A presentation at DevOpsDays Edinburgh in in Edinburgh, UK by Sasha Rosenbaum
When is AI taking over my job SASHA ROSENBAUM
My name is Sasha Rosenbaum I work for #Microsoft I’ve been #building #things with #technology for the last 13 years
Definitions
Intelligence The ability to accomplish complex goals
Artificial Intelligence The ability of a machine to perform tasks commonly associated with human intelligence
Machine Learning Machine learning (ML) is the science of getting computers to act without being explicitly programmed. ML is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
Stand up Touch your nose How exactly did you do that?
Superhuman AGI Superhuman artificial general intelligence is the ability of a machine to accomplish any goal as well or better than humans
Opinions Superhuman AGI is not possible Superhuman AGI will be achieved within the next couple of decades We only need to worry about conscious machines
Goal ≠ Purpose
Does Artificial Intelligence have to be that smart?
So, whom can these “narrow” intelligence systems replace?
Occupation Clerks Cashiers Cooks Taxi drivers Bakers Waiters Accountants Paralegals Likelihood of computerization 86-99% 83-97% 81-94% 89% 89% 94% 94% 94%
Occupation (United States) Office and administrative support occupations Sales and related occupations Food preparation and serving related occupations Transportation and material moving occupations Management occupations Education, training, and library occupations Production occupations Healthcare practitioners and technical occupations Business and financial operations occupations Construction and extraction occupations Personal care and service occupations Installation, maintenance, and repair occupations Building and grounds cleaning and maintenance occupations Computer and mathematical occupations Number of Employees 23,081,200 15,747,800 13,206,100 10,274,200 9,533,100 9,426,500 9,356,900 8,751,500 8,066,800 6,812,500 6,419,700 5,905,400 5,654,100 4,419,000
But wait, I am a “knowledge” worker, surely it isn’t easy to replace me?
Imagine a landscape of human competence, having lowlands with labels like arithmetic and rote memorization, foothills like theorem proving and chess playing, and high mountain peaks labeled locomotion, hand-eye coordination and social interaction. Advancing computer performance is like water slowly flooding the landscape. A half century ago it began to drown the lowlands, driving out human calculators and record clerks, but leaving most of us dry. Now the flood has reached the foothills, and our outposts there are contemplating retreat. We feel safe on our peaks, but, at the present rate, those too will be submerged within another half century. - Hans Moravec
Rate of progress
Rate of adoption
So, what do we do now?!?
The world will change in ways we do not anticipate
Luddites English workers in 1811–16, who destroyed machinery, especially in cotton and woolen mills, that they believed was threatening their jobs.
Selfishly speaking, resisting progress is a bad idea
Pensions Problem $$$
Which jobs will linger? vPerception and manipulation vCreative intelligence vSocial intelligence
Occupation Therapists Engineers Scientists Teachers Chefs Lawyers Event planners Software Developers Likelihood of computerization 0.3-34% 0.4-96% 0.4-67% 0.7-26% 1% 3% 4% 4-13%
AI Ethics
Bias is a property of information
We must build AI responsibly
Build AI responsibly!
Thank You! @DivineOps
Resources Tegmark, M. Life 3.0 - Being human in the age of artificial intelligence. Frey, C.B. & Osborn, M. A. The Future Of Employment: How Susceptible Are Jobs To Computerisation? Oxford University Kurzweil, R. The Singularity is near. When humans transcend biology.
When infrastructure automation concepts were first introduced, many IT professionals worried about automating themselves out of a job. But as we are dealing with our day to day challenges, Artificial Intelligence is making progress, achieving human parity in many areas of expertise. As AI is changing retail, healthcare, finance, manufacturing and even creative arts, is it time to ask when it is going to arrive in IT?
In this talk, I will overview the definitions of AI, ML and Deep Learning, the differences between AI and traditional programming and the relative difficulty of tasks that could be solved by AI. I will discuss the incredible progress that was made in the field in recent decades, and review which types of jobs are less likely to be taken over by machines. Finally, I will discuss the ethical problems rising from the ubiquitous use of AI and present prominent researchers’ predictions of how the future of humanity might unfold as AI continues to evolve.
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