The
field of AI is changing the way that we as humans perform daily tasks ranging
from how we drive to how we work and collaborate. The interesting thing that I
found in the advancement of AI was the change in how these systems are
programmed. The article entitled “The End of Work?” discusses the changes that
are occurring, and are expected to occur, in the workforce due to the
advancements in AI. This integration into the workforce is due to new methods
of deep learning where computers are able to teach themselves based on
experience through pattern recognition and trial and error. These methods are
demonstrated in the article “How to teach machines to see.” In this article, a
program was created using these methods that recognized patterns in images to
identify and group objects in order to identify the surroundings. This was done
by labeling each individual pixel in thousands of photos. After enough photos,
the computer is able to group the pixels into the preassigned groups, such as
pavement, buildings, and pedestrians, based on the prior experience. This will enable
a more accurate determination of a self-driving car’s location and surroundings
compared to the current use of GPS and sensors.
The expansion
of deep learning methods will allow for the in integration of AI into the
workplace through programming computers to perform simple tasks that can be
checked and modified by humans. This will free time for professionals to work
on the more interesting or difficult tasks. These capabilities are limited,
however, in that computers lack human intuition and creativity. They are also
task-specific and lack the ability to perform generalized tasks. These limit
the uses of AI to programmable, task-oriented jobs. The push towards use of AI
in the workplace will change the nature of the job market. While many are
worried that it will increase unemployment with the decrease in people needed
to run a business, it will also open the door to more people in the field of
robotics and programming, as well as create new fields. In addition, there will
be a greater push for higher education and a continuation of learning after
entering the workforce in order to compete with the emerging technologies.
In
addition to allowing systems to be programmed through learning, there is also a
change in how systems are programmed to interact with people. As Janet Tran discussed
in her post, computers are better at performing specific tasks and organizing
data from individual inputs into an overall solution. The majority of
human-computation systems today are based on this ability of computers, with
the computer assigning micro tasks to individuals, then organizing all of the
results of these tasks to complete the main objective. However, this method
limits the ability of the users to interact and collaborate, which allows
people to build off of each other’s ideas, and does not allow the expansion of
creativity that occurs when humans work in groups. In new human-computation technologies,
the computer acts more as a sharing platform where the work of one individual
is sent to the next to be evaluated and revised while the computer continues to
integrate each individuals work into the overall goal. This new method allows
individuals to build off of each other to expand the potentials of working
together from far away with the potential to solve the world’s major problems.
With
the new advancements in AI, people are becoming optimistic in their views of
how they will live in the future. As Laura Worley discussed, the article
entitled “AI will replace smartphones within 5 years, Ericsson survey suggests”
demonstrates the populations desire to move away from smartphones to more
integrated system of appliances and accessories. These technologies varied from
3D virtual reality around the viewer and holograms to AI doctors and teachers.
While these technologies are possible in the future, I agree with Laura that
the five –year timeline is unrealistic with some of these applications, such as
doctors and teachers. This is mainly because the people surveyed were laypeople
who were optimistic in what they want in the future, rather than the expert
opinions of the possibilities and timelines.
References:
"AI Will Replace Smartphones Within 5 Years, Ericsson
Survey Suggests." Kurzweil Accelerating Intelligence, 09 Dec. 2015.
Web. 11 Jan. 2016.
<http://www.kurzweilai.net/ai-will-replace-smartphones-within-5-years-ericsson-survey-suggests>.
"Can Human-machine Superintelligence Solve the World’s
Most Dire Problems?" Kurzweil Accelerating Intelligence, 05 Jan.
2016. Web. 11 Jan. 2016.
<http://www.kurzweilai.net/can-human-machine-superintelligence-solve-the-worlds-most-dire-problems>.
"How to Teach Machines to See." Kurzweil
Accelerating Intelligence, 22 Dec. 2015. Web. 11 Jan. 2016. <http:// http://www.kurzweilai.net/how-to-teach-machines-to-see>.
Shisan, Ji. "The End of Work?" The New York
Times. The New York Times, 09 Dec. 2015. Web. 11 Jan. 2016.
<http://www.nytimes.com/2015/12/10/opinion/the-end-of-work.html?ribbon-ad-idx=8&rref=science&module=Ribbon&version=context®ion=Header&action=click&contentCollection=Science&pgtype=article>.
Comments:
Yuanjin Li
Hi Rebecca! One of the articles I read also discussed how AI uses deep learning and how its functionality is similar to the neural system of the human brain. I agree with you that the integration of AI into the workplace will increase employment rather than decrease it since AI is far from being perfect. Naturally I feel like human kind will be pushing towards perfection, and I don't see AI being perfect any time soon.
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