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Transforming the energy industry with AI

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Transforming the energy industry with AI


However, most companies don’t have the resources to implement sophisticated AI programs to stay secure and advance digital capabilities on their own. Irrespective of size, available budget, and in-house personnel, all energy companies must manage operations and security fundamentals to ensure they have visibility and monitoring across powerful digital tools to remain resilient and competitive. The achievement of that goal is much more likely in partnership with the right experts.

MIT Technology Review Insights, in association with Siemens Energy, spoke to more than a dozen information technology (IT) and cybersecurity executives at oil and gas companies worldwide to gain insight about how AI is affecting their digital transformation and cybersecurity strategies in oil and gas operating environments. Here are the key findings:

  • Oil and gas companies are under pressure to adapt to dramatic changes in the global business environment. The coronavirus pandemic dealt a stunning blow to the global economy in 2020, contributing to an extended trend of lower prices and heightening the value of increased efficiency to compensate for market pressures. Companies are now forced to operate in a business climate that necessitates remote working, with the added pressure to manage the environmental impact of operations growing ever stronger. These combined factors are pushing oil and gas companies to pivot to new, streamlined ways of working, making digital technology adoption critical.
  • As oil and gas companies digitalize, the risk of cyberattacks increases, as do opportunities for AI. Companies are adding digital technology for improved productivity, operational efficiency, and security. They’re collecting and analyzing data, connecting equipment to the internet of things, and tapping cutting-edge technologies to improve planning and increase profits, as well as to detect and mitigate threats. At the same time, the industry’s collective digital transformation is widening the surface for cybercriminals to attack. IT is under threat, as is operational technology (OT)—the computing and communications systems that manage and control equipment and industrial operations.
  • Cybersecurity must be at the core of every aspect of companies’ digital transformation strategies. The implementation of new technologies affects interdependent business and operational functions and underlying IT infrastructure. That reality calls for oil and gas companies to shift to a risk management mindset. This includes designing projects and systems within a cybersecurity risk framework that enforces companywide policies and controls. Most important, they now need to access and deploy state-of-the-art cybersecurity tools powered by AI and machine learning to stay ahead of attackers.
  • AI is optimizing and securing energy assets and IT networks for increased monitoring and visibility. Advancements in digital applications in industrial operating environments are helping improve efficiency and security, detecting machine-speed attacks amidst the complexity of the rapidly digitalizing operating environments.
  • Oil and gas companies look to external partners to guard against growing cyberthreats. Many companies have insufficient cybersecurity resources to meet their challenges head-on. “We are in a race against the speed of the attackers,” Repsol Chief Information Officer Javier García Quintela explains in the report. “We can’t provide all the cybersecurity capabilities we need from inside.” To move quickly and address their vulnerabilities, companies can find partners that can provide expertise and support as the threat environment expands.

Cybersecurity, AI, and digitalization

Energy sector organizations are presented with a major opportunity to deploy AI and build out a data strategy that optimizes production and uncovers new business models, as well as secure operational technology. Oil and gas companies are faced with unprecedented uncertainty—depressed oil and gas prices due to the coronavirus pandemic, a multiyear glut in the market, and the drive to go green—and many are making a rapid transition to digitalization as a matter of survival. From moving to the cloud to sharing algorithms, the oil and gas industry is showing there is robust opportunity for organizations to evolve with technological changes.

In the oil and gas industry, the digital revolution has enabled companies to connect physical energy assets with hardware control systems and software programs, which improves operational efficiency, reduces costs, and cuts emissions. This trend is due to the convergence of energy assets connected to OT systems, which manage, monitor, and control energy assets and critical infrastructure, and IT networks that companies use to optimize data across their corporate environments.

With billions of OT and IT data points captured from physical assets each day, oil and gas companies are now turning to built-for-purpose AI tools to provide visibility and monitoring across their industrial operating environments—both to make technologies and operations more efficient, and for protection against cyberattacks in an expanded threat landscape. Because energy companies’ business models rely on the convergence of OT and IT data, companies see AI as an important tool to gain visibility into their digital ecosystems and understand the context of their operating environments. Enterprises that build cyber-first digital deployments similarly have to accommodate emerging technologies, such as AI and machine learning, but spend less time on strategic realignment or change management.

