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Feb 22 2024

Data at the center of business

With more than 5,000 branches across 48 states and 80 million customers, each with its own unique requirements to satisfy its customers’ financial needs, a clear data strategy is key for JPMorgan Chase. According to Mark Birkhead, firm-wide chief data officer at JPMorgan Chase, data analytics is the oxygen that breathes life into the firm to deliver growth and improve the customer experience.

Providing first-class business in a first-class way for clients and customers applies to every part of the firm, including its heavy investments in data analytics, machine learning, and AI. Using these advanced technologies, JPMorgan Chase can gain a deeper understanding of the breadth and specificity of the needs of the customers and communities it serves.

“It means using our data to drive positive outcomes for our customers and our clients and our business partners. And it means using this to actually help our customers and clients manage their daily lives in a better, simpler way,” says Birkhead.

At their best, a strong data strategy along with AI and machine learning adoption can free employees from tedious tasks to focus on high-value work. Reaching this extended intelligence — humans and machines working better together — means having the right deployment strategy. It’s key to understand both the potential and the limitations of these tools to make sure your enterprise is investing wisely in the areas where technologies like AI and machine learning can offer the greatest value.

“At the end of the day, what we’re trying to do is build an analytic factory that can deliver AI/ML at scale,” says Birkhead. “And that type of a factory requires a really sound strategy, efficient platforms and compute, solid governance and controls, and incredible talent.”

Adopting this vision at scale is a long-term investment that requires strong conviction, adherence to governance and controls, and operationalizing data. One of the most challenging aspects of this, Birkhead says, is defining your data priorities.

“Everyone talks about data every minute of every day. However, data has been oftentimes, I think, thought of as exhaust from some product, from some process, from some application, from a feature, from an app, and enough time has not been spent actually ensuring that that data is considered an asset, that that data is of high quality, that it’s fully understood by humans and machines.”

This episode of Business Lab is produced in association with JPMorgan Chase.

Full Transcript

Laurel Ruma: From MIT Technology Review, I’m Laurel Ruma and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace.

Our topic is data and analytics. Building a global data strategy requires a strong understanding of governance, regulations, and customer experience for both internal and external customers. As technologies like AI emerge, the opportunity expands for real-time learnings and making better decisions.

Two words for you: data strategy.

My guest is Mark Birkhead, who is the firmwide chief data officer at JPMorgan Chase.

This podcast is produced in association with JPMorgan Chase.

Welcome, Mark.

Mark Birkhead: Thank you for having me, Laurel. It’s great to be here.

Laurel: Let’s start here. You were recently appointed to firmwide chief data officer for JPMorgan Chase. Previously you were the chief data and analytics officer at Chase and JPMorgan Wealth Management. Can you give us some insight into how your new role factors into the firm’s data strategy?

Mark: Absolutely. My new role as the firmwide chief data officer will be focused primarily on driving this strategy and solutions, that maximize the impact that data can have on our clients and customers across the globe and doing it in a highly governed and controlled ways. Data plays a huge part in our firmwide strategy. It’s been described by several of our senior leaders as the oxygen that powers the firm. And I truly believe that. Data analytics has propelled so many of our businesses, including our consumer bank and business bank, our commercial bank, our wealth management businesses, and our payments business globally. And its impact continues to grow in more meaningful ways every single day and month.

Strong data analytics capabilities really do provide the foundational underpinnings for our core business activities, but it’s actually fueling the growth of our businesses in meaningful ways. This addition is driving productivity, delivering insights that help our customers grow their businesses, and enabling our bankers and advisors to deliver elevated customer experiences.

Laurel: Thank you Mark for giving that context. As a global firm, you talk about delivering first-class business in a first-class way for clients and customers. Could you tell us how data and analytics, AI and machine learning are used to improve outcomes for your customers?

Mark: Absolutely. When we talk about first-class business in a first-class way, it really applies to every part of our firm and we’re investing heavily in data analytics, machine learning, and AI. But this is not new to us. We’ve been utilizing AI and ML for many, many years in many different ways. The Chase Analytics team actually will celebrate a sixth anniversary next March with the same mission and objective. Again, this is not new to us, but when we think about applying first-class business in a first-class way to the new set of AI capabilities, the new set of LLMs [large language models], the new set of generative AI, it means to us really honoring our customers’ expectations when it comes to privacy. It means using our data to drive positive outcomes for our customers and our clients and our business partners. And it means using this to actually help our customers and clients manage their daily lives in a better, simpler way.

I’m going to actually spend most of my time talking about my former role as the chief analytics officer for Chase and JPMorgan Wealth Management, but really our AI efforts across the globe are very similar to what has been happening at Chase and JPMorgan Wealth Management. It’s really been focused on improving the financial health for our customers and our clients. Today, JPMorgan Chase serves over 80 million customers in the US and we use advanced analytics to deliver best-in-class experiences and to respond to the needs of our customers. And our customers have all kinds of situations at any given moment in time. And at one moment we’re planning for college and other times we’re dealing with some difficult times in a family situation. And being able to have the right tools for our bankers, for advisors, for our call center agents to utilize is really important to us.

And I mentioned the breadth of data analytics as being the oxygen of the firm, and that really is reflected in the Chase business. And one of the hardest parts of the CDAO [chief data and analytics officer] job is to determine what investments to make and where to focus our attention when it comes to solving data problems and also determining where we have to lead with AI/ML and when we actually don’t. For us, there’s a couple of things that we always have to lead in given the nature of our business. We have a branch network of 5,000 branches. It covers all over 48 states. And we’ve got to lead with geospatial analytics and that heavily utilizes AI and ML to determine the optimal placement of our branches, of our network, of our community centers, and for the staffing within those branches. We also have over 60 million digitally active customers.

We have to lead in product analytics, experimentation, understand the customer experience in a journey, and how they interact with our products across multiple channels. It might start in a branch, end up in a mobile app, and end up in a call center, but all that has to be stitched together. We also have to lead when it comes to preventing fraud, and it has really become a difficult task given what’s going on across the world. But protecting our customers, from these types of acts, is incredibly important to us.

And we also need to make sure that within our branches, within our customers, they get the best experience possible, which means really using data analytics, machine learning, AI to understand our customers and communities in deeper ways. And in fact, for our 5,000 branches, there’s not a lot of similarities. And we actually have to prepare playbooks for these branches to make sure our employees are trained on these types of situations, the needs of their customers and clients so they can actually produce the best possible service. The only way to deliver all that at our scale is through leveraging data analytics, machine learning, and AI.

Laurel: Touching on that, at its best artificial intelligence, machine learning, and a robust data strategy can automate those tedious tasks to free people up to focus on high-value work. How do you think about that as an ongoing effort?

Mark: We think about this a lot and innovation has cycles, and that includes my field as well. But those cycle times are really changing and becoming more compressed, and that’s drawn a lot of attention and scrutiny particularly to the field of AI. At the end of the day, with the emergence of LLMs and generative AI, there’s just more opportunities to enhance the work of our employees day-to-day. Sandy Pentland, who helped form your MIT Media Lab, really described a few years back to our employees, this interaction is extended intelligence, humans and machines working better together. And this is actually one of our highest priorities at JPMorgan Chase, leveraging machines to help our employees do their jobs better for our customers and for our clients. And today we’re exploring experimenting with LLMs in a number of capacities. But it’s really important to understand what these tools can do well and what they can’t, and then making sure that we’re actually organizing ourselves against them and making the right investments in people and resources in those areas where these actual tools can help us to the greatest extent.

It’s also important that we focus on the governance and controls around this. And all that comes into play when it comes to figuring out what we do with these tools and how we apply them. I was meeting with our global marketers a couple of weeks ago, and every time I do this and talk about our plans for generative AI across the firm or at Chase, talk about the impact it can have on JPMorgan Chase, I get two types of questions. One is, “What does this mean for me and my employees?” And I think the answer is, with any type of technology, it’s not exactly going to take your job, but people who do use this technology will. And that’s the same thing with AI. And the only caveat to all of this is I think when it comes to this type of technology and capability, particularly with generative AI, those that understand what this does well and what it doesn’t, will actually have a leg up and be better positioned to actually succeed.

The second question I always get is, “If we’re always using the same tool for every company, the same model, aren’t we all going to sound the same?” And that’s where I think the relationship of the business and our models and data scientists has to evolve. Every time we build a model or an AI solution, we always engage with the business. But I think given what’s going on now with LLMs and generative AI, it’s really important to mature that model. The thinking around design and analytics needs to change to ensure that we incorporate the brand voice, the marketers’ voice into these solutions to make sure that the content that we deliver using these tools reflects the brands that the customers have come to know is really important. And this entire operating model has to evolve. And I think it presents really exciting opportunities to go deeper with customers in meaningful ways, but it requires the model to change.

Laurel: Speaking of having a leg up, successfully deploying AI and machine learning has become a competitive differentiator for large enterprises. What are the challenges of deploying AI and machine learning at scale? And then a second big question is, as regulations for AI and machine learning evolve, how does the firm manage government regulations?

Mark: That’s a great question. And first, I would say across JPMorgan Chase, we do view this as an investment. And every time I talk to a senior leader about the work we do, I never speak of expenses. It is always investment. And I do firmly believe that. At the end of the day, what we’re trying to do is build an analytic factory that can deliver AI/ML at scale. And that type of a factory requires a really sound strategy, efficient platforms and compute, solid governance and controls, and incredible talent. And for an organization of any scale, this is a long-term investment, and it’s not for the faint of heart. You really have to have conviction to do this and to do this well. Deploying this at scale can be really, really challenging. And it’s important to ensure that as we’re thinking about AI/ML, it’s done with controls and governance in place.

