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The Rosenthal Effect – Why Algorithms get it Wrong

by | Feb 13, 2024

The Rosenthal effect, also known as the Pygmalion effect, operates on the powerful interplay between expectations and performance. Imagine a classroom where a teacher, influenced by preconceived notions or expectations, believes that certain students are exceptionally bright or talented.

This belief subtly alters the teacher’s behavior – they may provide more attention, encouragement, and challenging opportunities to those students. In response to this positive reinforcement, the students, consciously or unconsciously, begin to embody the expectations placed upon them. They may feel a sense of validation and confidence, fostering a positive emotional environment.

Conversely, for students who are not singled out with high expectations, the lack of special attention might result in lower self-esteem and reduced motivation. This dynamic can create a self-fulfilling prophecy, where students live up to or fall short of the expectations placed upon them.

Emotionally, this process can evoke feelings of empowerment, confidence, and success for those positively labelled, while others may experience frustration, self-doubt, or a sense of being overlooked. The Rosenthal effect underscores the profound impact that beliefs and expectations can have on shaping individuals’ experiences and outcomes.

 

Ranking Easy
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In the old days of the Internet ranking was easy for everyone.

Ranking Hard
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Today competition is fierce and makes it expensive to rank in search engines.

The Rosenthal Effect: Unraveling the Impact on Google and Amazon Algorithms

The foundation for any big tech algorithm today is scaringly simple: The algorithm is a money machine!

But how do we construct the best money-making algorithm possible? Base it on competition!

Now, basing an algorithm on competition to make money has never been scientifically proven to be the best method. It is simply a subtle assumption most of us make. According to Ken Wilber this is based on the general stage of consciousness society has developed, meaning it hasn’t always been like this and it changes over time.

https://www.themasculineman.com/integral-relationships/

 

Using competition will always benefit websites backed by a lot of capital and that is exactly what we see on the net today. Small sites don’t have a chinamans chance. Unless they use unrealistic long-tail keywords.

In short: Basing an algorithm on competition makes it biased towards – competition!

 

The Rosenthal Effect, also known as the Pygmalion Effect, highlights the profound influence of expectations on performance. Originating in the realm of education, this psychological phenomenon has implications far beyond the classroom. In the digital age, as algorithms play an increasingly pivotal role in shaping our online experiences, it is essential to explore how the Rosenthal Effect might be influencing technology giants like Google and Amazon.

 

Algorithmic Bias and Preconceived Notions:
Google and Amazon, as tech leaders, rely heavily on algorithms to curate content, recommend products, and personalize user experiences. However, these algorithms are not immune to biases. The Rosenthal Effect suggests that preconceived notions and expectations can shape outcomes. In the case of algorithms, the biases of their creators might inadvertently be embedded into the code, influencing the way information is presented or products are recommended.

 

Implicit Biases in Search Results:
Google, as the primary search engine for a vast majority, wields considerable influence over the information users access. The Rosenthal Effect implies that if there are implicit biases within the development team or the dataset used for training, these biases could manifest in search results. Users might be exposed to information that aligns with certain expectations, potentially perpetuating stereotypes or limiting exposure to diverse perspectives.

 

Amazon’s Product Recommendations and Customer Profiling:
Amazon’s recommendation engine is a cornerstone of its business model. However, the Rosenthal Effect warns that biased expectations may impact these recommendations. If the algorithms are trained on historical data that reflects biases in purchasing patterns, customers might be confined to a narrow set of options, reinforcing existing preferences and limiting exposure to alternative choices.

 

Effects on Small Businesses and Content Creators:
The Rosenthal Effect, when applied to algorithms, could inadvertently disadvantage smaller businesses or content creators. If algorithms favor established entities based on preconceived notions of success, it may be challenging for newcomers to gain visibility. This perpetuates existing power imbalances and limits the diversity of voices in online spaces.

 

Ethical Considerations and Algorithmic Transparency:
Understanding the Rosenthal Effect in the context of Google and Amazon algorithms emphasizes the need for transparency and ethical considerations in algorithmic design. Awareness of biases, continuous monitoring, and adjustments are crucial to ensuring fair and equitable outcomes.

 

In conclusion, the Rosenthal Effect serves as a lens through which we can examine the potential shortcomings of Google and Amazon algorithms. Acknowledging the impact of expectations on performance highlights the importance of mitigating biases and ensuring fairness in algorithmic decision-making. As society becomes increasingly reliant on digital platforms, it is imperative that tech giants address these issues to create a more inclusive and equitable online environment.

 

Research:

The Pygmalion or Rosenthal effect research.

Lenore Jacobson

Pygmalion in the classroom

 

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