Search neutrality is the idea that a search engine does not limit or influence a person’s ability to access information on the internet. The search engine market is very one sided with just a couple companies controlling the entire market.

“Search neutrality is a principle that search engines should have no editorial policies other than that their results be comprehensive, impartial and based solely on relevance. This means that when a user queries a search engine, the engine should return the most relevant results found in the provider’s domain (those sites which the engine has knowledge of), without manipulating the order of the results (except to rank them by relevance), excluding results, or in any other way manipulating the results to a certain bias.” -Wikipedia

According to the Stanford Encyclopedia of Philosophy:

Search-engine technology is not neutral, but instead has embedded features in its design that favor some values over others. Major search engines systematically favor some sites (and some kind of sites) over others in the lists of results they return in response to user search queries. Search algorithms do not use objective criteria in generating their lists of results for search queries.

Search engines may have completely positive intentions, but if their algorithms fail to give people objective and neutral results, they are failing. 93 percent of online experiences begin with a search engine. If the majority of people’s browsing is determined by a search engine, the search engines have a big responsibility to deliver a complete and accurate representation of information. Search Encrypt strives to remain a neutral and unbiased source of information on the internet.

Big Search Engines Penalized For Search Bias

Back in February 2018, India’s competition commission fined one of the major search engines approximately $21.1 million for abusing its power in the search market. The European Commission also imposed a record 2.4 billion euro ($2.7 billion) fine on the company for favoring its shopping service and demoting rival offerings.

Adam and Shivaun Raff, the British couple behind the price comparison website Foundem, played a vital role in bringing the search bias issues to light.

If a search engine manipulates its search results to favor its most profitable websites, there isn’t much other websites can do to change the very opaque system by which big search engines do this.

This is the problem that the Raffs had, and when they tried to contact the search engine giants for feedback, or an appeal process, they weren’t given much to work with. Online shopping services rely on traffic (which comes mostly form search engines) to be successful. However, if a major search engine demotes its site to the second or third page of results, its traffic (and profit) numbers will suffer in a major way.

So why is this a problem?

The biggest issue is that online shopping networks have to pay for their ads on search engines. The search engines though can put their results right next to the ads of their competitors, even though they don’t have to pay for the spots. By manipulating the algorithms that decide which shopping links to show, the search engine can lead people to click on its own ads even though they don’t have to pay for the ads.

Consider then that a big search engine has a particular political ideology they want to promote. All they have to do is change the search algorithms to influence public opinion to support their own interests. Because we don’t use your data to determine which search results you see, we can’t serve targeted ads. So our ads will be based on your search terms and nothing else!

Search Engines Aren’t Perfect

Safiya Umoja Noble, a USC Annenberg communications professor says that the values of the internet reflect the people who made it, mostly white, Western men. She explains that minorities and women aren’t fairly represented on the internet.

This is also an issue with the search engines that people use to find information on the internet. One counterargument though, is that the search engines themselves aren’t the problem. If the information they are crawling is biased, that same bias will be introduced into their search results.

“When we start getting into more complicated concepts around identity, around knowledge, this is where search engines start to fail us. This wouldn’t be so much of a problem except that the public really relies upon search engines to give them what they think will be the truth, or something vetted, or something that’s credible” Noble said.

Search engines and social media companies alike are discussing artificial intelligence and how they can apply it to clean up content on their sites. Unfortunately, if the AI used to sort and filter content is based on existing information and algorithms, the existing biases will be reinforced, not fixed. AI is a valuable tool, but it won’t help search engines or sites like Facebook deliver more neutral content.

Advantages of Search Neutrality

Search results would be more relevant to users and not biased towards sites with more ads

Neutral search results emphasize higher quality content over paid ranking

Allows for manipulation of search results by an objective algorithm, rather than allowing ranking on an individual basis.

Search neutrality minimizes the effects of cultural or ideological “filter bubbles“.

Disadvantages of Search Neutrality

Search bias allows “personalized” search results, people want this bias because it delivers smarter, more predictive results. Search neutrality minimizes this bias and “personalization”.

Regulating search engines and their results could limit a search engine’s ability to adjust rankings based on their own metrics.

Search Engines Without Tracking Minimize Search Bias

Search bias is introduced in two ways. One is from the search engine’s algorithm side, if it determines that a website is generally clicked on more than others. The other way happens when a search engine monitors a person’s internet behavior and tailors the results based on their past searches and resulting clicks.

Private search engines that don’t track your searches can’t customize your search results. If you are seeking unbiased information, this is a good thing. The convenience of personalized results is countered by the “filter bubble” effect this creates.

With private search engines, a conservative person who often reads Fox News could search for something and they would get the same results as a liberal person who reads the New York times. This can’t be said for big search engines that track their users’ searches. The conservative person is likely to get more conservative news sources in their search results than the liberal person who will likely get more left-leaning websites.

Can We Solve Search Bias?

Bias in search engines is a big issue, and it’s likely a big contributor to the political polarization happening in the United States. The same issue is found with algorithmic social media sites like Facebook. The first step to solving the issue is informing people that their main sources of information may not be perfect.

Being critical of information on the internet is a vital skill for navigating the modern information landscape. We need to be more skeptical of information we find online, and having higher standards for the products we use to find that information.

Search Encrypt: The Unbiased Search Engine

Search Encrypt doesn’t track your search history in any user identifiable way. We don’t use information about what you’ve searched for in the past, or what you like to look at online to give you “customized” search results. Any search engine that says they can improve the quality of your search results by tailoring them to you is giving you biased results.

If someone regularly visits news websites with either more conservative or more liberal views, that will not impact the search results they see on Search Encrypt. Our results are generally the exact same regardless of what a certain person has searched for or looked at in the past. This consistent and non-user specific functionality removes the possibility for search bias and filter bubbles.