Importantly, for oil and gas companies, AI, which may have once been reserved for specialized applications, is now optimizing everyday operations and providing critical cybersecurity defense for OT assets. Leo Simonovich, vice president and global head of industrial cyber and digital security at Siemens Energy, argues, “Oil and gas companies are becoming digital companies, and there shouldn’t be a trade-off between security and digitalization.” Therefore, Simonovich continues, “security needs to be part of the digital strategy, and security needs to scale with digitalization.”

To navigate today’s volatile business landscape, oil and gas companies need to simultaneously identify optimization opportunities and cybersecurity gaps in their digitalization strategies. That means building AI and cybersecurity into digital deployments from the ground up, not bolting them on afterward.

Download the full report.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

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Why can’t tech fix its gender problem?

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From left to right: Gordon MOORE, C. Sheldon ROBERTS, Eugene KLEINER, Robert NOYCE, Victor GRINICH, Julius BLANK, Jean HOERNI and Jay LAST.


Not competing in this Olympics, but still contributing to the industry’s success, were the thousands of women who worked in the Valley’s microchip fabrication plants and other manufacturing facilities from the 1960s to the early 1980s. Some were working-class Asian- and Mexican-Americans whose mothers and grandmothers had worked in the orchards and fruit can­neries of the prewar Valley. Others were recent migrants from the East and Midwest, white and often college educated, needing income and interested in technical work. 

With few other technical jobs available to them in the Valley, women would work for less. The preponderance of women on the lines helped keep the region’s factory wages among the lowest in the country. Women continue to dominate high-tech assembly lines, though now most of the factories are located thousands of miles away. In 1970, one early American-owned Mexican production line employed 600 workers, nearly 90% of whom were female. Half a century later the pattern continued: in 2019, women made up 90% of the workforce in one enormous iPhone assembly plant in India. Female production workers make up 80% of the entire tech workforce of Vietnam. 

Venture: “The Boys Club”

Chipmaking’s fiercely competitive and unusually demanding managerial culture proved to be highly influential, filtering down through the millionaires of the first semiconductor generation as they deployed their wealth and managerial experience in other companies. But venture capital was where semiconductor culture cast its longest shadow. 

The Valley’s original venture capitalists were a tight-knit bunch, mostly young men managing older, much richer men’s money. At first there were so few of them that they’d book a table at a San Francisco restaurant, summoning founders to pitch everyone at once. So many opportunities were flowing it didn’t much matter if a deal went to someone else. Charter members like Silicon Valley venture capitalist Reid Dennis called it “The Group.” Other observers, like journalist John W. Wilson, called it “The Boys Club.”

The men who left the Valley’s first silicon chipmaker, Shockley Semiconductor, to start Fairchild Semiconductor in 1957 were called “the Traitorous Eight.”

WAYNE MILLER/MAGNUM PHOTOS

The venture business was expanding by the early 1970s, even though down markets made it a terrible time to raise money. But the firms founded and led by semiconductor veterans during this period became industry-defining ones. Gene Kleiner left Fairchild Semiconductor to cofound Kleiner Perkins, whose long list of hits included Genentech, Sun Microsystems, AOL, Google, and Amazon. Master intimidator Don Valentine founded Sequoia Capital, making early-stage investments in Atari and Apple, and later in Cisco, Google, Instagram, Airbnb, and many others.

Generations: “Pattern recognition”

Silicon Valley venture capitalists left their mark not only by choosing whom to invest in, but by advising and shaping the business sensibility of those they funded. They were more than bankers. They were mentors, professors, and father figures to young, inexperienced men who often knew a lot about technology and nothing about how to start and grow a business. 

“This model of one generation succeeding and then turning around to offer the next generation of entrepreneurs financial support and managerial expertise,” Silicon Valley historian Leslie Berlin writes, “is one of the most important and under-recognized secrets to Silicon Valley’s ongoing success.” Tech leaders agree with Berlin’s assessment. Apple cofounder Steve Jobs—who learned most of what he knew about business from the men of the semiconductor industry—likened it to passing a baton in a relay race.

