Simply Speaking: Importance of AI literacy over reactionary policies rooted in fear

These pioneering models take on novel tasks they were not trained for and perform very well. That's why AI and supervised deep learning systems have now graduated to AGI. The key property of generality has already been achieved. The early AI systems were endowed with narrow intelligence able to concentrate on a single task. Their benchmark was attaining human level. MYCIN, only diagnosed and recommended treatment for bacterial infections. SYSTRAN only did machine translation. IBM’s Deep Blue only played chess and so on...

Later deep neural network models trained with supervised learning such as AlexNet and AlphaGo successfully took on a number of tasks in machine perception and judgment that had long eluded earlier heuristic, rule-based or knowledge-based systems. But emerging applications like OpenAI’s remarkable text-to-video generator Sora can potentially reshape marketing down to its foundations.

Sora’s uncanny ability to transform simple text into strikingly polished 4K video unlocks new frontiers for brands and agencies to drive engagement and ROI through visually dynamic campaigns personalised at scale. The potential for localised video content across languages, demographics and sectors appears boundless. As consumer attention increasingly shifts to digital video, reducing production barriers promises democratisation for small and large businesses to better compete in an intensely visual age.

In 2022, the projected global market revenue for online video advertising will already stand at a staggering $75 billion. As India's digital maturity and smartphone adoption continue to accelerate, Sora-like AI video solutions can no longer be ignored by forward-thinking marketers keen to engage this new generation of mobile-first consumers.

Such flexibility could allow marketers to swiftly generate product demonstrations, concept videos, explainers, advertisements, and other visually immersive content tuned precisely to messaging goals. This includes dynamic personalisation at scale, like showing clothing on varied models or positioning products in customised lifestyle settings. No longer limited by production bottlenecks, marketers can pursue more experimentation and iteration to better the engagement.

Indian edtech firms, for instance, can leverage Sora to develop personalised and cost-effective educational video content tailored to regional curriculum needs. E-commerce players can minimise product uncertainty by generating virtual try-on videos to engage customers better. Even specialised product categories like jewellery or textiles can showcase intricate details easily ignored in images and text.

I am not a doomer but a boomer. I feel the river flows only in one direction. Sora does raise valid concerns around copyright, ethics and misinformation, and these need continued vigilance. However, if scaled responsibly, Sora represents a democratising force, levelling the playing field for smaller brands otherwise excluded from sophisticated video campaigns. Just as DIY website builders and email services expanded access decades ago, AI video production can drive greater creativity, diversity and healthy competition across the marketing ecosystem.

Tapping emerging technologies has always required the courage to envisage new possibilities combined with the wisdom to navigate risks. With careful steering, Sora-like winds can take a marketer on a voyage never conceived. The time for exploration has arrived.

But as remarkable as Sora may be, we must acknowledge it represents only the earliest glimpses of an AI-driven video frontier still very much in its infancy. While capabilities today focus predominantly on transforming text to video, rapid innovation drives systems towards more interactive, multi-modal interfaces accepting verbal commands and even hand motions as inputs. Imagine marketers developing a storyboard scene-by-scene with verbal or textual instructions only, fluidly bringing product concepts and creative visions to life without extensive production requirements. Systems like Sora hint at a not-too-distant future where video personalisation and iteration can be dictated in real-time by marketers themselves, optimised dynamically for campaign goals.

Accessibility barriers around professional video production may fall fast. Emerging tools like RunwayML already enable those with zero coding or design experience to train AI models on custom datasets for tailored video generation applications. As synthetic video creation grows more commoditised, expect new crowdsourced marketplaces around stock video elements and datasets to minimise production costs further.

Tactical implementation of ideation could accelerate dramatically, freeing resources towards more strategic messaging experimentation. However, such rapid iteration heightens the risks of perpetuating societal biases if governance does not keep pace. Thoughtful oversight around training, data curation, model evaluation protocols and source transparency remains critical.

We must also examine concerns around generative video more holistically within broader technology regulation debates. Beyond Sora itself, tensions simmer around legal frameworks struggling to balance free speech, privacy, public safety and innovation in an increasingly complex digital ecosystem. Whatever legislative paths India pursues, will profoundly influence the AI landscape regionally and globally.

It may benefit policymakers to assess generative video governance within segmented contexts rather than one-size-fits-all decrees. Blanket bans risk overreach that stifles progress and accessibility. More pragmatic guardrails tailored across consumer, commercial and research domains could nurture innovation responsibly. Policy, too, must progress iteratively, evolving dynamically alongside technological change.

For all the risks, the promise of expanded video creativity and personalisation should not be readily dismissed, especially within a youthful, smartphone-native population like in India. Channelling energies into promoting AI literacy and ethical design principles may better serve the public than reactionary policies rooted in fear. If digital maturation has taught us anything this past decade, possibility scaffolded by commercially viable applications works wonders.