It doesn't know where it's going so last month you might have noticed something Google actually announced that they had met the exact Location of every single residence and every single business in the entirety of France every single house number Now if you were tasked with that job What would you need me a hundred people for a year?

What did Google do Google used an algorithm which did that entire process in one hour? They met every single residence and business exact location in one hour. How did they do it? well, they started with Google Street View which is hundreds of millions of images and They used a machine learning algorithm Machine learning algorithms are algorithms that you don't really program in the traditional sense But you just give it a sense of what you're trying to do and it figures it out so in this case they took a few hundred street numbers and kind of circled them and Said to the algorithm look for stuff like this and read them the algorithm did the rest Very similar with this with this project looking for these areas.

It's got green arrows are areas that are called mitosis These are the most terrifying parts of the breast cancer tumor These were hand marked up by a team of four expert pathologists working in unison That's because actually doing this is very very difficult to any two pathologists on the team only agreed with each other 50% of the time they then took this expert assessment for thousands of breast cancer images and they sent it to a machine learning algorithm the machine learning algorithm then automatically identified mitosis and thousands more images and it had a 60% overlap with the shared committee view so Algorithm is better than any expert pathologist in the world and identifying this incredibly difficult thing of ptosis This is actually happening again and again I was involved in a project a couple of years ago for Merck and they wanted to know can we find Molecules ahead of time which are likely to be toxic and you probably know the punchline The team that I was involved with did not try and program that but instead gave examples of a whole lot of toxic molecules to a machine learning algorithm It took only two weeks for the whole project and at the end of it Was a system that was much better than Merck and much better than anybody in academia or industry had ever developed for identifying toxic molecules I'll tell you something else in each one of these systems They were developed by people with no previous background in this area So for example this in the Merck example both developed by machine learning experts who had no previous background in biology and Generally these things take days or maybe a couple of weeks It's not just in medical and imaging areas This is also being used in language in fact on your Android phone when you're using Voice recognition it's using this kind of machine learning system.

And in fact, I'll tell you something else Not only are all these best in class algorithms using machine learning rather than traditional programming They're using the exact same algorithm one algorithm It's called deep learning and it's actually based on the computing process that the human brain uses We're now at a point whether the hardware the computer hardware can Approximate that well enough that we are seeing the best in class performance other examples the world's best algorithm for Translating English speech into Mandarin speech in the original inflection of the original speakers voice again is a deep learning algorithm So we're at a point now where a single algorithm, which is actually getting multiplicatively better every year The more data you give it the more computing power you give it the better It gets is now at or better than human performance at the very things Which humans spend most of their time doing all the blue areas here are countries where over 80% of?

employment is in services More specifically for example in the US 55% of employment is actually an information processing. This is the exact thing that these algorithms are now at or better than human performance at and getting multiplicatively better every year So there are opportunities for example for your organizations these same algorithms are actually also the best in the world at identifying churn credit scoring at the Prioritization you know any of your organizations that that use these approaches will get ahead those that don't will fall behind So it has a big commercial opportunity as well I think about the other side every single organization which is doing this is actually replacing Human jobs the most common jobs with machines this has happened once before And the Industrial Revolution Before that most people were working in manufacturing and agriculture Suddenly those jobs didn't exist anymore because machines did it better Did you know that the decades afterwards 80% of workers were much worse off in fact 80% of workers?

Did not have a basic living wage Incredibly disruptive What is this going to mean for us when all of the people currently in the services sector of many of them find themselves? Literally unable to add economic value because the computers are getting more applicatively better every year So you might be thinking this is all very nice in theory, but you know wouldn't you expect to have seen something in practice by now?

Wouldn't you expect to have already seen that like the the value of human capital is not keeping up with the improvements in productivity? Well, yes, you would In fact the value of human capital as expressed in median income has been flat for the last 15 years And it's now starting to go down at the very same time That productivity overall in the economy has kept increasing and increasing So what I wanted to tell you today is be aware of the exciting opportunities for all of your organizations from machine learning But also be aware of the threats to our socioeconomic systems that will come in the future And let's start to think about both the opportunities and the threats