Fashion has a misinformation problem.
You've probably heard that fashion is the second most polluting industry. It's a stat with a wide reach, found in articles, alongside other research, and on every third sustainable fashion Instagram. However, it's inaccurate. A report in 2012 listed that textile dyeing and finishing is the second biggest polluter to water behind agriculture. There are a lot of qualifiers there. Like the fact that we are referring to water pollution, not air or land pollution, and that it's the dye process, which extends beyond fashion and is not fashion as a whole. Also, that stat comes from 2012. A lot has shifted in industries since then. Despite all of that, the claim has been generalized and spread like wildfire: Fashion, as a whole, is the second biggest polluter of, apparently, anything and everything. Or at least that's what you'd assume if you just saw that "fact" in the contexts it's been shared. Without any of the criteria or original context given, the stat doesn't actually mean anything. It has no practical application because there's no clarity as to what the scope and cause of the pollution is. Always beware of a generalized statistic with no specifics or data.
But that's not the only problem. The problem is that you can find this stat in an article about the harm of fashion pretty easily. And that article will either not source it at all or link the source of the stat to another article which links to another article which links to another article. You get the picture. Even the United Nations has written "the fashion industry is widely believed to be the second most polluting industry in the world." Yet, no piece of legitimate research can back up this claim. Additionally, the statement has been debunked several times by journalists and prominent publications. I won't go into all the ways it has been falsified - you can read that yourself. However, we do need to talk about the pervasiveness of this problem.
The spread of generalized, extreme claims are all too common in the fashion industry. These claims may be based in a semblance of truth and often come from a place of wanting better for the industry, but, ultimately, they can undermine it. In order to be taken seriously in our call for a more sustainable industry, we need research-backed claims that can provide a pathway towards action. When claims are taken out of context and oversimplified, they lose their power to drive the right kind of change. While a statement that the fashion industry is the second biggest polluter can alarm people to the vast harm of the industry and prompt them to act accordingly, it doesn't provide the necessary insight of how to act. When you include the context that the specific polluter is dye in waterways, you have a direction in which to act and create meaningful change to address the source of the alarming statement.
All of this to say, we don't benefit from these vague claims. We need real research. And we need discernment and critical data consumption. As people interested in making the fashion industry better, we need to be careful how we shape the narrative with the information we share. How far this false statement was able to reach is an important lesson in how good intentions can corrode the core of our mission when it's not paired with an intentional effort to understand and responsibly share our own message. Perhaps another way to look at it is to consume and share information similarly to how we advocate for consuming clothing: slowly, thoughtfully, and backed by research. In the same way we look into the background of the brands we buy from and take time to consider the impact of adding a garment to the closet, we can apply equivalent research into the statistics we come across and a critical consideration of the impact of sharing such information.
Addressing & Negating Misinformation in Fashion
We cannot separate misinformation in fashion from the wide-spread "information disorder" that has led to the breakdown of public trust we currently exist within. To quote the Transformers Foundation's new Case Study on Misinformation, "Quality, trusted information is critical to our social order. Without it, we are moving quickly towards a world where the public may come to 'disbelieve all content,' including content coming from genuine expertise." We need accurate information in fashion in order to create trust that promotes the action needed to combat the climate crisis, fix supply chains, and interact with fashion in a healthy way.
"It is crucial for industries and society to understand the best available data and context on the environmental, social, and economic impact of different fibers and systems within fashion, so that the best practices can be developed and implemented, industries can make informed choices, and farmers and other suppliers and makers can be rewarded for and incentivized to operate using more responsible practices that drive more positive impacts." - Transformers Foundation
Without the accurate and responsible spread of data and information, we cannot effectively address the harms of the fashion industry. But where does misinformation come from? Not only does social media play a large role, but private actors (businesses, news outlets, journalists) can be motivated to participate in its spread by sensationalizing or exaggerating claims to improve readership and greenwashing or data-sharing to drive sales. Regardless of industry, in most of these cases, there is a lack of accountability to ensure data is used responsibly.
We also like to think that numbers and data are objective. However, the scientific process of developing data involves many decisions along the way that shape the data, such as methodology, what and how something is measured, what metrics are included and excluded, and so on. Then, consider how we like to draw comparatives between separate data sets (with different methodology and metrics), bring our own confirmation bias to the reading of data, and pull data out of its context. It's no wonder we are led astray in how we experience information. Data needs its context. It cannot accurately exist without the story behind how the numbers were developed. Reality is complex, nuanced, and full of caveats, and reality cannot be accurately boiled down to statistical data (especially in isolation).
“Sustainability is complex and designers and brands want something easy and simple. Unfortunately, when people create single scores or other metrics simplifying the complex science for ease of business, bad things can happen, one of which is misinformation.” - Jesse Daystar
Thus, we need to consuming data in the original context it was presented and gathered within.
How do we actually learn to approach data and research more mindfully?
Here are some tips:
As a reader:
Adopt healthy skepticism & apply critical thinking.
Understand there’s a wider context than a singular data statement.
Find the original source of the data. Footnotes are your friends.
Just because a credible institution shared it doesn’t mean it's accurate. In the same way, just because something is shared widely that doesn’t make it true.
Ask “what is the data not telling me?” Identify what context could be missing.
As a sharer:
Don’t compare data from different methodologies.
Share data within its context.
Understand your purpose in sharing the data.
Don’t manipulate your framing of the data to align with an underlying motive.
Look for recent, peer-reviewed studies.
Do your own fact-checking, check the original source before sharing what you’ve found.
Don’t oversimplify, cherry pick, or sensationalize.
Provide as much specifics and disclaimers as necessary.
Own up to mistakes. The more we talk about how we approach data, the more everyone can learn to do so better.
Be slow to repost. Social media helps decontextualized data and misinformation spread quickly.
Don’t create clickbait. Communicate context and nuance.
We can all afford to be more mindful in how we approach data, both reading and sharing it. Doing so can provide accountability to brands, journalists, and peers who use data to further their message. When we have that accountability, we can take meaningful steps towards better understanding and implementing the solutions needed. I highly recommend giving the case study a read, as it helped frame much of this piece!
October 2021.