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Predicting the climate bill’s effects is harder than you might think

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Predicting the climate bill’s effects is harder than you might think


Human decision-making can also cause models and reality to misalign. “People don’t necessarily always do what is, on paper, the most economic,” says Robbie Orvis, who leads the energy policy solutions program at Energy Innovation.

This is a common issue for consumer tax credits, like those for electric vehicles or home energy efficiency upgrades. Often people don’t have the information or funds needed to take advantage of tax credits.

Likewise, there are no assurances that credits in the power sectors will have the impact that modelers expect. Finding sites for new power projects and getting permits for them can be challenging, potentially derailing progress. Some of this friction is factored into the models, Orvis says. But there’s still potential for more challenges than modelers expect.

Not enough

Putting too much stock in results from models can be problematic, says James Bushnell, an economist at the University of California, Davis. For one thing, models could overestimate how much behavior change is because of tax credits. Some of the projects that are claiming tax credits would probably have been built anyway, Bushnell says, especially solar and wind installations, which are already becoming more widespread and cheaper to build.

Still, whether or not the bill meets the expectations of the modelers, it’s a step forward in providing climate-friendly incentives, since it replaces solar- and wind-specific credits with broader clean-energy credits that will be more flexible for developers in choosing which technologies to deploy.

Another positive of the legislation is all its long-term investments, whose potential impacts aren’t fully captured in the economic models. The bill includes money for research and development of new technologies like direct air capture and clean hydrogen, which are still unproven but could have major impacts on emissions in the coming decades if they prove to be efficient and practical. 

Whatever the effectiveness of the Inflation Reduction Act, however, it’s clear that more climate action is still needed to meet emissions goals in 2030 and beyond. Indeed, even if the predictions of the modelers are correct, the bill is still not sufficient for the US to meet its stated goals under the Paris agreement of cutting emissions to half of 2005 levels by 2030.

The path ahead for US climate action isn’t as certain as some might wish it were. But with the Inflation Reduction Act, the country has taken a big step. Exactly how big is still an open question. 

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China has censored a top health information platform

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China has censored a top health information platform


The suspension has met with a gleeful social reaction among nationalist bloggers, who accuse DXY of receiving foreign funding, bashing traditional Chinese medicine, and criticizing China’s health-care system. 

DXY is one of the front-runners in China’s digital health startup scene. It hosts the largest online community Chinese doctors use to discuss professional topics and socialize. It also provides a medical news service for a general audience, and it is widely seen as the most influential popular science publication in health care. 

“I think no one, as long as they are somewhat related to the medical profession, doesn’t follow these accounts [of DXY],” says Zhao Yingxi, a global health researcher and PhD candidate at Oxford University, who says he followed DXY’s accounts on WeChat too. 

But in the increasingly polarized social media environment in China, health care is becoming a target for controversy. The swift conclusion that DXY’s demise was triggered by its foreign ties and critical work illustrates how politicized health topics have become. 

Since its launch in 2000, DXY has raised five rounds of funding from prominent companies like Tencent and venture capital firms. But even that commercial success has caused it trouble this week. One of its major investors, Trustbridge Partners, raises funds from sources like Columbia University’s endowments and Singapore’s state holding company Temasek. After DXY’s accounts were suspended, bloggers used that fact to try to back up their claim that DXY has been under foreign influence all along. 

Part of the reason the suspension is so shocking is that DXY is widely seen as one of the most trusted online sources for health education in China. During the early days of the covid-19 pandemic, it compiled case numbers and published a case map that was updated every day, becoming the go-to source for Chinese people seeking to follow covid trends in the country. DXY also made its name by taking down several high-profile fraudulent health products in China.

It also hasn’t shied away from sensitive issues. For example, on the International Day Against Homophobia, Transphobia, and Biphobia in 2019, it published the accounts of several victims of conversion therapy and argued that the practice is not backed by medical consensus. 

“The article put survivors’ voices front and center and didn’t tiptoe around the disturbing reality that conversion therapy is still prevalent and even pushed by highly ranked public hospitals and academics,” says Darius Longarino, a senior fellow at Yale Law School’s Paul Tsai China Center. 

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