Recent advancements in AI, including upgrades in large language models and image generation, have showcased immense potential. However, odd behaviors in these systems, like Bing’s alter ego “Sydney” and eerie image generations in Stable Diffusion, raise concerns about machine super-intelligence. Nick Bostrom’s warnings about unregulated AI development emphasize the need for industry guardrails to ensure safe AI evolution and prevent uncontrollable advancements.
Generative AI has had a transformative impact on text and visual arts. While the AI’s ability to mimic artistic styles raises copyright concerns, does this constitutes “copying”? How will the definition of artistic talent evolve in the AI era?
The transformative potential of OpenAI’s ChatGPT is like how Google revolutionised search. ChatGPT could disrupt the targeted advertising model that sustains most internet businesses by providing summarized information instead of directing users to specific websites. The technology’s potential to change the internet’s fundamental business model is emphasized.
Education is evolving in the age of technology and AI. While modern education is moving away from rote learning to skills like critical thinking, students should also be trained to use AI as a research tool. However, the rise of AI-generated content poses challenges in distinguishing genuine research from fabricated material, necessitating the teaching of healthy skepticism and cross-referencing skills to students.
AI is being increasingly used in journalism and law. OpenAI’s GPT-3, can produce content nearly indistinguishable from human-written work. But we need to remember that AI is a tool, not a substitute for human creativity.
There are parallels between the myth of the Tower of Babel and the modern linguistic challenge of the internet. In this India has a unique need for translation technology, given its linguistic diversity. Bhashini may be the answer.
The South African patent office has granted a patent to an artificial intelligence program for an invention it has made. India granted a copyright to an AI application along similar lines. It is not clear how an artificial intelligence can exercise the IP granted by prosecuting a breach or negotiating commercial arrangements for its license. All these actions will have to be taken by humans on behalf of the AI in which case what is the point in calling the algorithm an inventor.
Ford’s internal combustion engine car beat Edison’s EV to the market and as a result we are on our current fossil fuel dependent path. What if things were different. Few Shot Learning is an alternative to data guzzling artificial intelligence models that allows us to not be dependent on large datasets.
The argument that data localization will boost India’s AI competence is flawed. Simply storing data in-country doesn’t translate to AI development, as data structures are company-specific and insights are often non-transferable. Instead, focusing on building AI infrastructure, incentivizing researchers, and encouraging homegrown AI development with existing data is more effective for fostering AI prowess.
Many prominent figures have warned of the dangers of uncontrolled AI development. Even so, skeptics argue that humans will always control machines. Modern AI lacks the ability to reason with “what if?” questions and counterfactual imagination, which are essential for human-like intelligence. Though machines are not yet at this level, I would urge caution in advancing AI towards these capabilities.
