As we transition from AI Spring to AI Summer, we are witnessing a massive paradigm shift across several industry sectors.

The current phase of labor automation seems centered around automation of low intelligence-intensive high-regularity jobs.

These presently include clerks of all manners, secretaries, documentation-related tasks and so forth.

The next phase of labor automation will still be dominated by low intelligence-intensive jobs but with low-regularity semi-creative jobs.

These include intermediate artists and artisans of all manners, including photography, film, and basic design tasks such as web and simpler graphic design. A good example of such automation might be tweening artists in animation industry. Artificial imagery and art. There is indication that current tech is already sufficient for beginner to intermediate level of musical performances. Although that will not be practical or desirable, it shows the tech is there. The possibilities are endless.

These also include various smart engineering assistance and research automation tools, journalism, and other jobs that require a bit of creativity but not much. Such systems will be indispensable for research and news aggregation on the internet. For instance, such a smart scientific survey system will be able to find methods in the vast engineering literature that solve a problem of interest.

I also predict the automation of all manners of finance workers and such, such as stock market brokers, insurance managers, and others that are a bit creative, but are performing low-intelligence routine tasks of high-frequency repetition. The automation of these tiresome, arduous tasks will enhance overall efficiency, and save a lot in salaries and bonuses. This has already started, here is an article about a new AI system that replaces insurance claim workers in Japan.

These sectors may be multiplied, in terms of semi-creative low-intelligence tasks, preferably with high-repetition and high-workload where benefits from AI automation will be most visible.

Here we come, Cyberia!

 

Labor Automation Trends

examachine

Eray Özkural has obtained his PhD in computer engineering from Bilkent University, Ankara. He has a deep and long-running interest in human-level AI. His name appears in the acknowledgements of Marvin Minsky's The Emotion Machine. He has collaborated briefly with the founder of algorithmic information theory Ray Solomonoff, and in response to a challenge he posed, invented Heuristic Algorithmic Memory, which is a long-term memory design for general-purpose machine learning. Some other researchers have been inspired by HAM and call the approach "Bayesian Program Learning". He has designed a next-generation general-purpose machine learning architecture. He is the recipient of 2015 Kurzweil Best AGI Idea Award for his theoretical contributions to universal induction. He has previously invented an FPGA virtualization scheme for Global Supercomputing, Inc. which was internationally patented. He has also proposed a cryptocurrency called Cypher, and an energy based currency which can drive green energy proliferation. You may find his blog at http://log.examachine.net and some of his free software projects at https://github.com/examachine/.

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