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Philip H. Hayes

From Wikipedia, the free encyclopedia

Philip H. Hayes
Philip Hayes.png
Member of the U.S. House of Representatives
from Indiana's 8th district
In office
January 3, 1975 – January 3, 1977
Preceded byRoger H. Zion
Succeeded byDavid L. Cornwell
Member of the Indiana State Senate
In office
Personal details
Philip Harold Hayes

(1940-09-01) September 1, 1940 (age 78)
Battle Creek, Michigan
Political partyDemocratic
Alma materIndiana University, Indiana University Law School

Philip Harold Hayes (born September 1, 1940) was a U.S. Representative from Indiana.

Born in Battle Creek, Michigan, Hayes attended Rensselaer (Indiana) Elementary School. He graduated from Rensselaer High School, 1958. B.A., Indiana University, 1963. J.D., Indiana University Law School, 1967. He was admitted to the Indiana bar in 1967 and District of Columbia bar in 1977. He was a lawyer in private practice. Deputy prosecuting attorney, Vanderburgh County, Indiana from 1967 to 1968. He served as member of the Indiana State senate from 1971 to 1974.

Hayes was elected as a Democrat to the Ninety-fourth Congress (January 3, 1975 – January 3, 1977). He introduced the National Climatic Program Act of 1975, a version of which eventually became law as the National Climate Program Act in 1978.[1][2] He was not a candidate for reelection in 1976, but was the unsuccessful primary election challenger to three-term incumbent Vance Hartke for nomination to the United States Senate. County attorney, Vanderburgh County, Indiana from 2001 to 2002. He is a resident of Evansville, Indiana.

YouTube Encyclopedic

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  • ✪ The Rise of the Machines – Why Automation is Different this Time


