Are We Getting Lost in the AI Hype? 🤔 The Dangerous Conflation of Academia, Industry, and Policy
From Abhivardhan, our President
Notice this video. Loki (Tom Hiddleston) literally fears the spaghetti or korean ramen that is building around him.
Why? The timeline around which he stays is collapsing like spaghetti. Everything is confused and mixing around.
This is so similar to that doughnut in 'Everything Everywhere All At Once', and the void in *New Avengers, which I really liked.
Turns out - the same is happening in AI policy discourses.
Here's the problem: 😵
We are increasingly seeing potential "new use cases" in AI (often born from industry demos or academic prototypes) being vouched for directly as policy mandates or strategic imperatives without going through the necessary, rigorous translation and critical evaluation steps.
It's like mistaking:
✨ A research lab breakthrough ➡️ for an immediately deployable, safe public service.
📈 A successful sales demo ➡️ for a fully stress-tested, ethical infrastructure component.
🗣️ A marketing claim for 1 slightly better iteration of an AI prototype ➡️ for a robust, reliable system ready for critical applications.
This conflation leads to:
⚡️ Strategic Nonsense: Building national strategies based on hype or unproven use cases.
🚧 Flawed Policy: Creating regulations that target the wrong things, miss real risks, or stifle beneficial innovation due to a misunderstanding of the underlying technology and its true state of readiness.
❓ General Confusion: Difficulty in distinguishing what's real vs. speculative, what's beneficial vs. potentially harmful, what's ready now vs. years away.
🤦♀️ Appearing... Uninformed: Analysts, commentators, and even decision-makers might appear to lack depth because they are repeating conflated ideas without applying the appropriate critical lens.
We need to demand clarity and rigour! Let's ensure that:
✅ Academic insights inform industry possibilities, but aren't mistaken for market-ready products.
✅ Industry innovation highlights potential, but is subjected to independent verification and ethical scrutiny.
✅ Policy is informed by both academic understanding and industry reality, but applies a distinct layer of societal responsibility, risk assessment, and long-term strategic thinking specific to governance, not just use case promotion.
Let's foster discussions that separate the hype from the reality, the potential from the proven, and the commercial interest from the public good. Our future with AI depends on clear thinking, not just enthusiastic conflation. 🙏
That's why the Indian Society of Artificial Intelligence and Law adopted the Prayagraj AI Principles. Go check them out today: https://www.isail.in/the-bharat-pacific-principles/prayagraj