Texas is listed as the third-most vulnerable state when it comes to robots replacing the workforce in manufacturing. Houston houses a third of the manufacturing jobs in the state. Thossaphol Somsri/Getty Images

If a new forecast comes true, Houston's manufacturing sector could take an especially hard hit from the upturn in the use of robots.

In a new report, Oxford Economics, a forecasting and analysis firm based in the United Kingdom, ranks Texas as the third most vulnerable state when it comes to human workers in manufacturing being replaced by robotic labor. The report gives no estimate of how many manufacturing jobs Texas might lose to robots, but around the world, robots could boot 20 million jobs by 2030.

About one-third of Texas' manufacturers operate in the Houston metro area, meaning the robot revolution carries significant weight for the regional economy.

In 2017, manufacturing accounted for $82.6 billion, or nearly 17 percent, of the Houston area's economic output, the U.S. Bureau of Economic Analysis says. Manufacturing employment in the region averaged 219,160 jobs in 2017, with total wages of nearly $4.8 billion.

Among the top manufacturing segments in the region are fabricated metals (22 percent of all manufacturing jobs), machinery (19 percent) and chemicals (17.5 percent), according to the Greater Houston Partnership. Between 2012 and 2017, manufacturing employment in the Houston area slipped by 9.8 percent, going from 243,011 workers to 219,160 workers.

However, a recent report from the Economic Innovation Group shows Harris County netted more manufacturing jobs (11,592) from December 2016 to December 2018 than any other county in the U.S.

According to the National Association of Manufacturers, the manufacturing sector in Texas created more than $226 billion in economic output in 2017. Last year, about 880,900 people held manufacturing jobs in Texas; that's more than 7 percent of the statewide workforce.

In declaring that Texas sits among the states most susceptible to job losses due to robotics, Oxford Economics took into account factors such as:

  • Dependence on manufacturing jobs.
  • Current use of robots in manufacturing.
  • Productivity of the manufacturing workforce.

Based on those criteria, Texas received a robot vulnerability score of 0.50. The top two states, Oregon and Louisiana, each got a score of 0.58, with the higher number meaning greater vulnerability.

The report cites three reasons for the ascent of robots in manufacturing:

  • Robots are becoming cheaper than humans.
  • Robots are becoming more sophisticated.
  • Demand for manufactured goods is rising.

"The rise of the robots will boost productivity and economic growth. It will lead, too, to the creation of new jobs in yet-to-exist industries, in a process of 'creative destruction,'" according to the Oxford Economics report. "But existing business models across many sectors will be seriously disrupted. And tens of millions of existing jobs will be lost, with human workers displaced by robots at an increasing rate as robots become steadily more sophisticated."

Tony Bennett, president and CEO of the Texas Association of Manufacturers, says the Oxford Economics report isn't all gloom and doom.

"Robotics and mechanization in our advanced manufacturing industries will continue to displace some general-labor jobs. However, this change is also ushering in a new set of higher-skilled jobs that are being created to engineer, build, and service these sophisticated machines," Bennett says. "The state of Texas must continue striving to increase educational opportunities in engineering, math, science, and career and technical programs to meet the complex manufacturing processes of the future."

Houston Community College's Advanced Manufacturing Center for Excellence is among the organizations in the Houston area that are preparing workers for jobs in robotics and other high-demand, tech-driven aspects of manufacturing.

"Innovation is Houston's bedrock," Houston Mayor Sylvester Turner said in 2017. "The city would have never thrived without the innovations it took to build the Ship Channel and the innovating that goes on every day in the energy industry, at the Texas Medical Center, at the Johnson Space Center and in the manufacturing sector. Now, Houston is poised to take its place at the forefront of the American future in technology."

Earlier this year, another study found a similarly daunting result. Almost half of Houston's workplace tasks are susceptible to automation, according to a new report from the Brookings Institution's Metropolitan Policy Program. Of 100 metros analyzed, Houston ranks 31st among the country's 100 biggest metros, with 46.3 percent of work tasks susceptible to automation.

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Houston doctor wins NIH grant to test virtual reality for ICU delirium

Virtual healing

Think of it like a reverse version of The Matrix. A person wakes up in a hospital bed and gets plugged into a virtual reality game world in order to heal.

While it may sound far-fetched, Dr. Hina Faisal, a Houston Methodist critical care specialist in the Department of Surgery, was recently awarded a $242,000 grant from the National Institute of Health to test the effects of VR games on patients coming out of major surgery in the intensive care unit (ICU).

