Source: Library of Congress. Children playing leapfrog, New York City. About 1908-1915. “No known restrictions on publication.”

What’s new?

In the 7 August 2021 issue of New Scientist, Jim Watson, research director at the UCL Institute for Sustainable Resources in London, argues that “Instead of developing energy infrastructures based on fossil fuels, low-income countries could leapfrog straight to cleaner low-carbon technologies.”

What does it mean?

Coal was king of the industrial revolution. All developed countries achieved their high standard of living by emitting greenhouse gases that are causing the climate crisis. Without just telling less developed countries that they should not follow that path, what can be done? Economic justice and environmental justice demand better approaches. Watson’s leapfrog may be an answer.

A leapfrog in technology is not a new idea, and is often applied to Africa, India, and elsewhere to describe a path using mobile and digital technology to fuel entrepreneurial ventures and social services. Financial Times quotes “Precious Lunga, a Zimbabwean neuroscientist who founded Baobab Circle, a health tech company,”

There are places where there’s still no running water, but you can stream a video,

and quotes “Calestous Juma, the Kenya-born former chair of the innovation for economic development executive programme at Harvard’s Kennedy School,”

The mobile handset in the hands of an ordinary African has become the symbol of leapfrogging.

Eliza Strickland in IEEE Spectrum presents evidence that African now leads the world in some digital applications.

Companies such as M-Pesa sprang up to solve a local problem—people’s lack of access to brick-and-mortar banks—and became a way for people not only to make payments, but also to get loans and insurance. “We’ve refined the concept of mobile money over the last 10 or 15 years,” says Kaabunga, “while other parts of the world are just now coming around to embracing it.”

She also reports that drones can deliver blood to hospitals that cannot be reached as quickly by poor roads.

But where does the electricity come from? Financial Times answers:

In the village of Sahabevava in north-east Madagascar, several hours down a bone-jolting road to the nearest town and far from the nearest electricity grid, Lydia Soa, a farmer, is the proud owner of a solar panel. It produces enough power to light her home — good for when the children do homework — power a boombox and, of course, recharge her mobile phone.

Jakkie Cilliers, in a chapter from his 2021 book The Future of Africa, describes more explicitly what the energy leapfrog might look like, with solar, wind, and ocean generated electricity, plus battery storage and transmission lines. Supplying cheap electricity will fuel the digital revolution, so the energy and digital revolutions are linked. He cautions, however,

A strong focus on technology can provide leapfrogging opportunities for low and middle-income countries, but governments must not lose sight of ‘traditional’ developmental issues, such as governance, infrastructure and skills.

Some actually point to a latecomer advantage, if the leapfrogging is done with careful planning.  Three authors at the Center for Strategic & International Studies state:

The lack of legacy infrastructure and entrenched vested interests could allow for the rapid adoption of emerging technologies, especially compared to developed nations that are forced to follow more incremental transition plans. This flexibility could allow developing nations to plan their policies, innovation ecosystems, and infrastructure with emerging technologies in mind from the start.

What does it mean for you?

While the idea of leapfrogging most often refers to taking a leap in the use of some technology, it can also apply to processes and softer improvements, although, of course, changes to technology and to processes go hand-in-hand. I always advise an organization to study a process thoroughly for efficiency (do all of those five people really need to approve purchases?) before automating.

Those, like me, who study and help organizations implement improvements often contrast incremental with dramatic improvements.  Continuous quality improvement using many small improvements throughout an organization can add up to large total improvement. Sometimes, however, a more dramatic leapfrog can be a better approach.

Benchmarking, according to ASQ, “is defined as the process of measuring products, services, and processes against those of organizations known to be leaders in one or more aspects of their operations.” How do the best performing organizations, both inside and outside of your industry, accomplish tasks? Combining best practices from many others can enable your organization to leap ahead.

However, for me, the biggest lesson is to focus on the goal, and then to think about different ways to get there, not just relying on the paths that others have already taken to that goal. Sometimes even the best ways to accomplish tasks can be dramatically improved by taking a fresh, innovative approach, not just tweaking the approaches that others already use.

Where can you learn more?

As I often do, I recommend my professional organizations as sources of information on how to improve: IISE (the Institute of Industrial and Systems Engineers) and ASQ (formerly the American Society for Quality).

This work is licensed under a Creative Commons Attribution 4.0 International License.

A shot in the arm

Source: Wikimedia This file is licensed under the Creative Commons Attribution 4.0 International license.

What’s new?

On 11 August, National Geographic described improvements being made in the processes to make vaccines, especially vaccines for COVID-19.

What does it mean?

While the US has ample supplies of COVID-19 vaccine (and a shortage of people willing to have the vaccine), most of the world needs more of the vaccine (and has plenty of people willing to have the vaccine). In addition to policy issues, such as the licensing of the vaccine, the rate of production of the vaccine affects the availability of COVID-19 and other vaccines.

