In a new paper being presented at the Association for Computing Machinery’s Fairness, Accountability, and Transparency conference next week, researchers including PhD students Nicholas Vincent and Hanlin Li propose three ways the public can exploit this to their advantage:
- Data strikes, inspired by the idea of labor strikes, which involve withholding or deleting your data so a tech firm cannot use it—leaving a platform or installing privacy tools, for instance.
- Data poisoning, which involves contributing meaningless or harmful data. AdNauseam, for example, is a browser extension that clicks on every single ad served to you, thus confusing Google’s ad-targeting algorithms.
- Conscious data contribution, which involves giving meaningful data to the competitor of a platform you want to protest, such as by uploading your Facebook photos to Tumblr instead.
People already use many of these tactics to protect their own privacy. If you’ve ever used an ad blocker or another browser extension that modifies your search results to exclude certain websites, you’ve engaged in data striking and reclaimed some agency over the use of your data. But as Hill found, sporadic individual actions like these don’t do much to get tech giants to change their behaviors.
What if millions of people were to coordinate to poison a tech giant’s data well, though? That might just give them some leverage to assert their demands.
There may have already been a few examples of this. In January, millions of users deleted their WhatsApp accounts and moved to competitors like Signal and Telegram after Facebook announced that it would begin sharing WhatsApp data with the rest of the company. The exodus caused Facebook to delay its policy changes.
Just this week, Google also announced that it would stop tracking individuals across the web and targeting ads at them. While it’s unclear whether this is a real change or just a rebranding, says Vincent, it’s possible that the increased use of tools like AdNauseam contributed to that decision by degrading the effectiveness of the company’s algorithms. (Of course, it’s ultimately hard to tell. “The only person who really knows how effectively a data leverage movement impacted a system is the tech company,” he says.)
Vincent and Li think these campaigns can complement strategies such as policy advocacy and worker organizing in the movement to resist Big Tech.
“It’s exciting to see this kind of work,” says Ali Alkhatib, a research fellow at the University of San Francisco’s Center for Applied Data Ethics, who was not involved in the research. “It was really interesting to see them thinking about the collective or holistic view: we can mess with the well and make demands with that threat, because it is our data and it all goes into this well together.”
Climate tech is back—and this time, it can’t afford to fail
Boston Metal’s strategy is to try to make the transition as digestible as possible for steelmakers. “We won’t own and operate steel plants,” says Adam Rauwerdink, who heads business development at the company. Instead, it plans to license the technology for electrochemical units that are designed to be a simple drop-in replacement for blast furnaces; the liquid iron that flows out of the electrochemical cells can be handled just as if it were coming out of a blast furnace, with the same equipment.
Working with industrial investors including ArcelorMittal, says Rauwerdink, allows the startup to learn “how to integrate our technology into their plants—how to handle the raw materials coming in, the metal products coming out of our systems, and how to integrate downstream into their established processes.”
The startup’s headquarters in a business park about 15 miles outside Boston is far from any steel manufacturing, but these days it’s drawing frequent visitors from the industry. There, the startup’s pilot-scale electrochemical unit, the size of a large furnace, is intentionally designed to be familiar to those potential customers. If you ignore the hordes of electrical cables running in and out of it, and the boxes of electric equipment surrounding it, it’s easy to forget that the unit is not just another part of the standard steelmaking process. And that’s exactly what Boston Metal is hoping for.
The company expects to have an industrial-scale unit ready for use by 2025 or 2026. The deadline is key, because Boston Metal is counting on commitments that many large steelmakers have made to reach zero carbon emissions by 2050. Given that the life of an average blast furnace is around 20 years, that means having the technology ready to license before 2030, as steelmakers plan their long-term capital expenditures. But even now, says Rauwerdink, demand is growing for green steel, especially in Europe, where it’s selling for a few hundred dollars a metric ton more than the conventional product.
It’s that kind of blossoming market for clean technologies that many of today’s startups are depending on. The recent corporate commitments to decarbonize, and the IRA and other federal spending initiatives, are creating significant demand in markets “that previously didn’t exist,” says Michael Kearney, a partner at Engine Ventures.
One wild card, however, will be just how aggressively and faithfully corporations pursue ways to transform their core businesses and to meet their publicly stated goals. Funding a small pilot-scale project, says Kearney, “looks more like greenwashing if you have no intention of scaling those projects.” Watching which companies move from pilot plants to full-scale commercial facilities will tell you “who’s really serious,” he says. Putting aside the fears of greenwashing, Kearney says it’s essential to engage these large corporations in the transition to cleaner technologies.
