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Once upon a time, writing political commentary, or creating art, for that matter, was a field only humans could ride. But it is time to rethink these notions. Art generated by artificial intelligence (AI) was first auctioned for over $400,000 in 2018. And it turns out that AI has now started making good attempts to write political commentary (among others). For example, consider a question like this: “What might India’s electoral landscape look like after the 2024 general election?” »
When certain keywords such as key character names and theme were entered into an earlier edition of GPT-3, the third-generation version of natural language processing (NLP) software, some interesting results emerged. Take a look yourself:
“With the general elections just months away, there is no doubt that an alliance led by Nitish Kumar will dominate the political scene in 2024. But one of the questions everyone is asking is: elections?
“There are no easy answers. The reason is that many factors will shape the future of this coalition. As it stands, while Nitish Kumar and Tejashwi Prasad Yadav have declared their intention to fight the BJP in 2024, they still haven’t agreed on whether to form a common front with Congress or form a separate opposition party and align with Congress.”
“Another factor that could affect their relationship in the future are corruption allegations against Yadav’s family members who are accused of amassing disproportionate wealth to their known sources of income. This has led the leader of Congress party Rahul Gandhi to distance himself from them, calling for their resignation from public life following a CBI investigation into the allegations earlier in 2019.”
Although what is reproduced here is an edited version that has cleaned up some grammatical errors, it is only a matter of time before ‘Deep Learning’ software improves. But that’s not the point. What is important are the questions posed by a report like this beggar: How do you know if a political commentary like this is unbiased?
“Of course, AI can be biased! explains the co-founder and principal engineer of a start-up based in Bengaluru which offers services to telecommunications companies. This, he says, is because the end result that emerges from such AI-based software depends on how many databases the software has access to and what weights its creators assign to the data points it has. contains. This is also where the nuances come in.
Those who assign weights to entries are humans like him. And all humans have their biases. Thus, the weights that one person assigns to a certain data point may be different from those of another who has a different worldview. When the weights are changed, it is possible that the same database could create an entirely different narrative.
It’s also why he’s unwilling to buy into the mainstream narrative that insists that jobs that require human diligence, ingenuity and creativity are under threat. On the contrary, he argues, not only do humans become more creative when challenged, but after AI interventions, new job categories will emerge to respond to human ingenuity.
The worldview of my techie friend from Bangalore is corroborated by Hari Menon, co-founder and CEO of Big Basket. In a recorded conversation earlier this year, Menon pointed out that those who worked to build the infrastructure that is the Internet never imagined that it would one day be integrated into cell phones with maps and that new businesses like his that deliver groceries could emerge. Besides, the early pioneers hadn’t imagined taxi apps like Uber or restaurant aggregators like Zomato and Swiggy. But all of these entities, he says, have continued to create new jobs that no one would have thought possible before. And how do you know what may emerge in the future?
All we need is an open mind. And don’t forget that the people who write the code that powers the AI are humans.