Estimated reading time: 10 minutes
This article was adapted from a transcript of our fireside chat with Kiana. Join our community to participate live in biweekly conversations with experts, activists, policymakers, and more!
Imagine if data can be used as a force of good, especially when taking action for our planet and our communities. As an environmentalist and data scientist, Kiana Kazemi, CEO of Beaker and co-founder of Intersectional Environmentalist, is democratizing access to environmental justice resources and solutions. In this fireside chat, Kiana explores how her work is empowering people to consume responsibly with the help of sustainability and ethics data.
Here’s what we’ll cover:
Reflecting on her exploration in the intersections of data, ethics, and justice within her work, Kiana highlights how data science and engineering are powerful tools for scaling transparency and action.
What inspired you to dive into your current work as a data scientist in the environmental field?
I’ve been an environmentalist since I was 8 years old. I’ve always been really passionate about conservation and environmental justice. Many communities don’t have equal access to nature or natural resources, and I wanted to understand why. I wanted to learn more about how climate, the environment, and people intersect and interact with one another.
Going into college at UC Berkeley, I initially wanted to study environmental science or policy. After taking different classes on campus, I realized I could learn a lot of this information outside of the classroom. I wanted to learn tangible skills that I felt I couldn’t learn on my own. This inspired me to take a data science class in my freshman year.
It was very difficult, but really fascinating. It was a new set of skills I didn’t have access to before starting college. I wondered 1) why no one is using these skills to address climate issues and 2) why it was a niche topic within the world of technology and software engineering. As I studied more, I began to use my data science background to create tools and resources that focused on addressing environmental and social justice issues.
Months later, I met some friends online during my sophomore year of college. During COVID, we started Intersectional Environmentalist, not thinking much of it, but it eventually became a really huge nonprofit. We had the opportunity to work with people from the White House, EPA, and the Department of Energy to raise awareness of environmental justice. We’ve also worked with clients such as Nike, Starbucks, and other really big brands ever since its launch. Though, I see this experience as a side quest in my journey and career.
Over the last couple of months, I returned back to my main quest that I’ve envisioned for the longest time, which is using software for social and environmental issues. This inspired me to launch Beaker with my partner, Farzaan, who studies AI at Stanford.
How can data transparency and access be leveraged to raise more awareness of justice-focused issues?
It’s unfortunately a niche within the world of technology, but in reality, technology has huge social and environmental implications. As engineers, we’re thinking of our technologies and innovations as existing within a vacuum or a bubble. We tend to forget that they interact with people.
If we’re creating a product, we need to remember that people are the end user. It’s going to have impacts on our society and our environment regardless. Unfortunately, a lot of engineering students never learn about ethics and social justice issues. They go out into the world and create innovations without realizing the human impacts of their work.
When I started to learn more about data ethics, I read a couple of different books and essays. One of my favorites is a book called Algorithms of Oppression, which looks at different algorithms and its embedded social biases. I learned that no technology is subjective. If a human being is creating a piece of technology, their personal biases are going to be embedded in that technology. For example, policing algorithms tend to have a lot of racial and gender bias, which has impactful consequences for a ton of people. Another example is our social media algorithms oftentimes have a really harsh impact on young people that are trying to understand their role in society.
Overall, we see our algorithms have a huge impact on people and their environment, and it’s really important that we’re super aware of the potential consequences.
How does Beaker use data to bridge the gap between education and action? Can you walk us through an example?
There’s an opportunity to leverage data to raise awareness and nudge action towards sustainability and environmental justice. For example, as consumers, it’s often difficult to measure the ethical and environmental impacts of our purchases, especially through the brands we consume. Finding this information can be time-consuming and overwhelming.
This is why we launched Beaker's Fashion Directory, a place where you can see how brands are operating environmentally and ethically. We have around 3,000 brands that are categorized and organized by ratings (ie., Beaker Score).
There’s other existing tools that give you ratings, but they don’t actually tell you their sources or how those ratings are measured. With the power of technology, we’re able to have complete transparency and a standardized system that shows you exactly how we’re rating a brand. You’re able to trace any information on our directory back to its original source.