We’re a bank. We have a responsibility to protect our customers and clients. We have a lot of financial data and we have an obligation to the countries that we serve in terms of ensuring that the financial health of this firm remains in place. And at JPMorgan Chase, we’re always thinking about that first and foremost, and about what we actually invest in and what we don’t, the types of things we want to do and the things that we won’t do. But at the end of the day, we have to ensure that we understand what’s going on with these technologies and tools and the explainability to our regulators and to ourselves is really, really high. And that really is the bar for us. Do we truly understand what’s behind the logic, what’s behind the decision-ing, and are we comfortable with that? And if we don’t have that comfort, then we don’t move forward.

We never release a solution until we know it’s sound, it’s good, and we understand what’s going on. In terms of government relations, we have a large focus on this, and we have a large footprint across the globe. And at JPMorgan Chase, we really are focused on engaging with policymakers to understand their concerns as well as to share our concerns. And I think largely we’re united in the fact that we think this technology can be harnessed for good. We want it to work for good. We want to make sure it stays in the hands of good actors, and it doesn’t get used for harm for our clients or our customers or anything else. And it’s a place where I think business and policymakers need to come together and really have one solid voice in terms of the path forward because I think we’re highly, highly aligned.

Laurel: You did touch on this a bit, but enterprises are relying on data to do so many things like improving decision-making and optimizing operations as well as driving business growth. But what does it mean to operationalize data and what opportunities could enterprises find through this process?

Mark: I mentioned earlier that one of the hardest parts of the CDAO job is actually understanding and trying to determine what the priorities should be, what types of activities to go after, what types of data problems, big or small or otherwise. I would say with that, equally as difficult, is trying to operationalize this. And I think one of the biggest things that have been overlooked for so long is that data itself, it’s always been critical. It’s in our models. We all know about it. Everyone talks about data every minute of every day. However, data has been oftentimes, I think, thought of as exhaust from some product, from some process, from some application, from a feature, from an app, and enough time has not been spent actually ensuring that that data is considered an asset, that that data is of high quality, that it’s fully understood by humans and machines.

And I think it’s just now becoming even more clear that as you get into a world of generative AI, where you have machines trying to do more and more, it’s really critical that it understands the data. And if our humans have a difficult time making it through our data estate, what do you think a machine is going to do? And we have a big focus on our data strategy and ensuring that data strategy means that humans and machines can equally understand our data. And because of that, operationalizing our data has become a big focus, not only of JPMorgan Chase, but certainly in the Chase business itself.

We’ve been on this multi-year journey to actually improve the health of our data, make sure our users have the right types of tools and technologies, and to do it in a safe and highly governed way. And a lot of focus on data modernization, which means transforming the way we publish and consume data. The ontologies behind that are really important. Cloud migration, making sure that our users are in the public cloud, that they have the right compute with the right types of tools and capabilities. And then real-time streaming, enabling streaming, and real-time decision-ing is a really critical factor for us and requires the data ecosystem to shift in significant ways. And making that investment in the data allows us to unlock the power of real-time and streaming.

Laurel: And speaking of data modernization, many organizations have turned to cloud-based architectures, tools, and processes in that data modernization and digital transformation journey. What has JPMorgan Chase’s road to cloud migration for data and analytics looked like, and what best practices would you recommend to large enterprises undergoing cloud transformations?

Mark: We’ve been on this journey for quite some time across JPMorgan Chase and globally. And we have a really solid relationship with our technology partners, with our cloud providers, and we really have ensured that as we move up to the cloud, we do it safely and thoughtfully with a sound strategy and governance and controls. And that’s been the first and foremost piece I would say with regard to a business like Chase and JPMorgan Wealth Management, which into itself is incredibly large and we’ve talked about this publicly many, many times. It is something that requires conviction and a sound data strategy, but at the end of the day, we are not just moving to the public cloud. We’re going to do that with modernized data, but we’re also going to improve governance and controls while improving the user experience.

And to do all of that, it’s a massive undertaking. And to ensure that our data is discoverable and easily usable where our analysts require us to make informed decisions when it comes to these investments, as well as these different types of choices and staging of the work product. And as we think about this, and my advice to others would be to do the same. If you look at the user experience when it comes to your data scientists and your modelers and how they spend their time, what their challenges are, what your analytic priorities are, all those have to be brought together before you actually start building out a data strategy. Otherwise, you’ll be building things that you may not need. And this is already hard enough, why not make it easier by understanding what you’re trying to build, what user population is looking for and then building to that specifically and then staging out in the right appropriate ways?

And that’s been our journey. And we have these milestones. We have goals and everything else. We have OKRs [objectives and key results], we have product teams, we have data engineers. Everyone is aligned and doing this, and we’re focused on doing this in the right way. We’re also focused on ensuring that we can do this in many cloud platforms, not just one. And that requires modern pipelines. It requires us to organize our data differently and inventory it in a certain way and describe it in ways that are easily understandable. This is really difficult work, but it’s well worth the investment. Even if you have to go slow and make little bits of progress year over year, this will absolutely pay off.

Laurel: Speaking of that payoff, working across the company is crucial to meet goals. What is your talent and skills strategy to mobilize cross-functional teams to ensure a data literate workforce that uses both domain and technical knowledge like data science?

Mark: Absolutely. And I’m really proud of our focus on talent, not only across JPMorgan Chase, but at Chase specifically. It has been really difficult to find great talent in this space. And once you have them, you want them to stay, you want them to grow, you want them to feel supported, and you want them to feel challenged, and you want them to be able to experiment and to work and design solutions that are elegant, that meet the needs of customers and that are advanced. And as we think about all of this, there’s a number of buckets that we’re really focused on.

First, in terms of attracting talent, we do have a very robust campus program. We have a very robust internship program, and we have a very robust rotational program that actually spans the firm. And in Chase, this rotational program has existed for many, many, many years. And it really gives data scientists and aspiring data scientists a chance to spend a couple of years with us, move across the bank and the firm, and to really understand what it’s like to work in various different types of settings and before they land in a job or land in a function or a field.

And that’s one piece. It’s really understanding the community, the new talent coming in at campuses, out of graduate programs, out of Ph.D. programs, and making sure that we have the right types of programs that meet their needs. And that’s one piece. We’re also really focused on our existing talent and our existing talent is absolutely incredible. And they come to us because they want to continue to grow. They want to continue to learn. And we’re heavily investing in training to make sure that learning development opportunities are available to our existing employees and design for the different types of data users and the different types of career goals that they have. And that’s a great thing about our field today. There are so many avenues with which you can go.

And it’s really exciting to actually be able to pick in adventure, pick a career with a firm like ours, at JPMorgan Chase. And then as I mentioned before, we are really focused on our communities and giving back. And in addition to our campus programs, we also try and invest in talent that may not actually come to work for us ever. And we do have hackathons. We bring in hundreds of college students twice a year for our campuses. We pay for everything. And they go through a twenty-four-hour hackathon where they work with other teams, meet other students, work with JPMorgan Chase volunteers, and really try to solve problems for a local nonprofit. And those hackathons really are investment in the next generation of analytic talent, but it also gives them an opportunity to work with real data, with real problems, and to learn a little bit and to help build the community.

And then lastly, we have programs around Data for Good, and our employees absolutely love this. We partner with over 30 nonprofits over the past two years to help them solve their needs. And nonprofits are amazing at serving their communities and finding needs. They’re not always great at bringing tech stacks or digital solutions or using data or analytics to help their nonprofits. And we have great partnership with them. All of this encompasses our talent strategy. It’s focused on engaging students early on in the process, experienced hires, developing our core talent, and giving them opportunities to do things beyond their core job, like giving back to their communities.

Laurel: Mark, thank you so much for joining us today on the Business Lab.

Mark: Laurel, thank you so much for having me. It was great to be here.

Laurel: That was Mark Birkhead, firmwide chief data officer at JPMorgan Chase, who I spoke with from Cambridge, Massachusetts, the home of MIT and MIT Technology Review.

That’s it for this episode of Business Lab. I’m your host, Laurel Ruma. I’m the global director of Insights, the custom publishing division of MIT Technology Review. We were founded in 1899 at the Massachusetts Institute of Technology, and you can find us in print, on the web, and at events each year around the world. For more information about us and the show, please check out our website at technologyreview.com.

This show is available wherever you get your podcasts. If you enjoyed this episode, we hope you’ll take a moment to rate and review us. Business Lab is a production of MIT Technology Review. This episode was produced by Giro Studios. Thanks for listening.

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.

This podcast is for informational purposes only and it is not intended as legal, tax, financial, investment, accounting or regulatory advice. Opinions expressed herein are the personal views of the individual(s) and do not represent the views of JPMorgan Chase & Co. The accuracy of any statements, linked resources, reported findings or quotations are not the responsibility of JPMorgan Chase & Co.

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Feb 17 2024

Grow or Die, Says Momentum Shake Founder

Mike Tecku first appeared on this podcast in 2019 as an Amazon marketplace seller. Shortly afterward, he sold that business, a maker of floormats. He retired, became bored, and in 2022 launched Momentum, a direct-to-consumer nutritional shake producer. He and I discussed that venture last year in his second appearance.

He’s back. Momentum Shake is flourishing, as is Tecku. He’s evolved from the nuts and bolts of making money to achieving a purpose, building a team, and self-improvement. “If I’m not growing, I’m dying,” he told me.

