From UPSC perspective, the following things are important :
Prelims level : Nothing much
Mains level : Ethics of AI
Most commercially available AI systems are optimized using the teleological perspectives and not the deontological perspective.
Ethical issues – a case study
An AI system introduced in 2015 in the U.S. failed to recognize the faces of African Americans with the same accuracy as those of Caucasian Americans.
- From a teleological perspective, this flawed AI system gets a go-ahead because Caucasian Americans constitute 72.4% of the country’s population
- From a deontological perspective, it can be rejected as its intention was not to identify people from all races.
- Digital platform companies, whose markets span many countries should aim to identify faces of all races with equal accuracy.
- AI facial recognition systems are used for law enforcement. Someone can be labeled a threat to public safety just because of limited data based on one’s skin color was used to train the AI system.
- The bias in the data used to train the algorithm stems from flawed historical and cultural perspectives and they contaminate the data.
NITI Aayog has a ₹7,500 crore plan to build national capability and infrastructure. The transformative capability of AI must be rooted in an egalitarian ethical basis.