You can look through all sorts of brands, especially ones that have limited information published on their social and environmental impacts. For example, brands like Patagonia are known for being transparent, but other brands such as Nike or Adidas, try to hide all of this information. With a simple click in our directory, you can really understand the full story behind these brands.
With Beaker, you’re able to look at these brands holistically. There are different criteria that a brand meets or doesn’t meet. For example, Patagonia is OCS (Organic Cotton Standard) certified, which is a type of cotton certification. Patagonia also audits their greenhouse gas emissions and has an animal welfare policy. However, they are still using animal products, so that might be important for someone to keep in mind. However, their ethics score is lacking because they don't audit their primary and secondary supply chain. On the other hand, they’re Fair Trade Certified.
You’ll also see each brand has a confidence rating, which implies that the information presented is based on what is accessible to us. For example, Patagonia tends to be a transparent company, so they have a high confidence rating. If you go to a different brand like Nike, you might see a lower confidence rating. This means we’re not super confident largely due to the brand not being transparent about their data and environmental policies.
It helps to take this information with a grain of salt and understand how reliable the information is being presented by the brand. Though, having this information accessible can help inform you what actions you need to take to consume consciously.
How do you acquire the data from each brand?
We wrote a scraping system and also used an AI system that helps us sort all of the data. We wrote an algorithm that goes into each brand’s website to look for and scrape the necessary information. Then, we taught an AI system that is run by our software to sort all of the information and organize it together. We also ensure there’s a human component. We audit every piece of information and go through each brand to make sure that the information collected aligns with other published information.
How do you determine the weights of each component?
Each component’s weight is determined by its relative importance with respect to a given axis (based on expert opinion or scientific research. A lot of our weights have been determined by its overall impact on the environment and on people. We work with sustainable fashion experts in the field, who help us understand how each component should be weighted. The weights are directly informed by data about correlation & causation for better performance on environmental and ethical footprints.
Each component either lies between the themes of transparency and action. How do you approach each component through those lenses?
Transparency is a really important indicator of your practices in the fashion industry because brands have to disclose whenever they measure their carbon emissions and their environmental impact.
We weigh transparency with actions. If you look at our website, a lot of actions tend to be scored higher and have slightly higher ratings. A transparency score is useful to know if a brand is disclosing any information. That’s also why we have the confidence rating, which helps consumers understand whether that brand is transparent about all of their practices.
How do you evaluate companies who may not be able to afford certifications? Are they at risk for a lower rating?
We will still give them a rating even if they don’t have a certification. There isn’t a set of criteria that every brand has to meet to get a score of 10 (the highest score). Every brand starts off at a 5. If the brand has good policies in place, your rating goes up from there (vice versa).
We still take other information into account and give points to brands without certifications For example, a brand might not be OCS certified, but they might have a data source published that indicates their products are organic. Another example is that a brand who might not have Fair Trade Certification still shows audits on their website of their primary and secondary supply chains being paid fairly.
We’re aware of this issue because there are other rating systems that try to score brands out of 100 and they only give you points if you meet all 100 criteria points. This is really difficult for any brand to do, especially for small brands who cannot afford expensive and time-consuming certifications.
We try to give flexibility to a brand to show us that they’re implementing sustainable practices and taking them seriously, and giving a score based on what information is available.
Reflecting on your experience building Beaker, how can we integrate ethics and social justice into technology and ensure that people who are already working in this space are aware of the impacts of their work?
It’s important to bring the topics outside of the niche and make it mainstream as a whole. For example, a class I took at UC Berkeley that focused on the societal and environmental impacts of technology. This class should be a requirement for every single software engineer, data scientist, and anyone who is innovating and building projects for humans. We all need to learn about the ethics and consequences of our work. At a college and university level, we need to embed these types of classes into our curriculums and adopt an interdisciplinary form of education.
We must also talk about representation in every field. Our workplaces can do a better job at encouraging employees to think about the ethical aspects of their work. We need engineers that come from different perspectives and backgrounds because our biases are embedded in our innovations. If we have a diverse range of people with different perspectives working on a new technology, we have a much more diverse technology that addresses the needs of different people and the potential impacts on different communities.
To get data-driven ratings and recommendations on your favorite brands, support Beaker’s work by checking out their Fashion Directory and bite-sized resources on their Instagram!
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