Our entire audio conversation is embedded below. The transcript is edited for length and clarity.

Eric Bandholz: Your entrepreneurial journey is impressive.

Mike Tecku: Growth gives me meaning and a sense of being alive. If I’m not growing, I’m dying. The American dream of not having to do anything runs counter to human nature. When I retired, I got good at golf. I read many books but could not shake the urge to solve problems. I’d be in a store and think, “This is an interesting product. I wonder if I could make this.”

I got depressed when I wasn’t working on anything. I could feel myself shrinking. About a year into that, I decided I needed to re-embrace being an entrepreneur. That’s just who I am. Those are my gifts. I wanted to use my gifts and strengths, and now I had the privilege of using them in a way that I wanted, not just to survive or make money.

The world is constantly changing. To make something perfect is impossible, but you can pursue it by continually adjusting. The farther you get along, the more precise the destination is, and the more attuned you are to your goal. You gain knowledge and make better decisions. When you’re really into something, you’re continually growing and perfecting your art.

Bandholz: How does a company strive for perfection?

Tecku: You must develop trust with your customers so they know you have their best interest at heart. If we change the flavoring of our shakes, customers worry we’re making it cheaper when the reality is the opposite. You must be transparent with customers and communicate that you want to add more value without increasing their costs. It’s essential to zoom out beyond supply and demand. What advantage can you bring to the market besides making more money?

I want to produce a product 10 times better than everybody for the same price. Most businesses are just media and marketing platforms. They don’t touch the product. If they’re doing anything at all, they’re selling commodities. I want to make something that is a masterpiece and stacks much value into it.

That wasn’t happening with our outsourced manufacturer. I love those people, but they can’t innovate at the speed I want. I can cut costs by 30% when I take over manufacturing. I can shrink cash flow, increase quantity, reduce costs, and improve quality. The only way to do that is through owning the manufacturing process.

Bandholz: What are the pitfalls of in-house manufacturing?

Tecku: The first step is believing it’s doable. I spent 10 years thinking manufacturing was complicated and beyond my expertise. But I had to start questioning myself. Why can’t I assemble a team of intelligent, hardworking individuals? Why can’t I solve those problems?

The goal is to make manufacturing easy. If I can build something simple and scalable, it will be more secure and reliable. I like to forecast five to seven years down the road. What are my goals? I want to scale to a hundred million dollars. What does that look like in the number of units I need to make a day and the machines capable of that?

I’m buying machines to simplify and reduce the chance of error. We can’t eliminate mistakes, but we can streamline processes, steps, and inputs. The machines I’m buying should be able to make a thousand bags an hour with one employee. That’s a scalable system.

Bandholz: You have a single SKU earning thousands of dollars monthly. You’re not touching it. There’s beauty in that.

Tecku: It is beautiful because it frees me for growth and improvement. Recall the old phrase, “Work on your business, not in it.” That can’t change. You have to be on top looking at the pieces. My job is decision-making. I want two hours of hyper-focused thinking every day.

Constantly executing is not the best use of my skills. Some people are way better at it. I consider all components of the business to be assets. The manufacturing facility I’ve been building for the last six months is an asset. I want it to run perfectly without me. That involves the machines, the space, the team — every decision.

Bandholz: I struggle with shifting from the execution role into strategy and decision-making.

Tecku: I try to check with my team to see if they need something from me. I have to remind myself this is what they’re good at and that they appreciate my trust in them. If you want to create independent people who think for themselves, you have to let them fail. My job is to determine the next step. There’s no right path. It requires a lot of walking around, reading books, talking to folks, and paying attention.

Bandholz: Where can folks follow you?

Tecku: Our site is MomentumShake.com. I’m on LinkedIn.

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Feb 15 2024

How the internet pushed China’s New Year red packet tradition to the extreme

This story first appeared in China Report, MIT Technology Review’s newsletter about technology in China. Sign up to receive it in your inbox every Tuesday.

If you ask any child in China what’s the most exciting thing about welcoming another year, they are likely to answer: the red packets. It’s a festive tradition: During the holidays, people give out red envelopes full of cold hard cash to young members of the family. You can reliably get cash gifts every year until you graduate from school and start working full-time.

So this week is a great opportunity to talk about how the tradition of giving red packets, which has been around for hundreds of years, has evolved in the digital age. Even though I’m not in China now, I still managed to send two red packets to my nephew and niece, through mobile payments on WeChat.

In fact, red packets have not merely turned from a physical activity to a digital one. They’ve become a way for Chinese tech companies to make a stack of money each year and attract new users and traffic. In return, users have to follow increasingly complicated rules to get a few bucks.

The digitization of red-packet giving started in the early 2010s, when super apps like Alipay and WeChat made it convenient for everyone to send and receive money on their phones. They also introduced mechanisms that breathed new life into the tradition, like a randomization allotment system, where people put one giant red packet in a group chat, and everyone opening it will get a random share of the total amount.

The promise of variable rewards increases the feeling of excitement when you get a big share. It also prompted those who didn’t get much to ask for another chance, which has really made it a centerpiece of the new red packet culture.

And it didn’t take long until tech companies became the ones giving out the money.

In 2015, WeChat decided to give out over $80 million in red packets during the Spring Festival Gala, a yearly tradition in China that gathers the family around the TV. To get a share of WeChat’s red packets, people had to shake their phones at a certain time of the show. According to data provided by WeChat, throughout Lunar New Year’s Eve, people shook their phones 11 billion times. At the peak, people shook their phones 800 million times in just one minute.

This immense success inspired every other tech company in China to join the game and spend millions of dollars. Today, every major app offers a version of that promotion during the new year. But what users need to do in return has become much more complicated.

1For example, to participate in one of the red packet events this year on Douyin, the Chinese version of TikTok, users have to complete a series of tasks: log in every day, invite new users to the platform, upload an avatar, follow certain accounts, set up a group chat, post a gif in the group chat, make a video call, upload a video, watch videos for a minimum amount of time, and download other apps. The more time you are willing to spend on these tasks, the more you will get back from the app.

The 2010s saw immense growth in China’s mobile internet sector, and one of the lasting outcomes is that apps have gotten very sophisticated at gamifying their gimmicks to attract users and traffic. The new year’s red packet promotions are essentially the pinnacle of these promotion gimmicks.

As the rules get increasingly convoluted, most people don’t have the time to follow up with every single mini-game. I stopped participating in these red packet promotions years ago because the payout is always abysmal compared to the efforts required. (Am I willing to message five of my college friends whom I haven’t spoken to for years in order to get this $5 cash gift? No.)

But there are still people who treat it seriously. As Chinese publications have reported, some people, particularly those who are less well off, would study the rules of these red packet games thoroughly, hoping to make a fortune with them. Since the games reward social interactions, some people actually pay others with their own money to join in the efforts. New apps have even emerged that connect people who are gaming the system.

This is a side of the Chinese tech world that the outside doesn’t often get to see. The Chinese mobile internet industry is saturated with mini-games or incentives that are designed to chase infinite growth.

Thanks to Temu, the Chinese ultra-fast e-commerce app that’s spending millions of dollars on Super Bowl ads, users outside China can also get a taste of these gimmicks. The spinning wheel of coupons, the never-ending request to invite new friends to join the app, and the farming mini-game to keep you hooked—these are the tactics that Chinese users are all too familiar with.

From what I have heard, most people still see it as a nuisance. But as the longevity of red packet promotions in China shows, once companies find the right audience and the right profitability model, these stunts could become a fact of online life for all of us.

Did you get any digital red packets this year? Let me know your experience at zeyi@technologyreview.com.

Catch up with China

1. Sam Altman’s plan for a $7 trillion-worth semiconductor empire includes building dozens of chip fabrication plants with money from Middle East investors, then having the Taiwanese chipmaker TSMC run them. (Wall Street Journal $)

2. A former TikTok executive is suing the company for unlawfully firing her due to what they called a lack of “docility and meekness.” (Financial Times $)

3. If he’s reelected, Donald Trump is promising a 60% tariff on all Chinese imports. If that actually happens (big if), it would almost wipe out all imports from China by 2030. (Bloomberg $)

For the first time in 22 years, Mexico has surpassed China to be the United States’ largest import source. (ABC News)

4. Members of the European Union have had a falling out because of their different positions on China and how to handle trade across economic sectors. (South China Morning Post $)

5. A new report found more than 100 websites disguised as local news outlets in Europe, Asia, and Latin America are actually part of an influence campaign linked to a Beijing public relations firm. (Reuters $)

6. How Hefei, a city in central China, rose up to become a leader in electric-vehicle production by investing government money in fledgling startups. (New York Times $)

Lost in translation

While we are on the topic of digital red packets, people are selling AI-generated artwork as red packet designs this year, according to the Chinese publication Guokr. After WeChat allowed users to customize what their red packet looks like on the app in 2019, a new business has emerged to let people spend a few bucks and get a new look for their digital gifts every year. Successful artists can make a decent bit of money with it.

However, the industry is now unsurprisingly being disrupted by image-making AIs like Midjourney. There’s even a burgeoning entrepreneurial scene where people repackage these AI services to tailor them to design red packets, simplifying the process. On social media, some people are promising that you can earn quick cash by generating AI red packets, attracting others to cash in on the trend. But in reality, there are still many obstacles to fine-tuning the designs and gaining traction among potential buyers.

One more thing

You might not be able to get an Apple Vision Pro yet, but you can hop on a Hainan Airlines flight, where all passengers are given a pair of augmented reality goggles made by a Chinese company for free in-flight entertainment. They look so much lighter than Apple’s headset. I want to try them out!

