Pre-cum-Mains GS Foundation Program for UPSC 2026 | Starting from 5th Dec. 2024 Click Here for more information
What are we teaching the robots?
Context
Hearing ‘VR, AR, AI, Bitcoin’ in one sentence is like hearing ‘5GB, 512KB and Pentium’ in the late ’90s. It fires up your inner geek. But to the discerning, VR and AR are so 2017 that they are almost retro. And at the moment, Bitcoin is looking bubblier than a bubble bath.
AI picks up racial and gender biases, which is a cause for concern
But AI is a different story. The strides that are being made in the areas of machine learning, image processing, and natural language processing are on a scale that resembles the moon landing
Impact on the job market
The most discernible impact of highly capable AI is in the tech field, particularly software development
- The process of programming and testing will become increasingly automated, significantly reducing the number of people required in the supply chain
Better then the human programmers
In fact, last year, Google’s machine-learning programme started generating machine-learning programmes that were better than what human programmers could code.
Career Choices
If ‘blue-collar automation’ could be cutting jobs on the factory floors with robots, AI-driven ‘white-collar automation’ will be cutting jobs in call centres, stock exchanges and even laboratories. In this scenario, any decision to get into photography, cooking or writing after an engineering degree is starting to look quite well informed
Moral Dilemmas: Questions that arise
Beyond the more tangible questions of jobs and skills, AI also brings with it moral conundrums. There are basic questions such as ‘who should a self-driving car try to save: its driver or a pedestrian?’ and the more complicated ones such as ‘are we passing on our biases to machines?’
Picking up racial bias
- In 2016, researchers at the University of Virginia published a paper that described how two massive image collections used to train programmes to process images that had gender biases, like associating images of cooking with women
- These collections passed on the biases to their ‘students’, who not only reproduced the bias but even amplified them
Conclusion
If what singularity, that much-speculated-on churn of AI generating better AI, finally spits out is a version of our worst self, with a tendency for racist tweets and sexist memes, then there is much to be disappointed about.
Discover more from Free UPSC IAS Preparation For Aspirants
Subscribe to get the latest posts sent to your email.