Page 428 - AI_Ver_3.0_class_11
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Ready 8
Activity: Role Play [CBSE Handbook]
1. Share the following examples of biased AI systems and their potential consequences and ask students to do a role play
to present each scenario:
Social Media Algorithms:
● Example: Algorithms on social media platforms often prioritise content based on user engagement metrics,
leading to echo chambers and reinforcing existing biases and opinions.
● Consequences: Biased social media algorithms can contribute to polarisation and the spread of misinformation,
undermining democratic discourse and social cohesion.
Loan Approval Systems:
● Example: Automated loan approval systems used by banks may use biased criteria that favour certain demographic
groups over others, leading to disparities in access to credit.
● Consequences: Biased loan approval algorithms can perpetuate financial exclusion and deepen economic
inequality, particularly for marginalised communities who may already face barriers to financial resources.
Criminal Sentencing Algorithms:
● Example: Some jurisdictions use algorithms to assist judges in determining sentencing decisions based on factors
such as criminal history and offense severity. However, these algorithms have been found to exhibit racial biases.
● Consequences: Biased sentencing algorithms may result in harsher punishments for individuals from minority
groups, contributing to mass incarceration and perpetuating systemic injustice within the criminal justice system.
School Admissions Algorithms:
● Example: Educational institutions may use algorithms to assist in the admissions process, considering factors like
academic performance and extracurricular activities. However, these algorithms may unintentionally disadvantage
students from underprivileged backgrounds.
● Consequences: Biased admissions algorithms can limit educational opportunities for disadvantaged students,
widening the achievement gap and hindering social mobility.
426 Touchpad Artificial Intelligence (Ver. 3.0)-XI

