Almost everyone thinks they know how to use Google and usually get the answer they want. Many will intuitively know that the query “milk good for you” leads to different results than “milk bad for you”. The same goes for queries for “climate change” versus “climate hoax,” or for “valid 2020 US election” versus “stop theft.”
Since search engines are more of a “wish list” than an authoritative source, they can help spread misinformation and disinformation that can be detrimental to democracy or society. They are not neutral information brokers.
Instead, search engines return a list of results they deem most relevant to a specific query. The underlying algorithms make a decision on the relevance and visibility of a specific query to a specific location and sometimes to a specific user.
Search engines are an integral but often invisible part of how people navigate the modern world. In this function, they also shape the understanding of reality and can thus harm the environment. In a recently published paper, we argue that the assumptions search engines make about what we’re looking for can lead people to emit more carbon than they otherwise would.
The environmental damage of algorithmic curation
Let’s take the example of the query “summer clothes”. You will receive a list of online or nearby stores that sell summer clothes, along with photos of models showing the clothes for sale. This is exactly what we expect.
But other possible interpretations of the query “summer clothes” are possible. Maybe you want to know what summer clothes were like in a particular historical period. Maybe you want to see which colors in your wardrobe are the best to wear this year. Or maybe you want to buy summer clothes, but only from certified organic or fair trade fabrics, or from a thrift store.
You can also enter the names of two major cities, such as “Berlin Stockholm”. Google will show you results that are mostly about air travel, not, for example, a comparison of the livability of those cities. Google will highlight various flight options in its built-in flight comparison, while finding train tickets requires you to scroll further.
These results are in no way predefined but rather the result of algorithmic curation. Even without personalization, search result listings are uniquely created from specific content optimized for specific searches, search engine algorithms, and a user’s query and location.
You can try it yourself with these cities and others. But note that using quotes, city order, or local vs. English spelling can make a difference, as many companies try to optimize for specific searches.
Any reader familiar with Google search knows that the alternative results we have described require further queries. Such queries should explicitly state that the search is for something other than buying clothes or flights. For example by asking “colors of summer clothes” or “Berlin Stockholm livable”.
In any case, the default options that the algorithms select and arrange shape what we think is the default. If we are not careful and reflective of our own goals when researching, it will also affect at least some people’s actions. And these actions have very real environmental implications.
Environmental damage as algorithmic damage
We suggest calling these environmental implications “algorithmically embedded emissions”. By this we mean the emissions potentially contained in the content that algorithmic information systems – such as search engines or a Facebook or TikTok feed – offer as a default option.
Our work so far is conceptual, but we hope to develop a way to quantify the concept in the future. So far, we can observe that search results tend to suggest high-carbon practices.
And it can be noted that related companies like flight comparison services or fast-fashion brands can also optimize their websites for better search engine rankings. These companies tend to have larger budgets than their more sustainable alternatives (a small brand of organic or repurposed summer clothing, for example).
In recent years, researchers have highlighted the potential harm that algorithmic decision-making can cause to people, for example by reproducing racial or gender biases. This is often called algorithmic prejudice.
The concept of algorithmically embodied emissions asks us to go even deeper into algorithmic damage. This shows that algorithmic decision making has real impacts on people and the planet.
It is also an example of how algorithmic decision making has higher order effects beyond the immediate harm to individuals. In other words: it matters how algorithms work and shape our actions. As the climate crisis gathers pace, we have only just begun to question how algorithms are shaping the way we think and act towards the environment.
In response to this article, a Google spokesperson said:
On Google Search, our goal is to provide people with timely, relevant, and helpful information to make choosing sustainability an easier choice. We fundamentally design our search ranking systems to surface reliable, high-quality information on topics such as climate change. To complement these efforts, we’ve also developed a number of features to give people useful context to make informed decisions about sustainability, including helping people quickly access information about the environmental impact of goods and services. they see in the results. We work with thousands of partners across multiple sectors – from cities and governments to businesses and nonprofits – to advance sustainability and climate progress.
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