How long do you think it will take before machines do your job better than you do? Automation used to mean big stupid machines doing repetitive work in factories. Today they can land aircraft, diagnose cancer and trade stocks. We are entering a new age of automation unlike anything that's come before. According to a 2013 study almost half of all jobs in the US could potentially be automated in the next two decades. But wait hasn't automation been around for decades? What's different this time? [Intro] Things used to be simple. Innovation made human work easier and productivity rose. Which means that more staff or services could be produced per hour using the same amount of human workers. This eliminated many jobs it also created other jobs that were better which was important because the growing population needed work. So in a nutshell innovation higher productivity fewer old jobs and many new and often better jobs overall this worked well for a majority of people and living standards improved. There's a clear progression in terms of what humans did for a living. For the longest time we worked in agriculture. With the Industrial Revolution, this shift into production jobs and as automation became more widespread, humans shifted into service jobs and then only a few moments ago in human history the Information Age happened. Suddenly, the rules were different. Our jobs are now being taken over by machines much faster than they were in the past. That's worrying of course... but innovation will clearly save us, right? While new information age industries are booming, they are creating fewer and fewer new jobs. In 1979, General Motors employed more than 800,000 workers and made about 11 billion U.S. dollars. In 2012, Google made about 14 billion U.S. dollars while employing 58,000 people. you may not like this comparison, but Google is an example of what created new jobs in the past - Innovative new industries. Old innovative industries are running out of steam. Just look at cars - when they became a thing 100 years ago, they created huge industries. Cars transformed our way of life, our infrastructure, and our cities. Millions of people found jobs either directly or indirectly. Decades of investment kept this momentum going. Today, this process is largely complete. Innovation in the car industry does not create as many jobs as it used to. While electric cars are great and all, they won't create millions of new jobs. But wait... what about the internet? Wome technologists argue that the Internet is an innovation on a power of the introduction of electricity if we go with this comparison we see how our modern innovation differs from the old one the internet created new industries but they're not creating enough jobs to keep up with population growth or to compensate for the industries the internet is killing at its peak in 2004 blockbuster had 84,000 employees and made 6 billion US dollars in revenue in 2016 Netflix had 4,500 employees and made 9 billion dollars in revenue for take us for example with a full-time team of just 12 people courtesan 2 reaches millions of people a TV station with the same amount of viewers needs way more employees innovation in the information age doesn't equate to the creation of enough new jobs which would be bad enough on its own but now a new wave of automation and a new generation of machines is slowly taking over to understand this we need to understand ourselves first human progress is based on the division of labor as we advanced over thousands of years our jobs became more and more specialized while even our smartest machines are bad at doing complicated jobs they are extremely good at doing now redefined and predictable tasks this is what destroyed factory jobs but look at a complex job long and hard enough and you'll find that it's ready just many narrowly defined and predictable tasks one after another machines are on the brink of becoming so good at breaking down complex jobs into many predictable ones but for a lot of people there will be no further room to specialize we on the verge of being out completed digital machines do this fly machine learning which enables them to acquire information and skills by analyzing data this makes them become better at something through the relationships they discover machines teach themselves we make this possible by giving a computer a lot of data about the thing we wanted to become better at so a machine all the things you bought online and it will slowly learn what to recommend to you so you buy more things machine learning is now meeting more of its potential because in recent years humans have started to gather data about everything behavior weather patterns medical records communication systems travel data and of course data about what we do at work what we've created by accident is a huge library machines can use to learn how humans do things and learn to do them better these digital machines might be the biggest job killer of all they can be replicated instantly and for free when they improve you don't need to invest in big metal things you can just use the new code and they have the ability to get better fast how fast if your work involves complex work on a computer today you might be out of work even sooner than the people who still have jobs in factories there are actual real-world examples of how this transition might be happening a San Francisco company offers a project management software for big corporations which is supposed to eliminate middle management positions when it's hired for a new project the software first decides which jobs can be automated and precisely where it needs actual professional humans it then helps assemble a team of freelancers over the Internet the software then distributes tasks to the humans and controls the quality of the work tracking individual performance until the project is complete ok this doesn't sound too bad while this machine is killing one job it creates jobs for freelancers right well as the freelancers complete their tasks learning algorithms track them and gather data about their work and which tasks it consists of so what's actually happening is that the freelancers are teaching a machine how to replace them on average this software reduces costs by about 50% in the first year and by another 25% in the second year this is only one example of many there are machines and programs getting as good or better than humans in all kinds of fields from pharmacists to analysts journalists to radiologists cashiers bank tellers or the unskilled worker flipping all of these jobs won't disappear overnight but fewer and fewer humans will be doing we'll discuss a few cases in a follow-up video but while jobs disappearing it's bad it's only half of the story it's not enough to substitute old jobs with new ones we need to be generating new jobs constantly because the world population is growing in the past we have solved this through innovation but since 1973 the generation of new jobs in the US has begun to shrink and the first decade of the 21st century was the first one where the total amount of jobs in the u.s. did not grow for the first time in a country that needs to create up to 150,000 new jobs per month just to keep up with population growth this is bad news this is also starting to affect standards of living in the past it was seen as obvious that with rising productivity more and better jobs would be created but the numbers tell a different story in 1998 US workers worked a total of 194 billion hours over the course of the next 15 years their output increased by 42 percent but in 2013 the amount of hours worked by US workers was still 194 billion hours what this means is that despite productivity growing drastically thousands of new businesses opening up and the u.s. population growing by over 40 million there was no growth at all when the number of hours worked in 15 years at the same time wages for new university graduates in the US have been declining for the past decade while up to 40 percent of new graduates are forced to take on jobs that don't require a degree productivity is separating from human labour the nature of innovation and the information age is different from everything we encountered before this process started years ago and is already well underway even without new disruptions like self-driving cars or robot accountants it looks like automation is different this time this time the machines might really take our jobs our economies are based on the premise that people consume but if fewer and fewer people have decent work who will be doing all the consuming are we producing ever more cheaply only to arrive at a point where too few people can actually buy all our stuff and services or will the future see a tiny minority of the super rich who own the machines dominating the rest of us and does our future really have to be that grim while we were fairly dark in this video it's far from certain that things will turn out negatively the Information Age and modern automation could be a huge opportunity to change human society and reduce poverty and inequality drastically it could be a seminal moment in human history we'll talk about this potential and possible solutions like a universal basic income in part two of this video series we need to think big and fast because one thing's for sure the machines are not coming they are already here this video took us about 900 hours to make and we've been working on it for over nine months projects like this one would not be possible without your support on if you want to help us out and get a personal Kurzgesagt bird in return that would be really useful we based much of this video on two very good books the rise of the robots and the second Machine Age you can find links to both of them in the video description highly recommended also we make a little robot poster you can buy it and a lot of other stuff in our DFTBA (Don't Forget To Be Awesome) shop. This video is part of a larger series about how technology is already changing and will change human life forever if you want to continue watching we have a few playlists


  • United States Congress. "Philip H. Hayes (id: H000392)". Biographical Directory of the United States Congress.

 This article incorporates public domain material from the Biographical Directory of the United States Congress website

U.S. House of Representatives
Preceded by
Roger H. Zion
Member of the U.S. House of Representatives
from Indiana's 8th congressional district

Succeeded by
David L. Cornwell

This page was last edited on 16 May 2019, at 08:24
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