Video instructions and help with filling out and completing Where Form 2220 Governing

Instructions and Help about Where Form 2220 Governing

Thanks everybody for coming this is a really exciting really exciting program it's being sponsored by the Graham school and three of our master's programs we have a master in biomedical informatics a master in data analytics and a master in threat and response management and these programs are all geared in some way toward analysis of data and and using machine learning and using analytics and part of the part of the part of the thrust for all the programs is to understand how to use data in an ethical way and how to use these algorithms that we're developing in a thoughtful way so I met Andrew a couple years ago at South by Southwest through a mutual friend we were both giving talks that year and we just had this amazing conversation talking about talking about our applications of machine learning so as a physician we're seeing the use of machine learning algorithms all over the hospital and all over medicine from things like predicting cardiac arrest to predicting sepsis to predicting patients that are going to be readmitted to the hospital and you know we just plow ahead with developing our models and developing our predictions and it was until I spoke to Andrew that it really stopped and thought about the implications of these algorithms and how they could be used in both good but also in also bad ways and it was really an eye-opening experience and ever since that meeting I've been really excited about bringing Andrew Andrew here to talk so andrew is a fascinating guy he used to work for the FBI cyber division he is the chief he's the chief privacy officer at mu de which is a data science company it just as really fascinating work and just is very very tuned in both to the technical analytic side as well as to the the legal and ethical implications of the work that we do so the title of Andrews talk is regulating artificial intelligence how to control the unexplainable and as you listen to Andrew I want you to keep in mind all of the not only the science and computer science of what we do but also the social implications and I hope that the questions that we talk about that we discuss afterwards will will will run the whole spectrum of the implications of this kind of technology so with that and you're excited to hear your talk and take it away wonderful thank you so much let me just switch here and while I am switching I will say thanks everyone for coming out thank you Sam Wendy Suzanne everyone I wanted to start today I should also say this is a condensed version of a longer talk and so I want folks here to keep me honest and try to keep this a little little casual so I'm gonna do my best to go off-script but I want to start today and and issues in fact by introducing you to a horse more specifically this is Hans or clever Hans as he became known as and Hans was one of the most famous horses in the world about a hundred years ago he was raised by a man named Wilhelm von ole stryn Hans lived in Germany and he was thought to be incredibly incredibly smart and his name so this is Hans that a public fair demonstrated his intelligence the folks that know about him just you know no spoilers so he was thought to speak German he could perform arithmetic he could count objects and much more here's a first-hand account of how he communicated numbers so small numbers were given with a slow tapping of the right foot with larger numbers he would increase his speed after the final tap you'd return his right foot to its original position and zero was expressed by a shake of the head the one example of a question he'd answer was I have a number in mind I subtract nine and I have three as a remainder what's the number I have in mind and Hans would unfailingly out the number twelve though Hans was quite simply the most interesting horse in the world and this is Hans with his owner in front of a board that he used to help him communicate and so Hans became world famous for his clear display of animal intelligence this is I didn't realize there were slides over there this is an article in the New York Times from 1904 a testing the honza's feats of intelligence and in this article the reporter recounted all of these feats instated I'm going to quote the facts here are not drawn from the imagination but are based on true observations and can be verified by the world's most preeminent scientists so what is going on here why am I starting a talk about machine learning by introducing you to a horse two reasons the first is that Hans illustrates something really profound in the way that humans approach the problem of intelligence and animals and machines and in humans so in 1911 a psychologist named Oscar folks'd published this book in which he demonstrated that Hans wasn't actually that clever at all in every case pons was watching the reactions of his trainer and reacting to involuntary cues and the body language of that trainer and so this wasn't a hoax vanastra didn't know he was creating these cues but while we were assessing the intelligence of clever Hans clever Hans actually demonstrated something very deep about our own intelligence and that is we have significant cognitive biases the way we process information is prone to irrational choices one of the cognitive biases we have baked into our brains is called cognitive bias it causes us to look for things that conform or existing hypotheses or beliefs and so clever Hans is really a testament to the fact