Innovation Article

Clifton B. Parker’s picture

By: Clifton B. Parker

An underlying theme emerged from the Stanford Institute for Human-Centered Artificial Intelligence’s fall conference: Artificial intelligence (AI) must be truly beneficial for humanity and not undermine people in a cold calculus of efficiency.

Titled “AI Ethics, Policy, and Governance,” the event brought together more than 900 people from academia, industry, civil society, and government to discuss the future of AI (or automated computer systems able to perform tasks that normally require human intelligence).

Discussions at the conference highlighted how companies, governments, and people around the world are grappling with AI’s ethical, policy, and governance implications.

David Hart’s picture

By: David Hart

Climate plans are the order of the day in the presidential primary campaign because carbon pollution is a global threat of unique proportions. But it’s worth asking whether candidates’ plans are based in the reality of the climate, the economy, and the election.

All three dimensions must come together for any climate plan to achieve its goals—and this is especially true when the subject is electric vehicles (EVs). There is no point in putting forward an EV plan that is so aggressive that it cannot be implemented even under the most auspicious economic circumstances. Nor is there a point in advancing an EV plan that would not yield significant climate benefits. And, if such a plan might hurt a candidate’s chances in the election, it would be worse than pointless.

Following the lead of Governor Jay Inslee, who dropped out of the race earlier this fall, Senators Cory Booker, Bernie Sanders, and Elizabeth Warren said they would require all passenger cars sold in the United States to be zero-emissions by 2030, while Senator Kamala Harris and Mayor Pete Buttigieg set a 2035 deadline.

Thomas R. Cutler’s picture

By: Thomas R. Cutler

Quality control and inventory control are equally important to the ongoing success of all manufacturing businesses. Both form the basis of an efficient organization that operates at high productivity levels, minimizes waste, and delivers quality products to meet or exceed consumers’ expectations.

Until a about decade ago, there were layers of quality assurance and quality control steps before products reached the end user. Along with production controls, these steps included quality controls related to warehouse operations, logistics, and inventory verification at retail stores, in order to double-check product quality and order fulfilment accuracy.

Today, more than a million small manufacturers worldwide have forgone any retail sales in favor of a D2C (direct to consumer) model, cutting out warehouse operations and retail stores. The reason is simple: margins. A jewelry manufacturer, for example, selling a bracelet for $20 online, with hard costs of $2, can realize huge profit margins by eliminating the wholesale middleman. That same bracelet would have wholesaled to retailers for $8. But now, while product quality is still a customer expectation, consumers also expect quality delivery and customer service.

Pawel Korzynski’s picture

By: Pawel Korzynski

Dell is doing it. MasterCard, too. Even universities, not exactly bastions of social media influence, are embracing it. Employee advocacy in social media is gaining currency as an effective way to promote an organization by the very people who work in it. Rather than creating ads or hiring social media influencers to boost a brand, companies like Vodafone and Starbucks to schools like Oslo Metropolitan University (OsloMet) are tapping staff members at all levels to become brand ambassadors, with arguably improved conviction and results.

Jennifer Chu’s picture

By: Jennifer Chu

In today’s factories and warehouses, it’s not uncommon to see robots whizzing about, shuttling items or tools from one station to another. For the most part, robots navigate pretty easily across open layouts. But they have a much harder time winding through narrow spaces to carry out tasks such as reaching for a product at the back of a cluttered shelf, or snaking around a car’s engine parts to unscrew an oil cap.

Now MIT engineers have developed a robot designed to extend a chain-like appendage flexible enough to twist and turn in any necessary configuration, yet rigid enough to support heavy loads or apply torque to assemble parts in tight spaces. When the task is complete, the robot can retract the appendage and extend it again, at a different length and shape, to suit the next task.

The appendage design is inspired by the way plants grow, which involves the transport of nutrients, in a fluidized form, up to the plant’s tip. There, they are converted into solid material to produce, bit by bit, a supportive stem.

Likewise, the robot consists of a “growing point,” or gearbox, that pulls a loose chain of interlocking blocks into the box. Gears in the box then lock the chain units together and feed the chain out, unit by unit, as a rigid appendage.

