the combination of two algorithms working in concert, actually kind of competitively. One algorithm was designed to create works of art, billions of combinations that it thought were human, like, the other algorithm judged the out the output of the first algorithm. So the first algorithm is just designed to make pretty pictures. The second algorithm is designed to judge which ones humans will like based on machine learning. So now you’ve got two algorithms working hand in hand to produce a piece of artwork that actually sold for you know, $40,000 at Christie’s Auction House,

Alexander Ferguson 2:00
but how can these algorithms be used to better serve the public good Everman offers a hopeful story.

William Ammerman 2:07
Something very interesting happened when Wikipedia was created, Wikipedia was created largely by human contributors who were contributing information into Wikipedia. And over time, Wikipedia got populated. And somebody looked at it and said, You know, it’s a very strange thing. But Wikipedia seems to be biased in favor of male scientists. They did a study on this and they realize that, yeah, women, female scientists are vastly underrepresented in Wikipedia. And they started to kind of go backwards and try to deconstruct that. And they figured out that the majority of Wikipedia contributors were men. And I don’t know exactly what the percentages were, but more men were contributing to Wikipedia than women. And so they actually wrote an algorithm to go in and identify this bias and start to correct for it. So they started to try to, you know, intentionally balance the scales and try to say, Okay, there’s lots of brilliant female scientists, they just happen to be underrepresented by a bias in the system, we’re going to actually use an algorithm to go back and try to correct that bias. So not only can algorithms produced biases, unintentionally, but the good news is if we identify those algorithms, we can actually use algorithms to correct biases and identify them.

Alexander Ferguson 3:33
That concludes the audio version of this episode. To see the original and more visit our UpTech Report YouTube channel. If you know a tech company, we should interview, you can nominate them at UpTech report.com. Or if you just prefer to listen, make sure you subscribe to this series on Apple podcasts, Spotify or your favorite podcasting app.