Search engines like Google have a massive influence on what information users get to see, and on what search results users select. This leads to search engines having a significant impact on what information we as a society acquire. It has been often lamented that search engines are biased. I, however, argue that we have only scratched the surface because search engine bias is a multifaceted concept and the discussion usually solely focuses on some aspects. Search engine bias can be classified into four different areas. Firstly, there are biases on the side of the search engine, e.g., in their ranking functions. Secondly, there are biases through external influencing of search engine results, predominantly through “search engine optimization”. Thirdly, biases occur on the side of the user (e.g., position bias, confirmation bias, visual attraction bias). And fourthly, there are self-interests of search engine providers which influence the search results. Further to giving an overview of the topic, I will show how search engine providers (and regulators) can take steps towards making search fair. Whereas a bias-free search engine is impossible, a fair search is. Here, I will not only focus on the big web search engines but also on how developers and product owners can make their search systems fair. Or, to put it another way, I will show what can we learn from these “worst practices” in web search when designing our own systems.