ISO’s picture

By: ISO

As artificial intelligence (AI) becomes increasingly ubiquitous in various industry sectors, establishing a common terminology for AI and examining its various applications is more important than ever. In the international standardization arena, much work is being undertaken by ISO/IEC’s joint technical committee JTC 1—Information technology—Subcommittee SC 42—Artificial intelligence, to establish a precise and workable definition of AI. Through its working group WG 4, SC 42 is looking at various use cases and applications. The convener of SC 42/WG 4 is Fumihiro Maruyama, senior expert on AI at Fujitsu Laboratories.

Currently, there are a total of 70 use cases that the working group is examining. Health, for example, is a fascinating area to explore. Maruyama himself describes one use case in which a program undertakes a “knowledge graph” of 10 billion pieces of information from existing research papers and databases in the medical field. The application then attempts to form a path representing the likely development from a given gene mutation to the disease that deep learning has predicted from the mutation.

Chad Kymal’s picture

By: Chad Kymal

With the advent of the internet, cloud, and electronic workflows, what is the future of documented management systems? Do we continue with a structure of quality manual, processes, work instructions, and forms and checklists? How do we imagine the future of documented management systems?

For enterprise and site documentation, there’s a need for all entities, from site to department to individuals, to have their own documented management system structure. The documented management system should be a repository of organizational knowledge, in the form of documentation, records, projects, audits, dashboards, customer and/or interested party needs and expectations, calibration data, and much more. How is this possible?

Furthermore, documented flows should give way to virtual electronic workflows that help implement and sustain an integrated management system.

Steve Hawk’s default image

By: Steve Hawk

The company Grace Science was born through an inversion of the normal business sequence. Typically, if an entrepreneur launches a startup and it succeeds, the founders will create a nonprofit, declaring, “We want to give back.” In this case, the nonprofit spawned the startup.

The company’s inception accelerated when Matt Wilsey first met with Carolyn Bertozzi in 2015. Bertozzi is the Anne T. and Robert M. Bass Professor of Chemistry and professor of chemical and systems biology and of radiology (by courtesy) at Stanford University.

Wilsey’s daughter, Grace, has an ultra-rare disorder caused by a mutation in a gene known as NGLY1. Only 54 people in the world have been diagnosed with the disease. In 2014, Wilsey and his wife, Kristen, created a nonprofit, the Grace Science Foundation, in their quest to find a cure. The foundation has raised about $9 million to date.

Brian Charles’s picture

By: Brian Charles

It’s often difficult to pinpoint the exact moment when things change, but it usually happens faster than one imagines. Old technology gets replaced by new innovations; first by early adopters, and then, suddenly, by everyone. A century ago silent movies reigned, then talkies, and now 3D and virtual reality. What was once a disruptive new technology quickly becomes the norm.

For forward-thinking manufacturers, digital transformation initiatives, and their growing focus on machine health, are fast becoming the norm. I’ll say it out loud: The machine health tipping point is here. It’s no longer possible to avoid putting machine health at the center of your company's digital transformation strategy if you want to succeed through the Foutrth Industrial Revolution.

In the United States, manufacturing is on the rise, with a growth of 3.9 percent in 2019. At the same time, a generational shift is playing in the industrial workforce, as older workers retire and a new generation of manufacturing talent enters the workforce. This generational shift comes with a new mindset, attitude, and eagerness to adopt new technologies that will increase productivity on the shop floor.

Boris Liedtke’s picture

By: Boris Liedtke

In May 2019, a California jury found Monsanto’s weed killer, Roundup, to be a “substantial factor” in the cancer suffered by a couple and ordered the U.S. agrochemical company to pay them $2 billion in damages. This was the third and largest verdict against Monsanto, now owned by German pharmaceutical giant Bayer, over its decades-old product.

A judge slashed the award to $86.7 million in July 2019 after Bayer appealed, but it is cold comfort for the company. An estimated 13,400 similar Roundup cancer cases are pending in state and federal courts across the United States. European investors and Bayer’s management are in shock at the size of the settlements.

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