Passengers making their way from Shenzhen to Xi'an aboard Hainan Airlines flight HU7874 on February 7th were treated to an immersive entertainment experience with Rokid AR Entertainment Kits.

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Feb 10 2024

How Merchants Rack-up Airline Points

Allen Walton is the founder of SpyGuy, a seller of surveillance cameras from his base in Texas. He’s also a world traveler and a seasoned acquirer of airline travel points. Ecommerce merchants who pay with a rewards credit card for advertising, shipping, and other expenses can “rack-up crazy points,” he told me.

In our recent interview, his third for this podcast, he elaborated on his methods for obtaining cheap airline tickets and hotel accommodations.

The entire audio of our conversation is embedded below. The transcript is edited for clarity and length.

Eric Bandholz: You are the points guy.

Allen Walton: I’m pretty well-versed. For almost 10 years now, I have been paying attention to points and miles and figuring out how to save money, especially on international travel. Many folks come to me for tips, and I am happy to help because I know how meaningful it is to lay flat on a business seat when you’re on your way to meet suppliers in Asia.

If you desire to travel, whether for business or personal, and you’re willing to learn some rules to redeem those points, you could fly business class from the U.S. to Asia or get just under $400 in cash. There are some tricks. Ideally, you must be flexible about when you fly out or your final destination.

Say you’re trying to get to Barcelona in the summer. There might not be something available that gets you the whole way there, but if you’re happy with ending up in Madrid or Paris, there might be something there that’s just a fraction of the price of trying to get to Barcelona. Flexibility opens up the possibilities.

Bandholz: What’s the process?

Walton: Airlines have loyalty programs. American has the AAdvantage program, United has MileagePlus, and Air France has Flying Blue. You can rack-up airline miles from standard fares and redeem those miles for tickets. You can also get airline miles just by making regular credit card purchases. You don’t have to fly on those airlines to rack up their miles.

“Anytime awards” or “everyday awards” are where you pick the exact flight you want on the same date you want, and the airlines will quote you a price that will typically be expensive in terms of points. On United, it might be 200,000 points from New York to Japan or New York to Hong Kong. But there are what’s called “saver awards.” On many flights, the airlines will designate a small number of seats at a saver rate, which might be much less. So, instead of 200,000 points, it might be 80,000. If you know the game’s rules, you can look for these saver seats, which aren’t on every flight, but you can book these awards at a fraction of the average points.

Bandholz: Do you have to switch credit cards to get the maximum points?

Walton: No. Getting a big signup offer, canceling it, and switch cards to max out the number of points is what somebody with a nine-to-five job might do because they don’t spend the amount of money necessary to facilitate redeeming points for miles. You do not need to do that as an ecommerce entrepreneur. When you factor in ad spend, shipping, SaaS, and paying suppliers, your monthly spend on a credit card is so much that you don’t need to do that game. You could stick with one, two, or maybe even three cards and rack up many points from your regular business expenses.

Bandholz: What are the best cards for entrepreneurs?

Walton: There are a few for ecommerce entrepreneurs, particularly the American Express Business Gold Card. For the last decade, it was four points for every dollar of online advertising and shipping. That was big for anyone who advertised online or shipped physical products. You could rack up crazy points. AmEx recently tweaked that card. This year, instead of 4-times on shipping, they added 4-times on software and cloud computing. Klaviyo and ClickUp will be on that, for example. The card has a $400 annual fee but pays itself when you get four points for every dollar you spend. You can start redeeming that for business-class international travel or hotel stays.

The Chase Ink Business Preferred is the next option, but getting multiples of this card is much more challenging. Generally, you need a relationship with the small business banker at Chase, such as your local regional banker. This card gives you 3-times points on online ads and 3-times on shipping. It has a $95 annual fee and a 100,000 signup bonus. You could do a round-trip ticket from the U.S. to Europe in business class just from the signup bonus. And so it’s a card worth picking up if you’ve tapped out on AmEx cards.

You might want to consider looking at a hotel card for loyalty reasons. I have platinum status with Marriott Bonvoy because there are a lot of Marriotts. They give you a 4:00 p.m. checkout, an upgrade to suites, and a free breakfast. Sometimes you have to ask. They won’t do it automatically. It makes it a lot easier to get status for when you’re traveling and want a better hotel experience, specifically the late checkout.

Consider getting another card for any spending that doesn’t have a multiplier.

Bandholz: Where do you search plane tickets by point costs?

Walton: There’s a tool now that I love called Seats.aero. It scans the most popular routes every hour or so. It will tell you when the flight takes off, how many seats are available, and booking options. There’s a free version, but the paid version costs $10 a month and is worth it. They have a bot that crawls all the airlines’ websites. It will find what’s available at that saver level, what date it is on, how much the fees are, and how you book. It’ll explain all that right there, but it’s imperfect and doesn’t include every airline. It misses a lot of stuff.

Bandholz: How can folks connect with you?

Walton: My website is SpyGuy.com. My Twitter handle is @allenthird.

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Feb 3 2024

Marketer Finds Joy in ‘Bigging’ Others

Aaron Orendorff is a chaplain turned writer turned digital marketer. He was the first editor-in-chief at Shopify Plus and then vice president of marketing at Common Thread Collective, an ecommerce agency.

He’s now head of marketing for Recart, an SMS platform. His passion is empowering colleagues and clients. He told me, “I find joy in bigging others up.”

The entire audio of our recent conversation is embedded below. The transcript is edited for length and clarity.

Eric Bandholz: Tell us who you are.

Aaron Orendorff: I’m the head of marketing for Recart. We’re an SMS app for Shopify businesses. My claim to fame is coming up with Shopify Plus. I cut my teeth with Shopify early in ecommerce. I remember writing how-to guides and articles about why you should trust the cloud for ecommerce.

I then moved to the agency side at Common Thread Collective. Now I’m sending text messages.

I didn’t have any background in this industry, nor any clients, pedigree, or connections. My life radically changed a decade ago. I’ll celebrate 11 years of sobriety at the beginning of February.

At the time I was unemployed and unemployable in Klamath Falls, Oregon. I created a website and wrote 10 blog posts to make it look like something was happening. I bought a traffic course from Neil Patel. It said to purchase your first 5,000 followers on Twitter. So I did. I think it screwed me for quite a while, but it helped to look like I was a legit business.

Bandholz: You have a big Twitter following.

Orendorff: Yes. My production rate is so much lower than what I see happening in the world. I’m relentlessly enthusiastic. I find joy in bigging others up.

At my core, I’m a writer. I warn folks when I’m starting to work with them and say, “Listen, I’m going to light you up in this Google Doc more than you’ve ever been in your entire life. The fact that I do that is an act of love. I would not invest in this if I didn’t believe in you.”

Criticism is a gift. Criticism is love because it takes energy, and it takes emotional risk. It’s much easier to fix and ship a thing than tell somebody where they went wrong. You run the risk of them misunderstanding or thinking ill of you. And I care a lot about that.

Bandholz: There is a line between criticism and hate.

Orendorff: That’s a powerful point. I’m fascinated by how to get somebody; how do you get on their side and disagree with them? How do you rapidly build trust? What are the cues? What are the shortcuts to it? What are the heuristics? The rule of thumb?

Bandholz: It’s just authenticity, right? You have to be authentic. From there, you build trust. Where can people follow you?

Orendorff: @AaronOrendorff on Twitter or find me on LinkedIn. If you need help with text marketing, visit Recart.com.

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App Business

Jan 31 2024

Why the world’s biggest EV maker is getting into shipping

Earlier this month, a massive ship picked up over 5,000 electric cars from two ports in northern and southern China. Five days later, it passed through Singapore, and it is now headed for India. However, its final destination is in Europe, where most of the cars will be sold.

The ship’s name is BYD Explorer No.1. As the first of a massive fleet that BYD is building, it reflects the Chinese company’s ambition to establish a seafaring business that supports its new role in the global car trade.

BYD, founded by a Chinese metallurgy researcher named Wang Chuanfu in 1995, started out making small batteries for mobile devices. It later expanded its business to automobiles and eventually combined the two to make electric vehicles. In two decades, it became China’s largest EV maker. By the fourth quarter of 2023, it was the world’s.

BYD offers a lot of options, ranging from affordable sedans to luxury SUVs, and there’s rising appetite for its cars overseas. In 2023, BYD exported over 240,000 vehicles, up from 55,000 in 2022. But it’s run into a snag: to get the most financial benefit from its exploding popularity abroad, it’s having to expand beyond the car trade into the shipping business.

The shortage of car-carrier vessels

To understand why BYD has made this move, you need to learn a little about how cars are transported across the sea. Usually, the cargo industry uses roll-on/roll-off (RORO) ships. Unlike ships that use a crane to lift up cargo and place it aboard, RORO ships have ramps that allow vehicles to be driven directly on, making the whole process much easier.

But these ships have been in short supply for the past few years. While old vessels have been entering retirement, new ship orders were down because of the 2008 financial crisis and the industry-wide upgrade to more environmentally friendly fuels, leaving a shortfall.

Also, most car companies have longstanding relationships with shipping firms or own their own fleets of boats. For example, Japanese car makers like Nissan and Toyota each have fleets of RORO ships that can carry tens of thousands of cars. But China’s domestic car-carrier vessels represent only 2.8% of global shipping capacity, leaving the Chinese brands few options for getting their cars across the seas.