Of the three types of COVID-19 vaccines (messenger RNA that conveys instructions to help the body fight the virus, inactivated virus to prime the immune system to produce antibodies, and a cold virus as a vehicle for immunizing material) each has its own method for production; the latter two are produced only in large batches.

A batch process requires weeks to grow host cells and then days to grow and process the vaccine.  The vat of cells eventually stops making product of sufficient quality; the vaccine eventually kills off the cells. Then the tanks must be properly cleaned and prepared for the next batch.

While the idea of change from a batch to a continuous process has been pursued since 1965, those approaches have still used large vats, seeking to siphon off the vaccine continuously. Recently an approach described in the National Geographic article has used 300-meter-long tube; it has been successful in a prototype. In this approach, fresh cells are continuously fed into the opening of the tube, another tube feeds in small quantities of the vaccine, and a pump keeps the fluid moving through the tube to the end where the vaccine and cell debris are separated. The new process is smaller and can be rapidly scaled-up when needed.

What does it mean for you?

The biggest point to understand from this article is that advances in product technology are always coupled with advances in process technology. Engineers work constantly to develop new products and to improve the design of existing products – and engineers do the same for processes, that is, they work constantly to develop new processes and to improve the design of existing processes.  The National Geographic article’s description of the new tube based process is an example of a new manufacturing process.

The Moderna and Pfizer vaccines are mRNA vaccines and these are new products. As Chemistry World states, “Large-scale production of such a vaccine has never happened before.” That article also says that Moderna and BioNTech have not released details on their manufacturing processes, but the processes is apparently not complicated: “The mRNA synthesis takes two hours, while making the vaccine takes a couple of days.” However, some of those steps are tricky.

The mRNA situation illustrates the interconnection between product design and process design. A new product may require a new manufacturing process. I can confidently predict that the world will continue to need new vaccines. It seems likely that mRNA vaccines will be an important tool in our capacity to counter new infectious diseases, so engineers will need to improve the processes for making mRNA vaccines. I am sure there are engineers busy on that task right now.

Manufacturing processes for different products can look similar. The National Geographic article describes how the inspiration for using tubes to manufacture vaccines can from observation of an oil refinery.

Product design and process design interact in many ways. Some changes in processes may enable higher quality also and the quality of vaccines is a crucial consideration in their manufacture. Different manufacturing processes can be harder or easier to scale. Some, as in batch processing, have an inherent scale, while a continuous process may be able to scale up or down more easily.

Once a product has somewhat stabilized, incremental product improvements and incremental process improvements continue to be developed. The cost of the technology for solar and wind power continues to fall dramatically largely because of advances in manufacturing processes.

Where can you learn more?

I am an industrial engineer. Most industrial engineers work in manufacturing, working on continuous improvement of manufacturing processes. The Institute of Industrial & Systems Engineers is the professional organization for such work.

This work is licensed under a Creative Commons Attribution 4.0 International License.

I told you so

What’s new?

In a 28 July article at New Scientist, Jeff Hecht says that fully autonomous cars are still in the future. In fact, “Some observers are now openly saying the dream of full autonomy is a mirage: creating robot vehicles able to tackle any kind of road or traffic situation is just too tough a nut to crack.”

What does it mean?

The article cites SAE International, formerly the Society of Automotive Engineers, for its six levels of automation, as shown in the diagram at the top of this post.  Fully autonomous vehicles, at level 5, are still in the future, with vehicles working at levels 0, 1 or 2 now.

The New Scientist article does a good job of reviewing problems with getting to fully autonomous vehicles: safety or the perception of safety; the predominance of computer engineers in autonomous vehicle development with their “move fast and break things” style (I can hardly write that phrase without shuddering); and the inability of human to quickly take over driving if needed (the article cites research that it takes an average of 5 seconds – an eternity in a fast moving vehicle).

The article notes that, skipping over level 3 and  moving to level 4 or 5 autonomy might make sense so that the human never needs to engage, but then points out that computer vision stumbles over simply situations that humans can easily handle: “We can instinctively tell, for example, whether lane markings are complete or dashed lines even if they are partly covered by snow, or that a stop sign remains a stop sign even if partially obscured, and instantly recognise the implications of an emergency vehicle heading our way.”

A level 2 driving system, according to the SAE classification, GM’s Super Cruise option in premium Cadillacs, is described by Cadillac as “the first true hands-free driving-assistance feature for compatible roads.” When engaged, the technology controls both speed and direction of the vehicle, staying in the lane; it can also change lanes when the driver turns on the turn signal. A Driver Attention Camera system makes sure that the driver is still paying attention. Its ability to drive is limited: “If equipped with Lane Change on Demand, you are able to prompt the system to change lanes for you. However, Super Cruise will not steer to avoid safety situations. You need to take control to steer around a traffic situation or object, merge into traffic, exit the highway, make a turn, or stop for crossing traffic or a traffic light, stop sign or other traffic control device. Super Cruise does not steer to avoid construction zones.”