Susan Schofer, a partner at the venture firm SOSV, has some advice for those VCs and startups reluctant to work with existing companies in traditionally heavily polluting industries: Get over it. “We need to partner with them. These incumbents have important knowledge that we all need to get in order to effect change. So there needs to be healthy respect on both sides,” she says. Too often, she says, there is “an attitude that we don’t want to do that because it’s helping an incumbent industry.” But the reality, she says, is that finding ways for such industries to save energy or use cleaner technologies “can make the biggest difference in the near term.”
It’s tempting to dismiss the history of cleantech 1.0. It was more than a decade ago, and there’s a new generation of startups and investors. Far more money is around today, along with a broader range of financing options. Surely we’re savvier these days.
Making an image with generative AI uses as much energy as charging your phone
“If you’re doing a specific application, like searching through email … do you really need these big models that are capable of anything? I would say no,” Luccioni says.
The energy consumption associated with using AI tools has been a missing piece in understanding their true carbon footprint, says Jesse Dodge, a research scientist at the Allen Institute for AI, who was not part of the study.
Comparing the carbon emissions from newer, larger generative models and older AI models is also important, Dodge adds. “It highlights this idea that the new wave of AI systems are much more carbon intensive than what we had even two or five years ago,” he says.
Google once estimated that an average online search used 0.3 watt-hours of electricity, equivalent to driving 0.0003 miles in a car. Today, that number is likely much higher, because Google has integrated generative AI models into its search, says Vijay Gadepally, a research scientist at the MIT Lincoln lab, who did not participate in the research.
Not only did the researchers find emissions for each task to be much higher than they expected, but they discovered that the day-to-day emissions associated with using AI far exceeded the emissions from training large models. Luccioni tested different versions of Hugging Face’s multilingual AI model BLOOM to see how many uses would be needed to overtake training costs. It took over 590 million uses to reach the carbon cost of training its biggest model. For very popular models, such as ChatGPT, it could take just a couple of weeks for such a model’s usage emissions to exceed its training emissions, Luccioni says.
This is because large AI models get trained just once, but then they can be used billions of times. According to some estimates, popular models such as ChatGPT have up to 10 million users a day, many of whom prompt the model more than once.
Studies like these make the energy consumption and emissions related to AI more tangible and help raise awareness that there is a carbon footprint associated with using AI, says Gadepally, adding, “I would love it if this became something that consumers started to ask about.”
Dodge says he hopes studies like this will help us to hold companies more accountable about their energy usage and emissions.
“The responsibility here lies with a company that is creating the models and is earning a profit off of them,” he says.
The first CRISPR cure might kickstart the next big patent battle
And really, what’s the point of such a hard-won triumph unless it’s to enforce your rights? “Honestly, this train has been coming down the track since at least 2014, if not earlier. We’re at the collision point. I struggle to imagine there’s going to be a diversion,” says Sherkow. “Brace for impact.”
The Broad Institute didn’t answer any of my questions, and a spokesperson for MIT didn’t even reply to my email. That’s not a surprise. Private universities can be exceedingly obtuse when it comes to acknowledging their commercial activities. They are supposed to be centers of free inquiry and humanitarian intentions, so if employees get rich from biotechnology—and they do—they try to do it discreetly.
There are also strong reasons not to sue. Suing could make a nonprofit like the Broad Institute look bad. Really bad. That’s because it could get in the way of cures.
“It seems unlikely and undesirable, [as] legal challenges at this late date would delay saving patients,” says George Church, a Harvard professor and one of the original scientific founders of Editas, though he’s no longer closely involved with the company.
If a patent infringement lawsuit does get filed, it will happen sometime after Vertex notifies regulators it’s starting to sell the treatment. “That’s the starting gun,” says Sherkow. “There are no hypothetical lawsuits in the patent system, so one must wait until it’s sufficiently clear that an act of infringement is about to occur.”
How much money is at stake? It remains unclear what the demand for the Vertex treatment will be, but it could eventually prove a blockbuster. There are about 20,000 people with severe sickle-cell in the US who might benefit. And assuming a price of $3 million (my educated guess), that’s a total potential market of around $60 billion. A patent holder could potentially demand 10% of the take, or more.
Vertex can certainly defend itself. It’s a big, rich company, and through its partnership with the Swiss firm CRISPR Therapeutics, a biotech co-founded by Charpentier, Vertex has access to the competing set of intellectual-property claims—including those of UC Berkeley, which (though bested by Broad in the US) hold force in Europe and could be used to throw up a thicket of counterarguments.
Vertex could also choose to pay royalties. To do that, it would have to approach Editas, the biotech cofounded by Zhang and Church in Cambridge, Massachusetts, which previously bought exclusive rights to the Broad patents on CRISPR in the arena of human treatments, including sickle-cell therapies.