As a result, their access to RORO ships has become prohibitively expensive. According to Clarksons Research, the intelligence arm of the world’s largest shipping services provider, the price to rent (or charter, as the industry says) a car-carrier ship for a day skyrocketed to $115,000 in 2023, a historical high and close to seven times the average pre-pandemic price, which was around $17,000 in 2019.

New demand to ship cars predominantly comes from China right now. The country is on the verge of becoming the world’s largest car exporter (in fact, it may already have gained that status in 2023, but we won’t know until the official numbers are finalized). It exports a mix of traditional gas cars, electric cars made by Chinese companies, and Tesla cars manufactured in the Giga Shanghai plant.

The shortage of shipping capacity is what’s standing in its way.

Venturing out by themselves

That’s why Chinese auto companies, which have become such prominent exporters thanks to the rise of EVs, are starting to form their own shipping businesses.

News that BYD was looking to buy or charter ships was first reported by the shipping outlet Lloyd’s List in late 2022. In December that year, the company changed its corporate registration to include the business of international cargo shipping and ship management. MIT Technology Review contacted BYD for comment, but it did not respond in time for publication.

BYD Explorer No.1 was delivered at the beginning of this year. The RORO vessel, which can carry 7,000 cars at the same time, is officially registered under Zodiac Maritime, a UK company controlled by the Israeli shipping tycoon Eyal Ofer, but BYD has leased it for an undisclosed period of time. In a press release, BYD says it plans to add seven more vessels to the fleet in the next two years. It also plans to let other companies export their vehicles using BYD’s ships, it says.

For its maiden voyage, the ship is carrying over 5,000 BYD vehicles and heading toward the ports of Vlissingen in the Netherlands and Bremerhaven in Germany, according to Chinese state media outlet Xinhua.

BYD is not the only Chinese automaker making this move. SAIC Motor, a Chinese state-owned company, sold 1.2 million vehicles overseas in 2023, 24% of which were EVs. It formed a RORO shipping subsidiary in 2021, and its newest RORO vessel, the largest of its kind and able to carry 7,600 cars, also set sail for the first time in January. Like BYD Explorer No.1, it’s going to Europe.

While BYD has announced that it will add energy-storing battery tech to its vessels, the RORO ships it’s chartering today are not electric yet. Most of the newer ships can be powered by either traditional fuel or liquefied natural gas, which is a cleaner energy source.

From carrying wood pulp to cars

It will be some time before these Chinese companies finish assembling their sea freight empires, as these massive new ships take years to build. In the meantime, some have turned to creative fixes for the supply shortage: repurposing ships that were designed for other types of cargo.

Particularly, they have their eyes on gigantic ships typically used to import thousands of tons of wood pulp from South America to China, where it’s made into everyday products like tissue, paper, and books. These wood-pulp carriers often end up empty or barely loaded on the way back, because China doesn’t have similar products to export.

However, in recent years Chinese car companies have started to sell their vehicles to the South American continent, and shipping companies saw an opportunity there. China Ocean Shipping Company (COSCO), one of the largest shipping companies in the world, designed a foldable rack that can load cars and stack them up into a wood-pulp carrier. In July last year, COSCO loaded such a ship with over 2,700 cars and sent them to Brazil.

With makeshift arrangements like this and new RORO vessels being built, shipping bottlenecks for Chinese automakers could be significantly reduced in the next couple of years. Having their own fleets or chartering ships from domestic shipping companies could also further drive down costs, making Chinese cars even more competitive abroad.

And just as the auto industry in Japan and South Korea has pushed these two countries to become global leaders in shipping, EVs could make China a major player in the ocean too.

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Jan 30 2024

Actionable insights enable smarter business buying

For decades, procurement was seen as a back-office function focused on cost-cutting and supplier management. But that view is changing as supply chain disruptions and fluctuating consumer behavior ripple across the economy. Savvy leaders now understand procurement’s potential to deliver unprecedented levels of efficiency, insights, and strategic capability across the business.

However, tapping into procurement’s potential for generating value requires mastering the diverse needs of today’s global and hybrid businesses, navigating an increasingly complex supplier ecosystem, and wrangling the vast volumes of data generated by a rapidly digitalizing supply chain. Advanced procurement tools and technologies can support all three.

Purchasing the products and services a company needs to support its daily operations aggregates thousands of individual decisions, from a remote worker selecting a computer keyboard to a materials expert contracting with suppliers. Keeping the business running requires procurement processes and policies set by a chief procurement officer (CPO) and team who “align their decisions with company goals, react to changes with speed, and are agile enough to ensure a company has the right products at the right time,” says Rajiv Bhatnagar, director of product and technology at Amazon Business.

At the same time, he says, the digitalization of the supply chain has created “a jungle of data,” challenging procurement to “glean insights, identify trends, and detect anomalies” with record speed. The good news is advanced analytics tools can tackle these obstacles, and establish a data-driven, streamlined approach to procurement. Aggregating the copious data produced by enterprise procurement—and empowering procurement teams to recognize and act on patterns in that data—enables speed, agility, and smarter decision-making.

Today’s executives increasingly look to data and analytics to enable better decision-making in a challenging and fast-changing business climate. Procurement teams are no exception. In fact, 65% of procurement professionals report having an initiative aimed at improving data and analytics, according to The Hackett Group’s 2023 CPO Agenda report.

And for good reason—analytics can significantly enhance supply chain visibility, improve buying behavior, strengthen supply chain partnerships, and drive productivity and sustainability. Here’s how.

Gaining full visibility into purchasing activity

Just getting the full view of a large organization’s procurement is a challenge. “People involved in the procurement process at different levels with different goals need insight into the entire process,” says Bhatnagar. But that’s not easy given the layers upon layers of data being managed by procurement teams, from individual invoice details to fluctuating supplier pricing. Complicating matters further is the fact that this data exists both within and outside of the procurement organization.

Fortunately, analytics tools deliver greater visibility into procurement by consolidating data from myriad sources. This allows procurement teams to mine the most comprehensive set of procurement information for “opportunities for optimization,” says Bhatnagar. For instance, procurement teams with a clear view of their organization’s data may discover an opportunity to reduce complexity by consolidating suppliers or shifting from making repeated small orders to more cost-efficient bulk purchasing.

Identifying patterns—and responding quickly

When carefully integrated and analyzed over time, procurement data can reveal meaningful patterns—indications of evolving buying behaviors and emerging trends. These patterns can help to identify categories of products with higher-than-normal spending, missed targets for meeting supplier commitments, or a pattern of delays for an essential business supply. The result, says Bhatnagar, is information that can improve budget management by allowing procurement professionals to “control rogue spend” and modify a company’s buying behavior.

In addition to highlighting unwieldy spending, procurement data can provide a glimpse into the future. These days, the world moves at a rapid clip, requiring organizations to react quickly to changing business circumstances. Yet only 25% of firms say they are able to identify and predict supply disruptions in a timely manner “to a large extent,” according to Deloitte’s 2023 Global CPO survey.

“Machine learning-based analytics can look for patterns much faster,” says Bhatnagar. “Once you have detected a pattern, you can take action.” By detecting patterns in procurement data that could indicate supply chain interruptions, looming price increases, or new cost drivers, procurement teams can proactively account for market changes. For example, a team might enable automatic reordering of an essential product that is likely to be impacted by a supply chain bottleneck.

Sharing across the partner ecosystem

Data analysis allows procurement teams to “see some of the challenges and react to them in real-time,” says Bhatnagar. But in an era of interconnectedness, no one organization acts alone. Instead, today’s supplier ecosystems are deeply interconnected networks of supply-chain partners with complex interdependencies.

For this reason, sharing data-driven insights with suppliers helps organizations better pinpoint causes for delays or inaccurate orders and work collaboratively to overcome obstacles. Such “discipline and control” over data, says Bhatnagar, not only creates a single source of truth for all supply-chain partners, but helps eliminate finger-pointing while also empowering procurement teams to negotiate mutually beneficial terms with suppliers.

Improving employee productivity and satisfaction

Searching for savings opportunities, negotiating with suppliers, and responding to supply-chain disruptions—these time-consuming activities can negatively impact a procurement team’s productivity. However, by relying on analytics to discover and share meaningful patterns in data, procurement teams can shift focus from low-value tasks to business-critical decision-making.

Shifting procurement teams to higher-impact work results in a better overall employee experience. “Using analytics, employees feel more productive and know that they’re bringing more value to their job,” says Bhatnagar.

Another upside of heightening employee morale is improved talent retention. After all, workers with a sense of value and purpose are likelier to stay with an employer. This is a huge benefit in a time when nearly half (46%) of CPOs cite the loss of critical talent as a high or moderate risk, according to Deloitte’s 2023 Global CPO survey.

Meeting compliance metrics and organizational goals

Procurement analytics can also deliver on a broader commitment to changing how products and services are purchased.

According to a McKinsey Global Survey on environmental, social, and governance (ESG) issues, more than nine in ten organizations say ESG is on their agenda. Yet 40% of CPOs in the Deloitte survey report their procurement organizations need to define or measure their own set of relevant ESG factors.

Procurement tools can bridge this gap by allowing procurement teams to search for vendor or product certifications and generate credentials reports to help them shape their organization’s purchases toward financial, policy, or ESG goals. They can develop flexible yet robust spending approval workflows, designate restricted and out-of-policy purchases, and encourage the selection of sustainable products or preference for local or minority-owned suppliers.

“A credentials report can really allow organizations to improve their visibility into sustainability [initiatives] when they’re looking for seller credentials or compliant credentials,” says Bhatnagar. “They can track all of their spending from diverse sellers or small sellers—whatever their goals are for the organization.”

