Effectively Utilizing Advanced Manufacturing Requires a New Approach to Closing Skills Gap

Advances in manufacturing technologies are fundamentally changing the nature of work at manufacturing enterprises. As new technologies are deployed, a large number of workers find themselves with obsolete skills and lose jobs. On the other hand, companies that are contemplating deploying new manufacturing technologies are unable to find workers with the right skills and hence many available manufacturing positions remain vacant.

The rate of rapid changes in manufacturing technologies is pointing to a future where major manufacturing technology refresh will occur every five to ten years. This means that a worker will need to face the challenge of skill obsolescence multiple times in a typical career. Overcoming this challenge using the current workforce education and training paradigm is not practical. Not finding a scalable solution to this challenge will lead to a major disruption to the way of life for the middle class.

Over the last few years, I have interacted with workers, companies, and colleges and discussed challenges and opportunities in the manufacturing workforce training area. Based on my analysis, the main challenges are the following:

1. Acquiring new manufacturing skills often requires six months or more. Displaced workers are economically vulnerable and simply do not have cash reserves to complete the training. 
2. Many displaced workers do not have math and programing prerequisites to learn advanced manufacturing technologies. Completing these prerequisites takes extra time. 
3. Many advanced manufacturing technologies are expensive. Colleges and training institutes are unable to acquire them in sufficient quantities to rapidly build the capacity needed to retrain the workforce. 
4. Workers are unable to travel to far away training locations for long periods of times to complete the training due to family constraints and/or economic considerations.

The workforce retraining will need to occur frequently. Therefore, simply relying on government grants to sustain the current training models will not suffice. Manufacturing enterprises have embraced innovations and learned how to deliver personalized products at low costs with highly compressed schedules. Once we start viewing the workforce training enterprise as a part of the manufacturing supply chain, we realize that many principles that led to significant efficiency gains in manufacturing will be applicable to the work training as well. We should aim to realize a new workforce training enterprise with the following attributes:

1. Enable trainees to participate in training remotely. 
2. Accelerate the training process. 
3. Reduce time needed to complete prerequisites. 
4. Leverage spare capacity on existing machines to reduce capital investments.

Unfortunately, there is no simple solution to meet these needs. The solution will require development of new technologies and pedagogical tools to accelerate learning, commitment from individuals to life-long learning, and cultures at companies to incentivize acquisition of new skills. Government will also need to provide education based tax credits. Colleges will need to master the agile manufacturing principles to quickly roll out new programs to meet emerging needs. Addressing the workforce training challenge this will be a step towards solving the most pressing societal problem faced by the advanced economies.

What can robotics community learn from artists with disabilities?

The robotics community aspires to build general purpose robots that can perform complex tasks effortlessly. In reality, we see the current generation of robots struggling to do even simple tasks.

We as roboticists admire human painters that can breathe life into canvasses with few brush strokes and sculptors in whose hands a marble slab melts like butter and an stunning awe-inspiring form emerges. We sigh with envy and hope that someday our robots will be good enough to carve a recognizable shape into the marble without us writing few hundred thousand lines of code.

We often look at human hands and eyes and marvel at the ingenious “design” behind the two. Everything from the available number of degrees of freedom to highly adaptive and high resolution sensing is truly remarkable. Human hands and eyes working in tandem endow artists with impressive hand-eye coordination capabilities that enable them to perform “miracles” and create mesmerizing art.
 
We compare human hands and eyes with the “clunky” hand designs and “dumb” cameras found in robots of today and resign to the fact that with current robotic hand and vision technologies, we are not going to get too far in terms of mimicking any impressive human feat. Do we need to wait for significantly improved robot hand and perception technology to build more capable robots or can we do better with what we already have?
 
I have been recently researching art created by artists with different types of disabilities. I am developing a very different perspective on whether the current hand and eye technology limitations are holding back the robotics community.  


I recently was introduced to paintings created by artists with severe visual impairment. A good starting point is “10 Remarkable Paintings by Blind and Visually Impaired Artists”.  This work is truly inspiring. Figures 1 and 2 show two representative paintings.

Figure 1: A painting by 
John Bramblitt (Image Source: http://illusion.scene360.com/art/78311/blind-artists/)

Figure 2: A painting by Eşref Armağan (Image Source: http://esrefarmagan.com/wp-content/uploads/2013/05/24.png)

Doug Landis is paralyzed from the neck down. He holds a pen in his mouth and creates amazing drawings by controlling the pen with his mouth. His art work is called mouth art. Figure 3 shows one of his drawings.
 

