Automated Decision-Making
Computer Science: OCR A Level, topic 5.2.10
Automated Decision-Making
Automated decision-making, driven by algorithms, plays a significant role in various aspects of modern life. It raises ethical concerns about fairness, bias, and accountability.
Tailoring experiences algorithms
- Automated decision-making algorithms are widely used to tailor user experiences.
- For example: determining content shown on social media feeds based on past interactions and interests.
- While personalisation can enhance user engagement, it also raises concerns.
- Users are only exposed to content that reinforces their beliefs, potentially leading to a more close-minded society.
Algorithm based assessment
- Algorithms may assess the likelihood of a criminal reoffending or determine a candidate's eligibility for a loan.
- Algorithms often do such assessments without considering context-specific factors.
- Such factors would be included in human judgment.
- Algorithm-based assessment leads to fears of unfair or biased outcomes.
Streamlining hiring
- Despite ethical concerns, the use of automated decision-making has led to increased efficiency in many sectors.
- For example: in employment, algorithms can streamline hiring by pre-screening applicants based on desired traits.
- Streamlining hiring allows companies to fill positions more swiftly.
Algorithmic trading
- In the financial sector, algorithmic trading has become dominant.
- Algorithmic trading allows for rapid decision-making based on historical data to predict market movements.
Fairness
- To ensure fairness, these algorithms must be transparent, rigorously tested, and supplemented with human oversight to prevent biased or unethical decisions.
Test yourself on Automated Decision-Making
What is algorithmic trading based on?