Delivering the procurement of tomorrow

Advanced analytics can free procurement teams to glean meaningful insights from their data—information that can drive tangible business results, including a more robust supplier ecosystem, improved employee productivity, and a greener planet.

As supply chains become increasingly complex and the ecosystem increasingly digital, data-driven procurement will become critical. In the face of growing economic instability, talent shortages, and technological disruption, advanced analytics capabilities will enable the next generation of procurement.

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.

Learn how Amazon Business is leveraging AI/ML to offer procurement professionals more efficient processes, a greater understanding of smart business buying habits and, ultimately, reduced prices.

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Jan 28 2024

People are worried that AI will take everyone’s jobs. We’ve been here before.

MIT Technology Review is celebrating our 125th anniversary with an online series that draws lessons for the future from our past coverage of technology.

It was 1938, and the pain of the Great Depression was still very real. Unemployment in the US was around 20%. Everyone was worried about jobs.

In 1930, the prominent British economist John Maynard Keynes had warned that we were “being afflicted with a new disease” called technological unemployment. Labor-saving advances, he wrote, were “outrunning the pace at which we can find new uses for labour.” There seemed to be examples everywhere. New machinery was transforming factories and farms. Mechanical switching being adopted by the nation’s telephone network was wiping out the need for local phone operators, one of the most common jobs for young American women in the early 20th century.

Were the impressive technological achievements that were making life easier for many also destroying jobs and wreaking havoc on the economy? To make sense of it all, Karl T. Compton, the president of MIT from 1930 to 1948 and one of the leading scientists of the day, wrote in the December 1938 issue of this publication about the “Bogey of Technological Unemployment.”

How, began Compton, should we think about the debate over technological unemployment—“the loss of work due to obsolescence of an industry or use of machines to replace workmen or increase their per capita production”? He then posed this question: “Are machines the genii which spring from Aladdin’s Lamp of Science to supply every need and desire of man, or are they Frankenstein monsters which will destroy man who created them?” Compton signaled that he’d take a more grounded view: “I shall only try to summarize the situation as I see it.”

His essay concisely framed the debate over jobs and technical progress in a way that remains relevant, especially given today’s fears over the impact of artificial intelligence. Impressive recent breakthroughs in generative AI, smart robots, and driverless cars are again leading many to worry that advanced technologies will replace human workers and decrease the overall demand for labor. Some leading Silicon Valley techno-optimists even postulate that we’re headed toward a jobless future where everything can be done by AI.

While today’s technologies certainly look very different from those of the 1930s, Compton’s article is a worthwhile reminder that worries over the future of jobs are not new and are best addressed by applying an understanding of economics, rather than conjuring up genies and monsters.

Uneven impacts

Compton drew a sharp distinction between the consequences of technological progress on “industry as a whole” and the effects, often painful, on individuals.

For “industry as a whole,” he concluded, “technological unemployment is a myth.” That’s because, he argued, technology “has created so many new industries” and has expanded the market for many items by “lowering the cost of production to make a price within reach of large masses of purchasers.” In short, technological advances had created more jobs overall. The argument—and the question of whether it is still true—remains pertinent in the age of AI.

Then Compton abruptly switched perspectives, acknowledging that for some workers and communities, “technological unemployment may be a very serious social problem, as in a town whose mill has had to shut down, or in a craft which has been superseded by a new art.”

Even those who agreed that jobs will come back in “the long run” were concerned that “displaced wage-earners must eat and care for their families ‘in the short run.’”

This analysis reconciled the reality all around—millions without jobs—with the promise of progress and the benefits of innovation. Compton, a physicist, was the first chair of a scientific advisory board formed by Franklin D. Roosevelt, and he began his 1938 essay with a quote from the board’s 1935 report to the president: “That our national health, prosperity and pleasure largely depend upon science for their maintenance and their future improvement, no informed person would deny.”

Compton’s assertion that technical progress had produced a net gain in employment wasn’t without controversy. According to a New York Times article written in 1940 by Louis Stark, a leading labor journalist, Compton “clashed” with Roosevelt after the president told Congress, “We have not yet found a way to employ the surplus of our labor which the efficiency of our industrial processes has created.”

As Stark explained, the issue was whether “technological progress, by increasing the efficiency of our industrial processes, take[s] jobs away faster than it creates them.” Stark reported recently gathered data on the strong productivity gains from new machines and production processes in various sectors, including the cigar, rubber, and textile industries. In theory, as Compton argued, that meant more goods at a lower price, and—again in theory—more demand for these cheaper products, leading to more jobs. But as Stark explained, the worry was: How quickly would the increased productivity lead to those lower prices and greater demand?

As Stark put it, even those who agreed that jobs will come back in “the long run” were concerned that “displaced wage-earners must eat and care for their families ‘in the short run.’”

World War II soon meant there was no shortage of employment opportunities. But the job worries continued. In fact, while it has waxed and waned over the decades depending on the health of the economy, anxiety over technological unemployment has never gone away.

Automation and AI

Lessons for our current AI era can be drawn not just from the 1930s but also from the early 1960s. Unemployment was high. Some leading thinkers of the time claimed that automation and rapid productivity growth would outpace the demand for labor. In 1962, MIT Technology Review sought to debunk the panic with an essay by Robert Solow, an MIT economist who received the 1987 Nobel Prize for explaining the role of technology in economic growth and who died late last year at the age of 99.

1962 cartoon of Robert Solow walking past three scarecrows and whistling nonchalantly — Robert Solow’s 1962 essay was illustrated by a cartoon of a Solow-looking character whistling past a trio of straw men (presumably jobless ones).

In his piece, titled “Problems That Don’t Worry Me,” Solow scoffed at the idea that automation was leading to mass unemployment. Productivity growth between 1947 and 1960, he noted, had been around 3% a year. “That’s nothing to be sneezed at, but neither does it amount to a revolution,” he wrote. No great productivity boom meant there was no evidence of a second Industrial Revolution that “threatens catastrophic unemployment.” But, like Compton, Solow also acknowledged a different type of problem with the rapid technological changes: “certain specific kinds of labor … may become obsolete and command a suddenly lower price in the market … and the human cost can be very great.”

These days, the panic is over artificial intelligence and other advanced digital technologies. Like the 1930s and the early 1960s, the early 2010s were a time of high unemployment, in this case because the economy was struggling to recover from the 2007–’09 financial crisis. It was also a time of impressive new technologies. Smartphones were suddenly everywhere. Social media was taking off. There were glimpses of driverless cars and breakthroughs in AI. Could those advances be related to the lackluster demand for labor? Could they portend a jobless future?

Again, the debate played out in the pages of MIT Technology Review. In a story I wrote titled “How Technology Is Destroying Jobs,” economist Erik Brynjolfsson and his colleague Andrew McAfee argued that technological change was eliminating jobs faster than it was creating them. This wasn’t just about a mill shutting down. Rather, advanced digital technologies were leading to job losses across a broad swath of the economy, raising the specter once again of technological unemployment.

Like the 1930s and the early 1960s, the early 2010s were a time of high unemployment.

It’s difficult to pinpoint a single cause for something as complex as a dip in total employment—it could be just a result of sluggish economic growth. But it was becoming increasingly obvious, both in the data and in everyday observations, that new technologies were changing the types of jobs in demand—and while that was nothing new, the scope of the transition was troubling, and so was the speed at which it was happening. Industrial robots had killed off many well-paying manufacturing jobs in places like the Rust Belt, and now AI and other digital technologies were coming after clerical and office jobs—and even, it was feared, truck driving.

In his farewell speech before leaving office in January 2017, President Barack Obama spoke about “the relentless pace of automation that makes a lot of good middle-class jobs obsolete.” By that time, it was clear that Compton’s optimism needed to be rethought. Technical progress was not turning out to lead to inevitable job growth, and the pain was not limited to a few specific locations and industries.

Why Musk is wrong

In an interview late last year with the UK prime minister, Rishi Sunak, Elon Musk declared there will come a time when “no job is needed,” thanks to an AI “magic genie that can do everything you want.” Musk added that as a result, “we won’t have universal basic income, we’ll have universal high income”—apparently answering Compton’s rhetorical question about whether machines will be “the genii which … supply every need and desire of man.”

It might not be possible to prove Musk wrong, since he gave no timeline for his utopian prediction; in any case, how do you argue against the power of a magical genie? But the end-of-work meme is a distraction as we figure out the best way to use AI to expand the economy and create new jobs.

Breakthroughs in generative AI, such as ChatGPT and other large language models, will likely transform the economy and labor markets. But there’s no convincing evidence that we’re on a path to a jobless future. To paraphrase Solow, we should worry about that when there’s a problem to worry about.

Even a bullish estimate about the effects of generative AI by Goldman Sachs puts its impact on productivity growth at around 1.5% a year over the next 10 years. That, as Solow might say, is nothing to sneeze at, but it’s not going to end the need for workers. The Goldman Sachs report calculated that roughly two-thirds of US jobs are “exposed to some degree of automation by AI.” Yet this conclusion is often misinterpreted—it doesn’t mean all those jobs will be replaced. Rather, as the Goldman Sachs report notes, most of these positions are “only partially exposed to automation.” For many of these workers, AI will become part of the workday and won’t necessarily lead to layoffs.

The end-of-work meme is a distraction as we figure out the best way to use AI to expand the economy and create new jobs.