Figure 3: A painting by Doug Landis (Image Source: http://www.odditycentral.com/pics/doug-landis-mouth-art.html)

These examples show that humans are able to create amazing art despite serious physical handicaps. Something magical happens in the brain and it enables the artist to create amazing art by controlling the available sensing and manipulation modalities. Many years ago Matt Mason told me that "simple hands" are capable of doing quite a bit. My recent explorations seem to support that point of view. We need to develop a better understanding of what minimal sensory and manipulation capabilities are needed to create a piece of art.  

Hopefully, this post will inspire roboticists to stop waiting for the perfect robot hands and eyes. We ought to be able to do better with what we have right now.   

Accelerating Learning: Is it possible to beat 10,000-hour rule?

In his very well-written and popular book Outliers, Malcolm Gladwell popularized 10,000-hour rule. This rule is based on work done by Ericson, a psychologist.  The basic premise behind this rule is that it takes 10,000 hours of quality practice to become an expert in something. Another wonderfully written book Bounce by Mathew Syed also referred to this rule. Both books attempt to explain anatomy of success, in particular, extreme success. 10,000-hour rule has been interpreted by the popular media in many different ways. You might disagree with the numerical value of the number of hours it takes to become an expert. However, there appears be no doubt that currently it takes a long time to become an expert.

We are living in the age of rapid technological advances. The rapid change of technology is a harbinger of creative destruction. As an existing industry dies due to obsolescence of the underlying technology, many jobs associated with it disappear too. Similarly, the birth of a new industry creates many new jobs. We will soon be approaching the situation where people will need to retool themselves by acquiring new skills every five to ten years to ensure that they remain employed.      

This new reality is in conflict with the way education system works today.  To become expert at something and get a well-paying job, one must spend years in post-secondary training.  If you want to change your field significantly, you can count on spending several years in the school again. 10,000-hour rule seem to provide a justification for it! However, spending years in school to retool themselves after losing the job is not going to be an economically viable option for most people.

We need to find a better way. One way would be to accelerate the learning process.  Can we beat 10,000-hour rule? Can we master a new craft in 1,000 hours instead? 
In a conventional classroom, one memorizes lots of facts and information, develops motor skills necessary to do the physical tasks associated with the profession (e.g., surgery), and learns problem solving and decision making skills. In disciplines that involve creating something new (e.g., engineering design, architecture), one also learns synthesis process and divergent thinking to enable creation of new artifacts.        

We live a different world compared to the early twentieth century. However, we have not made any significant leap in the learning process over the past one hundred years. I would like to share the following observations:

• A large amount of time in a conventional education program is spent on memorizing lots of facts and information.  Clearly, it was necessary to do it in the past. But within few years, we can envision a smartphone that gives a person ability to instantly search for virtually every known fact and information.  How crucial is it to devote time to memorizing all the facts associated with a profession? We can instead imagine a scenario where a human memorizes crucial high level facts that help him/her in understanding how the information is organized within the field, but the low level facts need not be stored in the human brain. The human can access them from the cloud on as-needed basis. The decreased emphasize on rote memorization can speed up the learning process.
   
• In many educational programs, a significant amount of time is spent on motor skill development.  Many future jobs will be done with assistance from robots (and perhaps exoskeleton). This should reduce the time needed to develop motor skills.    
   
• In the current education system, problem solving, decision making, synthesis, and divergent thinking skills are learned in the context of a discipline.  So these skills are not easily transferable to a new discipline. For example, let us assume that you are currently an architect and would like to switch to bio-medical engineering. Unfortunately, it will take you many years in school to accomplish this.  We ought to be able to structure education such that problem solving, decision making, synthesis, and divergent thinking skills are learned in such a way that they can be easily transferable from one career (e.g., architect) to another (e.g., bio-medical engineer).   
   
• Technology can be used during the learning process to ensure every hour spent on learning actually contributes to learning. Facial expression recognition (and perhaps non-invasive brain imaging) can help in making sure that the person is not getting bored or frustrated! This ought to improve the learning process. Personalized computer-based tutoring system should also improve the efficiency of learning process.  

In my opinion, accelerating the pace of learning is one of the biggest challenge and opportunity facing the human race.  Clearly, training world-class athletes and musicians will continue to take more than 10,000-hour of quality practice. But we ought to be able accelerate learning in many other fields.