Social implications of AI

Ethical aspects

From UNESCO’s perspective, the most central ethical issues regarding Artificial Intelligence concern its implications in the following sectors:

Culture;
Cultural diversity;
Education;
Scientific knowledge;
Communication;
Information.

Source: https://research.aimultiple.com/ai-ethics/

How to navigate these dilemmas?

According to Cem Dilmegani, the best practices to navigate these ethical dilemmas are:

Transparency
Explainability
Inclusiveness
Alignment

Algorithmic bias

AI systems are vulnerable to biases and errors introduced by humans.
Data that is used to train AI systems often introduces biases.

Bias of AI algorithms in computer systems is categorized in:

Existing bias;
Technical bias;
Emergent bias
Experts warn that algorithmic bias is already pervasive in many industries and that almost no one is making an effort to identify or correct it.

Reflective questions

Think of how culture and education can be positively and negatively affected by AI.

Provide an answer

Give 3 examples of ethical dilemmas for the use of AI,

Self-reflection

Think of how culture and education can be positively and negatively affected by AI.

References

UNESCO, Preliminary Study on the Ethics of Artificial Intelligence, 2019
Cem Dilmegani, AI Ethics: Top 9 Ethical Dilemmas of AI and How to Navigate Them, https://research.aimultiple.com/ai-ethics/
Friedman, Batya; Nissenbaum, Helen (July 1996). "Bias in computer systems". ACM Transactions on Information Systems (TOIS). 14 (3): 330–347. doi:10.1145/230538.230561. S2CID 207195759.
Knight, Will. "Google's AI chief says forget Elon Musk's killer robots, and worry about bias in AI systems instead". MIT Technology Review. Archived from the original on 2019-07-04. Retrieved 2019-07-26.