One critical wild card is how many new jobs will be created by AI even as existing ones disappear. Estimating such job creation is notoriously difficult. But MIT’s David Autor and his collaborators recently calculated that 60% of employment in 2018 was in types of jobs that didn’t exist before 1940. One reason innovation has created so many new jobs is that it has increased the productivity of workers, augmenting their capabilities and expanding their potential to do new tasks. The bad news: this job creation is countered by the labor-destroying impact of automation when it’s used to simply replace workers. As Autor and his coauthors conclude, one of the key questions now is whether “automation is accelerating relative to augmentation, as many researchers and policymakers fear.”

In recent decades, companies have often used AI and advanced automation to slash jobs and cut costs. There’s no economic rule that innovation will in fact favor augmentation and job creation over this type of automation. But we have a choice going forward: we can use technology to simply replace workers, or we can use it to expand their skills and capabilities, leading to economic growth and new jobs.

One of the lasting strengths of Compton’s 1938 essay was his argument that companies needed to take responsibility for limiting the pain of any technological transition. His suggestions included “coöperation between industries of a community to synchronize layoffs in one company with new employment in another.” That might sound outdated in today’s global economy. But the underlying sentiment remains relevant: “The fundamental criterion for good management in this matter, as in every other, is that the predominant motive must not be quick profits but best ultimate service of the public.”

At a time when AI companies are gaining unprecedented power and wealth, they also need to take greater responsibility for how the technology is affecting workers. Conjuring up a magical genie to explain an inevitable jobless future doesn’t cut it. We can choose how AI will define the future of work.

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Jan 20 2024

Beardbrand Survives Its Hardest Year

Hosting “Ecommerce Conversations” is a welcome respite from my day job of running Beardbrand, the direct-to-consumer company I co-founded in 2012. I periodically post podcast updates on Beardbrand’s performance, hoping the transparency helps other entrepreneurs.

Here’s my recap of 2023.

It was a terrible year for me and Beardbrand. It was the first year we were in the red. We’ve always had around 15% margins, but not in 2023

I described the year in this week’s episode, embedded below. The transcript is condensed and edited for clarity.

Losses

Beardbrand generates revenue primarily through our website but also via wholesale accounts. Sales from our site were down 53% from the peak of 2021 — our best year. They decreased slightly in 2022, but profit increased because we lowered expenses. In 2023, profit and sales continued to decline significantly. A huge tax bill last April was the downside of being so profitable in 2022. We’ve always had tax bills, which we paid on time, but it was difficult this time with the other losses.

Then we got hit with a tax lien early last year. The state of Texas audited us for sales tax compliance. We had to pay additional taxes, penalties, and fees. They gave us 30 days. Fortunately, we run a very conservative business and have emergency savings. We paid the state and the IRS simultaneously, plus some hefty bills from the holiday season. Thus all our cash went out the door at the beginning of 2023.

Another loss at that time was a mistaken 100%-off discount code. I created it about eight years ago, and somehow, it was reachable on our website. It was leaked to a Facebook group or on TikTok. We had roughly $30,000 worth of products purchased with this code. None of us here caught it.

Target was a key wholesale account for about five years. We lost that business in 2023. The staff there simply stopped replying to our emails after we proposed 2023 plans. We emailed, “If you don’t reply, we’ll assume you won’t carry our products from now on. We’ll adjust our order projections.”

We had purchased a lot of specialized inventory for Target that we could not sell elsewhere. We destroyed about $500,000 worth of unsalable products at the end of the year. Additionally, Target now claims we owe chargebacks for markdowns, which we strongly dispute. They have refused to pay about $170,000 of invoices over the disagreement.

We faced more challenges. My business partner had her third baby and decided to step back from the company. It’s been a challenge not having her in the day-to-day. We furloughed our entire team to half-time this past summer, and our organic YouTube content performed worse than ever. We tried TikTok Shops with the recommendation from Paul at BK Beauty, but it wasn’t effective for us. Lastly, we were sued for accessibility reasons despite the website’s excellent accessibility rating.

Wins

Our biggest win was having enough savings to cover our losses, tax bills, and unsalable products. Conserving cash over the years finally paid off.

We were fortunate not to have lost employees. Everyone we furloughed stuck through the hard times and returned to full-time in August.

Since June, we’ve been profitable, but not at the margins I’m comfortable with. We’ve plugged the holes in our boat. Now we’ve got to get the wind behind the sails.

Part of our sales drop was due to manufacturing glitches and launching products that did not meet customers’ expectations. We’ve resolved many product concerns by returning to our old-school formulations and finding manufacturers who align more with our production needs.

Another win was raising our prices in June. Our average order went from $48 to $60. We’re getting fewer orders, but our per-order fulfillment and shipping costs are a smaller percentage. That’s been nice. We pay less to our outsourced fulfillment vendor.

Another big win is increasing sales from product subscriptions. We went from about 1,100 product subscribers to about 3,000. I see that growth continuing into 2024.

For years we did not sell on Amazon. We launched there in 2023 and reached a $1 million annual run rate by year-end. Hopefully, Amazon will become a seven-figure channel in 2024 and beyond.

A final win was starting a new marketing strategy. After talking with the founders of Batch cannabis, we introduced an affiliate program. We’ve had good promotions and referrals from our affiliate partners, with excellent articles and other placements. We hope the program grows, not just in affiliate revenue but also in improved organic search traffic.

Looking Forward

Despite the challenges, I remain optimistic. Twelve years in, I’m as motivated as on day one to roll out new products and serve our customers. Tough times require perseverance to pull through.

We had many manufacturing problems in 2023. We’re excited to grow with a manufacturer that aligns with us. We will take it slow, one product at a time. We’ve learned the benefits of a tightly aligned partnership with one manufacturer versus diversifying with several.

We continue to focus on Meta for customer acquisition. We haven’t given up on our YouTube organic strategy. We plan on introducing a new video format. If that does not perform, we might shut down YouTube organic and focus on other avenues. We hope Amazon sales continue to grow and eventually replace what we lost on Target.

But our top priority is getting back to 15 to 20% profitability. That would help me sleep better at night.

I want to build Beardbrand. To me, the destination is the journey. Creating a business my kids can grow up around brings me joy and excitement. I’m aiming for a generational company that my kids and grandkids can run, allowing our family to live happy, healthy, functional lives. That’s why I show up every day.

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App Business

Jan 7 2024

The race to produce rare earth materials

Abandoning fossil fuels and adopting lower-carbon technologies are our best options for warding off the accelerating threat of climate change. Access to rare earth elements, key ingredients in many of these technologies, will partly determine which countries will meet their goals for lowering emissions or increasing the proportion of electricity generated from non-fossil-fuel sources. But some nations, including the US, are increasingly worried about whether the supply of those elements will remain stable.

According to the International Energy Agency, demand for rare earth elements is expected to reach three to seven times current levels by 2040; demand for other critical minerals such as lithium may multiply 40-fold. Delivering on the 2016 Paris Agreement, under which signatory nations are obligated to reduce emissions to cap the global temperature increase, would require the global mineral supply to quadruple within the same time frame. At the current rate, supply is on track to merely double.

Obtaining rare earth elements begins with obtaining source materials, which can happen, broadly, in three ways: primary extraction, or mining directly from the earth; recovery from secondary sources, such as end-of-life electronics; and extraction from unconventional sources, including industrial wastes like coal ash and waste products from mines. But China so dominates the market—it controlled 60% of global production in 2021—that other countries are at a disadvantage. After China announced export restrictions in 2023 on gallium, germanium, and graphite, nations scrambled to find alternative sources in anticipation of future restrictions.

Primary extraction in the US is limited; only one active mine, the Mountain Pass Rare Earth Mine and Processing Facility in California, produces rare earth elements domestically. Opening new mines can take decades. As a result, scientists and companies alike are intent on increasing access and improving sustainability by exploring secondary or unconventional sources.

Finding critical materials

All but one of the 17 rare earth elements appear on a 2022 list of 50 designated “critical materials”—meaning they are economically important yet vulnerable to supply disruption. The 17, such as praseodymium (used in aircraft engines), gadolinium (used in MRI imaging), and neodymium (used in computer hard drives), include the “lanthanide series”—the 15 elements with atomic numbers 57 to 71 near the bottom of the periodic table—as well as two chemically similar elements. The “rare” in “rare earth elements” refers not to the quantity available but rather to their wide dispersion—it’s hard to find an economically meaningful quantity in a single location.

One unconventional source of rare earth elements is coal ash, the residual solid waste from burning coal at power plants. Historically, coal ash has often been mixed with water to form a slurry that is stored in ponds (also called surface impoundments). This ash, which contains elevated concentrations of rare earth elements, could be a significant domestic source of the materials in former US coal towns, which face challenges due to plant closures. There are more than 1,000 coal ash ponds across the US, mostly spread across the eastern part of the country. One of the largest facilities, Plant Barry in Mobile County, Alabama, contains more than 21 million tons of ash spread over 600 acres.

These ponds are not harmless; according to the US Environmental Protection Agency, improper management of them can compromise waterways, groundwater, drinking water, and air via contaminants such as mercury, cadmium, and arsenic. A document submitted by Earthjustice, a nonprofit environmental law organization, and Earthworks, a nonprofit focused on preventing the destructive impacts of oil, gas, and mineral extraction, responding to a 2023 request for information from the US Department of Energy, noted that “91% of power plants storing coal combustion residuals (CCRs) are polluting the underlying groundwater to levels that exceed federal drinking water standards.” Ponds can also be destabilized during extreme weather events, and the resulting flood of contaminated material can destroy wildlife, damage property, and threaten community health and safety.

