PSY205 (Social Psychology): End-of-Course Assessment

Module / Subject / School

PSY205: Social Psychology
Singapore University of Social Sciences

Requirements

Question 1
(Word Count: including in-text citations and excluding your reference list, shall fall between 1,800 to 2,000 words.)

First, examine the following excerpt from Hofmann et al.’s (2024) abstract to understand how their findings apply to the phenomena of prejudice:

Hundreds of millions of people now interact with language models, with uses ranging from serving as a writing aid to informing hiring decisions … Here, we demonstrate that language models embody covert racism in the form of dialect prejudice: we extend research showing that Americans hold raciolinguistic stereotypes about speakers of African American English and find that language models have the same prejudice, exhibiting covert stereotypes that are more negative than any human stereotypes about African Americans ever experimentally recorded … Language models are more likely to suggest that speakers of African American English be assigned less prestigious jobs, be convicted of crimes, and be sentenced to death.
Finally, we show that existing methods for alleviating racial bias in language models such as human feedback training do not mitigate the dialect prejudice, but can exacerbate the discrepancy between covert and overt stereotypes, by teaching language models to superficially conceal the racism that they maintain on a deeper level.

Extracted from Hofmann, V., Kalluri, P. R., Jurafsky, D., & King. S. (2024). Dialect prejudice predicts AI decisions about people’s character, employability, and criminality. Computation and Language. https://doi.org/10.48550/arXiv.2403.00742.

Develop your understanding of social psychology in the digital world as you apply theories of prejudice to analyse the extent to which biases of language technology, as uncovered by Hofmann et al. (2024), are relevant to the local Singapore context.

What We Score

Writer’s Comment

This assignment tests your ability to apply social psychology theory to real-world digital phenomena.

Common challenges include:

Shallow theory application: Students often fail to fully connect social psychology concepts like prejudice, stereotyping, or social categorisation to AI biases.
Limited local context analysis: Many submissions focus solely on global or US-centric examples, neglecting Singapore’s multicultural and multilingual landscape.
Vague implications: Recommendations and reflections may lack specificity regarding digital ethics, employment, or social justice.

Strong submissions clearly:

Apply multiple theories of prejudice: e.g., social identity theory, stereotype activation, and implicit bias frameworks.
Assess local relevance: Analyse how dialect, ethnicity, and language use in Singapore might intersect with AI biases.
Draw actionable insights: Discuss measures for mitigating bias in AI applications and public awareness campaigns.

General Tips to Improve Your Score

Critically analyse Hofmann et al. (2024) and connect findings to theory.
Incorporate Singaporean context in your examples.
Link all arguments to social psychology concepts of prejudice.
Structure your essay with clear subheadings and coherent argumentation.

Why Students Work With Our Experts for This Assignment

Expert understanding of social psychology: Guidance on connecting theory with real-world technology.
Digital bias analysis support: Help in translating Hofmann et al.’s findings to Singapore’s context.
Structured essay planning: Assistance in organising content to meet word count and clarity requirements.
Top-quality submissions: Designed to achieve scores consistently above 75%.

If you need help with this Social Psychology assignment, our team knows exactly how to handle this kind of thing.