The hubbub around generative AI and its sweepingly disruptive potential, has rekindled the old debate on AI ‘Apocalypse Now’.
Though interestingly, this fear and loathing coincides with everyday AI integration and pervasive use across all walks of life, from facial recognition, voice assistance, meta-encyclopedic chatbots, to other interactive features. This must be the central paradox of our time: everyone claims to be wearily anxious of AI, and yet displays gushing enthusiasm about its promise.
Tech wizards including Bill Gates, Steve Wozniak, Elon Musk, and thousand other scientists and tech tycoons have signed an open letter that calls for at least six-month moratorium on training all AI systems powerful than GPT.
Geoffrey Hinton, a pioneer of neural networks, widely regarded as the ‘Godfather of AI’, resigned from Google and issued a grim foreboding about the ‘existential risks’ of AI.
Peril or Promise?
The alarmism encapsulates a defining trend about our topsy turvy era – skepticism about never-ending, as-good-as-it-gets, unbounded tech optimism.
This goes along with the acknowledgement of what Azeem Azhar calls ‘The Exponential Gap’: the inability of social-cultural-legal and institutional frameworks to keep up pace with rapid innovations and drastic tech advances. Bridging this divide, and solving the ramifications stemming out of it, will be a contentious issue in years to come.
It’s not just individual behaviors, communities, or societies that are warily ambivalent about AI. Unlike other previous tech advances, it is simultaneously the most intrusive and the most insular. From customized content to geopolitical tides, AI has it all in its thrall.
Intense completion between USA and China to develop next-gen AI, in the quest to become the world’s leading tech superpower’, is being considered a throwback to the Cold War and Space Race Redux.
With red-lines drawn and deploying all tricks-in-the-trade, including licensing, stringent norms, standardization, trade restrictions, regulatory oversight, and zealously guarding innovations, the intent appears to retain a tactical advantage and cutting-edge while precluding rivals.
By the end of the year, G-7 will establish an ‘AI working’ group. USA and EU have signaled their intent to deepen AI collaboration and establish standards.
Silent Winners
What’s most idiosyncratic about AI is not the human or digital brain debate, or enormous capability to control and manipulate, but that accelerating pace of innovation follows a unique logic of its own.
One has to keep in mind extreme unpredictability and the law of unintended consequences while dealing with it, at organizational as well as trans-national levels.
As opposed to nuclear or space programs in the heydays of the Cold War, innovation and tech incubation is not top-down, but more participative, multi-vectored, and competitive as a result of booming startups and dynamic private sector.
Few months back, a leaked memo by an anonymous Google senior software engineer create quite an uproar. The stark memo says that Google is not winning the AI race, but neither is Open AI’. Celebratory news seems to come from an unexpected quarter: the open-source communities.
The reasons for tech behemoths losing grip and open source community securing gains are inherent to the nature of digital innovation: distributed, decentralized, smaller, agile models, drastic cost-reduction, knowledge diffusion, scalability, multi-modality, newer iterations and upgrades.
This anticipation may or may not turn out to be true, but coming from an insider it surely indicates things being more complex than we think.
It remains to be seen who masters AI, but the result may bewilder us all. Facts are stranger than fiction, and AI is scripting its own hyper-reality.
Disclaimer: Views Expressed are Author's Own. Geospatial World May or May Not Endorse it