A startup, Rivalia Chemical, believes the health hazard posed by ash ponds can be addressed by repurposing ash to create a domestic supply of rare earth elements. Laura Stoy, the environmental engineer who founded Rivalia in 2021, says she is motivated by both environmental concerns and the potential for economic revitalization.

Stoy began developing Rivalia’s flagship technology during graduate school at the Georgia Institute of Technology and is now working to scale it within the Chain Reaction Innovations program at the DOE’s Argonne National Laboratory. In 2019, Georgia Tech supported the budding company in filing a patent (currently pending) for its technology, for which Rivalia holds an exclusive license.

That technology extracts rare earth elements from coal ash, leaving behind a solution rich in those elements and a residual solid containing iron and other metals. Through sequential steps of heating and cooling, rare earths are transferred into an ionic liquid—a salt in liquid state—via a proton-exchange mechanism. Acid-based reduction techniques and salt-based leaching can reduce the amount of iron in the final solution, after which rare earths must be further separated to produce pure metals or oxides. Rivalia can sell primary outputs to companies that handle subsequent processing steps, manufacturers using rare earths, and sell residual solids to concrete producers. Stoy says Rivalia’s efforts will produce materials that could be used for cleaner products and alternative energy sources. Furthermore, they could help reduce the carbon footprint of concrete production by repurposing the solid residue as a replacement for emission-heavy Portland cement—a major ingredient in concrete. (For more on this, see “Climate’s hardest problems”.)

Rivalia prefers to work with existing waste products as opposed to coal that has not yet been burned. This approach is risky; extraction from unconventional sources can cost more than mining, given the low concentrations of rare earth elements and the greater initial concentration of toxic contaminants.

Still, Stoy says, this is a strategic move in light of the need to diversify supply. It’s also an opportunity to make use of a widely available material with few alternative uses and significant economic value; the value of rare earth elements in US coal ash reserves was previously estimated at $4.3 billion (based on 2013 prices) and has likely grown since then. As a fairly new startup, the company is still in the R&D stage and is currently focused on reducing extraction costs.

“I want to be one player in a big ecosystem where there’s a lot of folks producing rare earths. That’s the best outcome for everyone.”

The race to produce rare earth elements domestically in the US is, at least partially, an attempt to figure out how to do so economically; however, companies are unlikely to get production costs low enough to be able to compete on price alone. Experts hope consumers will be willing to pay a premium, partly absorbing the increased costs.

“Hopefully there is a market for a domestically produced material that’s produced in an environmentally conscious manner and an ethical manner that’s respectful of the workers producing the material,” says Evan Granite, program manager for the carbon ore program at the DOE’s Office of Fossil Energy and Carbon Management.

Regulators have started addressing the coal ash problem, so startups hoping to use the material will need to watch ongoing developments closely. The EPA began regulating the management of coal ash ponds in 2015 following destructive spills in 2008 and 2014. A recently proposed update to the 2015 rule mandates that older, inactive ponds that were previously exempt be covered or excavated.

Following the 2015 regulation, Earthjustice said that closing ponds by capping them in place is insufficient if they are within five feet of groundwater, and that in such cases only full excavation will prevent future damage. Either option—capping or excavation—would make coal ash harder to access for companies like Rivalia. Stoy says she considers this a reason to move decisively.

Stoy says she is wary of inadvertently creating new markets for coal by-products, which could jeopardize the country’s clean-energy ambitions. Ironically, if utilities stopped using coal, Rivalia’s source materials would eventually dry up. However, she isn’t worried just yet—even in the absence of new production, the US now has 2 billion metric tons of ash, and many other countries seem likely to continue burning coal for the foreseeable future.

Handling all that ash will have to be done with care, says Lisa Evans, senior counsel in the clean-energy program at Earthjustice. Evans says that even for companies motivated by cleanup hopes, additional regulatory oversight is needed to ensure they dispose of by-products appropriately. “What I’ve experienced in so many years of looking at how industries behave is that they don’t do anything they’re not required to do,” she says, adding that the government should also ensure that communities receive adequate notice of nearby extraction activities.

Modernizing extraction

Another unconventional source of critical materials is tailings—the waste products of mines themselves. The EPA does not yet regulate mine tailings, even though they are similar to coal ash in the environmental risks they pose, says Evans of Earthjustice.

Phoenix Tailings is a Massachusetts-based startup extracting rare earth elements from mining sites. Two of Phoenix’s founders, who grew up in communities affected by mining, say they are motivated by personal experience in addition to the growing demand for rare earth elements.

Besides the four rare earths used most commonly in magnets (neodymium, praseodymium, dysprosium, and terbium), Phoenix recovers battery metals, platinum group metals, low-carbon irons, and other materials in what it calls a “portfolio approach” that improves economic viability. Like Rivalia, Phoenix repurposes residual materials into concrete and other aggregates. This, the company says, provides long-term storage for carbonaceous materials, reducing environmental impact by trapping them and preventing them from ending up in the water supply.

Phoenix works to modernize extraction, reducing the amount of energy, equipment, and funding required, says cofounder Anthony Balladon. “You develop chemistries that are tuned for the rare earths, as opposed to trying to brute-force your way through them,” he says.

After obtaining an oxide concentrate containing the rare earths, Phoenix uses separation techniques to draw out the desired end products. This is followed by reduction into final metal and alloy products using mixed-halide molten-salt electrolysis, resulting in 35% to 45% lower energy requirements. Chief technology officer Tomás Villalón says Phoenix’s process reduces the amount of material inadvertently lost between processing steps and improves the purity of the final product. Phoenix’s founders also highlight the sustainability of the company’s process, which they say uses no hazardous materials and creates zero direct carbon emissions. The company is currently producing rare earth metals for commercial clients and expects to be producing over 3,000 tons per year of finished rare earth metals by 2026.

Villalón estimates that Phoenix will be busy for a long time: at least 10 billion tons of mine tailings are created each year from new activity.

Increased demand for magnets

Some companies target recycled materials rather than coal wastes as a source of recoverable rare earths. Noveon Magnetics—formerly Urban Mining—extracts critical materials from discarded commercial magnets (from motors or medical devices, for example, or from storage drives used by data centers) or those withdrawn from the supply chain because of manufacturing defects or obsolescence. From these materials, Noveon manufactures new sintered neodymium boron magnets, critical components of generators in wind turbines and motors in electric vehicles.

According to DOE projections, US demand for these rare earth magnets is set to more than quadruple by 2050. This is partly because of improved industrial technologies, says Noveon’s chief commercial officer, Peter Afiuny. “Industrial pumps, compressors, HVAC systems … 50% of our electric consumption is being driven by those motors. If you’re talking about getting to carbon neutral, you need to upgrade those systems and make them more efficient,” he says.

There are fewer than 10 active magnet manufacturers outside China; Noveon is the only one in the US. Afiuny says it acquires all its materials domestically.

The company produces a new type of high-performance magnet, which it calls “EcoFlux,” using less material than conventional versions, says Afiuny. While it’s hard for recycled magnets to perform as well as nonrecycled products, Afiuny says that Noveon has managed the feat by combining a proprietary technology that improves the composition and properties of magnetic materials with its patented Magnet-to-Magnet technology that can recycle up to 99.5% of input materials. He adds that Noveon has multiple customers and produces at commercial scale in its Texas facility. He says the company plans to produce 10,000 tons a year within five years.

These new magnets serve the same types of customers from which the materials were collected—such as companies using motors to power consumer electronics and medical or automotive products. The result is a loop of reuse.

Can these alternative sources replace existing imports? In a recent paper published in the National Academy of Engineering’s magazine, The Bridge, DOE researchers estimate that for some critical materials such as germanium, coal ash can meet US demand for nearly 4,000 years, but for most materials, the supply will last for less than 20 years (and for nickel, for just a little more than one year).

Additional new sources are needed, says Granite: “You’re going to need many different waste materials and nontraditional sources to meet the long-term demand, because we project growing demands for many of these critical metals.”

The researchers suggest that a much broader range of waste sources could be considered, including “red mud,” created during aluminum production, and “produced waters,” which result from oil production, as well as materials sourced from the ocean floor or even outer space.

A universal policy priority

Between 2015 and 2021, the DOE awarded at least $27 million to projects related to extracting rare earth elements from both conventional and unconventional resources. In 2022 and 2023, the government announced at least $1 billion of funding available to support related work, including significant amounts from the Bipartisan Infrastructure Law. Other agencies have also announced support for companies working to help boost the nation’s supply of critical materials, signaling a renewed sense of urgency for a longtime item on the policy agenda. Rivalia, Phoenix, and Noveon have all benefited from government support, suggesting that the government is willing to place bets on companies at varied sizes and stages of progress.

These funding allocations often reveal the priorities of the issuing administration; the focus under former president Donald Trump, for example, was independence from China, while the Biden administration’s support for domestic production of rare earths seems more tied to its push for wider adoption of electric vehicles. Regardless of motivation, all parties seem aligned on the importance of rare earth elements.

“It’s something that’s broadly supported in a bipartisan way,” says Rivalia’s Stoy. “It’s something that I think is very safe from a research funding perspective. The government is interested in this and is going to be funding it for a long time.”

As the race to achieve self-sufficiency in rare earth elements and critical materials intensifies, the US is likely to further expand both the number of organizations involved and the diversity of potential sources.

Despite growing competition, Stoy says there’s room for everyone. “I want to be one player in a big ecosystem where there’s a lot of folks producing rare earths,” she says. “That is the best outcome for everyone.”

Mureji Fatunde is an academic and writer who explores how companies and consumers make decisions.

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