Then comes the beginning of my “I told you so” moment. The system is available for use only on designated roads. I studied the map (at the same link I gave earlier) and found that most interstate highways are included. Near my hometown of Pueblo, designated roads include I-25 and stretches of US-50 east and west of Pueblo that are divided highways. We drive to and from Columbus, Ohio, at least once each year to visit family, and I found that our first day of driving, which is not on the interstate or other divided highway, is not on designated roads, but I-70, which we join in Hays, Kansas, is, as is the rest of our drive on I-70, except for a stretch of I-70 west of Kansas and a few gnarly intersections with other highways (which I, as a human, know are pretty tricky). I expect that Super Cruise would not be useable in practice on some other stretches of I-70 where I know that construction was underway earlier this summer.

Honda claims to have a level 3 vehicle (recall that the driver must be ready to take over driving quickly). I found the disclaimers disquieting, including a diagram showing, I think, that the vehicle might recognize only the upper section of the cab of a truck pulling an empty flatbed. It might not detect the flatbed and, I think, your vehicle thus might follow the cab and could run into the flatbed.

The CEO of GM, Mary Barra, wants to have Super Cruise available “in 95% of driving scenarios.”  New Scientist points out that of the 6.5 million kilometers of public roads in the US, only 300,000 kms meet current Super Cruise requirements. “Of those that aren’t covered by the system, 4.2 million kilometres are paved, ranging from busy city streets and quiet, wide, well-maintained streets in affluent suburbs to lightly travelled two-lane rural byways without centre lines. The remaining 2 million kilometres are unpaved, lacking markings and often signs.”

Dr Missy Cummings is a professor at Duke University, director of the Humans and Autonomy Laboratory and Duke Robotics, and an expert in human-autonomous system collaboration. In an October 2020 interview with Forbes, she was blunt about the problems with sensors, testing, and lack of repeatability in performance of existing autonomous vehicles. She says, for example, “If you can’t get a single Tesla to repeat its behavior in the same conditions over and over again, then why are we letting these cars, in theory, engage in automated driving?”

Finally, in my “I told you so” moment, New Scientist says, “The need to upgrade those roads to be robot-friendly ‘is a hidden cost most people are not thinking of’, says Cummings.” The designated roads for Cadillac’s Super Cruise are designated because these are roads that have been designed and built in a way that is friendly to an autonomous vehicle: divided highways, clearly and consistently marked lanes, and so forth. The part of the system that is not carefully controlled in that environment is all the other cars on the road.

On 23 Jan 2021, I wrote: “One of the difficult parts of autonomous driving is to predict what other vehicles will do, especially ones being driven by humans. Limiting the environment to only automated vehicles provides an easier problem to solve. The word `system’ also suggests coordination among automated vehicles, in which they share navigation information, but also share information about their intentions.”

I will go further now and say that the best application of autonomous vehicles is in long distance driving using designated lanes with only other autonomous vehicles. I think that application will be very useful for long distance trucking. One could counter my argument by saying that I have described a train and I agree.

What does it mean for you?

Don’t be dazzled by the rhetoric. Another quote from Dr Cummings in the Forbes interview: “I’m not worried that China or Russia will pull ahead of us in AI technology. Everyone is really bad at it right now.” She also describes current facial recognition technology as “terrible,” and says about Elon Musk “I’m not bothered by him as a person, I just really want him to reconsider what he’s doing with Autopilot because I think it’s exceedingly dangerous.”

Don’t be dazzled by the big companies throwing money around. New Scientist mentions that Uber and Lyft both sold their vehicle development groups in the last year.

The New Scientist article concludes: “There is a growing sense that the phase of irrational exuberance that often characterises new technologies might be over for self-driving cars, replaced by a more limited vision in which automation doesn’t fully replace human drivers, but helps us drive better under certain circumstances. That’s still a revolution of sorts – just not the one, perhaps, we first thought was coming.” I think this conclusion applies to many other areas of automation.

Where can I learn more?

Because the phrase “artificial intelligence” has almost come to mean any computer application, my skepticism may seem to be countered by useful applications. I am not, of course, saying that computers are useless. But this article has a list of successful applications that includes two I have already dismissed (autonomous vehicles and face recognition) and also includes Gmail’s spam detector – which, I find, worked flawlessly until a few months ago and now fails regularly.

I admire the people working to further the capabilities of computers to make our lives better. I am old enough to be still thrilled by the existence of my laptop, my cell phone, cruise control on my vehicle, Supernatural on my Oculus Quest II, etc. My life is better with these technologies.  But those people must believe in what they are doing and they are not trust worthy in their evaluation of the value of their work or in their prediction of the future of these technologies.

The preceding two paragraphs are an apology for not being able to recommend a good source of reliable information on what to expect from automation in the future.

This work is licensed under a Creative Commons Attribution 4.0 International License.