Data Dilemmas
- Challenges and ethical issues arising from the collection, storage, use, and sharing of data in digital societies.
- Data dilemmas can arise due to:
- Data bias, reliability and integrity.
- Control, ownership and access to data.
- Data privacy, anonymity and surveillance.
Data Bias, Reliability and Integrity
Data Bias
- When data reflects prejudices or inaccuracies, leading to unfair outcomes in decision-making processes.
- Data bias can arise from:
- Biased data collection: When the data collected is not representative of the entire population.
- Biased algorithms: When the algorithms used to process the data are biased.
Facial Recognition Technology: Many facial recognition systems have been found to misidentify people of color at higher rates than white individuals. This is often due to training datasets that lack diversity.
Data Reliability and Integrity
- The consistency and accuracy of data over time.
- The trustworthiness of data, ensuring it has not been altered or tampered with.
- Data reliability and integrity can be compromised by:
- Human error: Mistakes made during data entry or processing.
- System failures: Technical issues that corrupt data.
- Malicious attacks: Cyberattacks that alter or destroy data.