The five-year study will focus on older patients using mental stimulation techniques to reduce incidences of delirium. The award comes courtesy of the National Institute on Aging K76 Paul B. Beeson Emerging Leaders Career Development Award in Aging.

“As the population of older adults continues to grow, the need for effective, scalable interventions to prevent postoperative complications like delirium is more important than ever,” Faisal said in a news release.

ICU delirium is a serious condition that can lead to major complications and even death. Roughly 87 percent of patients who undergo major surgery involving intubation will experience some form of delirium coming out of anesthesia. Causes can range from infection to drug reactions. While many cases are mild, prolonged ICU delirium may prevent a patient from following medical advice or even cause them to hurt themselves.

Using VR games to treat delirium is a rapidly emerging and exciting branch of medicine. Studies show that VR games can help promote mental activity, memory and cognitive function. However, the full benefits are currently unknown as studies have been hampered by small patient populations.

Faisal believes that half of all ICU delirium cases are preventable through VR treatment. Currently, a general lack of knowledge and resources has been holding back the advancement of the treatment.

Hopefully, the work of Faisal in one of the busiest medical cities in the world can alleviate that problem as she spends the next half-decade plugging patients into games to aid in their healing.

Houston scientists develop breakthrough AI-driven process to design, decode genetic circuits

biotech breakthrough

Researchers at Rice University have developed an innovative process that uses artificial intelligence to better understand complex genetic circuits.

A study, published in the journal Nature, shows how the new technique, known as “Combining Long- and Short-range Sequencing to Investigate Genetic Complexity,” or CLASSIC, can generate and test millions of DNA designs at the same time, which, according to Rice.

The work was led by Rice’s Caleb Bashor, deputy director for the Rice Synthetic Biology Institute and member of the Ken Kennedy Institute. Bashor has been working with Kshitij Rai and Ronan O’Connell, co-first authors on the study, on the CLASSIC for over four years, according to a news release.

“Our work is the first demonstration that you can use AI for designing these circuits,” Bashor said in the release.

Genetic circuits program cells to perform specific functions. Finding the circuit that matches a desired function or performance "can be like looking for a needle in a haystack," Bashor explained. This work looked to find a solution to this long-standing challenge in synthetic biology.

First, the team developed a library of proof-of-concept genetic circuits. It then pooled the circuits and inserted them into human cells. Next, they used long-read and short-read DNA sequencing to create "a master map" that linked each circuit to how it performed.

The data was then used to train AI and machine learning models to analyze circuits and make accurate predictions for how untested circuits might perform.

“We end up with measurements for a lot of the possible designs but not all of them, and that is where building the (machine learning) model comes in,” O’Connell explained in the release. “We use the data to train a model that can understand this landscape and predict things we were not able to generate data on.”

Ultimately, the researchers believe the circuit characterization and AI-driven understanding can speed up synthetic biology, lead to faster development of biotechnology and potentially support more cell-based therapy breakthroughs by shedding new light on how gene circuits behave, according to Rice.

“We think AI/ML-driven design is the future of synthetic biology,” Bashor added in the release. “As we collect more data using CLASSIC, we can train more complex models to make predictions for how to design even more sophisticated and useful cellular biotechnology.”

The team at Rice also worked with Pankaj Mehta’s group in the department of physics at Boston University and Todd Treangen’s group in Rice’s computer science department. Research was supported by the National Institutes of Health, Office of Naval Research, the Robert J. Kleberg Jr. and Helen C. Kleberg Foundation, the American Heart Association, National Library of Medicine, the National Science Foundation, Rice’s Ken Kennedy Institute and the Rice Institute of Synthetic Biology.

James Collins, a biomedical engineer at MIT who helped establish synthetic biology as a field, added that CLASSIC is a new, defining milestone.

“Twenty-five years ago, those early circuits showed that we could program living cells, but they were built one at a time, each requiring months of tuning,” said Collins, who was one of the inventors of the toggle switch. “Bashor and colleagues have now delivered a transformative leap: CLASSIC brings high-throughput engineering to gene circuit design, allowing exploration of combinatorial spaces that were previously out of reach. Their platform doesn’t just accelerate the design-build-test-learn cycle; it redefines its scale, marking a new era of data-driven synthetic biology.”