This article is based on a panel discussion at the Writing Symposium: Putting the I in AI, organized by the Center for Writing, NYU Abu Dhabi UAE. Sabin was one of the speakers.
It is indeed a hard pill for thousands – perhaps millions – to take that AI or broadly speaking new technologies will remove humans doing menial and not so menial jobs the world over. And it certainly would not be limited to one sector alone but across the board. It is the negative, flip side of the coin even if one looks back in retrospect at different industrial revolutions of the past. But the bigger question or rather the ongoing conversation about technology replacing humans really needs to be addressed with understanding and reasoning.
There will always be hype about the things we know not of or have little information about. Myths are created due to lack of information and knowledge. The silverscreen, especially Hollywood, did much to magnify the myth of AI; metamorphosing it into gargantuan proportions with the likes of Terminator, the notions of Skynet or VIKI (the latter in I, Robot. An apocalyptic world decimating humanity, as if we are not living in one or doing that to ourselves in the first place!
In a Guardian article, poets and authors shared their apprehensions as well as confidence when it comes to AI. Adam Robert’s wrote ‘surely one difference between a machine and a human is that the machine doesn’t have a subconscious – it’s all circuits and logic gates, all network connections and processes. And yet when the machine writes, it writes like the subconscious – a collective subconscious, I suppose: the swirling-around of a million online interactions, searches, and texts. Perhaps this is an artefact of its novelty. As the technology develops, perhaps it will add-in the “conscious mind” part of writing, the revising and correcting, the checking over and polishing. If we add in that, then the finished product really will be indistinguishable from the stuff human writers produce.’
In the same article, Roberts talks about Sir Walter Scott and how he kept on churning novel after novel. When in the end Scott suffered a series of strokes, could barely speak, when his conscious mind was ‘disengaged’, he kept on writing… perhaps not as good or what convention might deem good but it had its remarkable Scott brand on it. This may seem simplistic but the difference when one looks at the analogy is that Scott is a sentient being – an amalgamation of socio, political, economic, cultural, emotional influences, social interactions; while the other is artificial… a sum total of algorithms, text, networks, logic. It is, at best, merely a mimic. It is artificial, it is trained by humans.
Sure, the story does not end there. But one has to see and assess the many layers of this scenario. Indeed one has to grapple with the lightening speed of innovation that is happening today compared to ones in the past. But what one fails to consider is human learning is also taking place side by side. Perhaps, not at the same pace but – and to reiterate – history is the perfect revelation when it comes to any industrial revolution. Bottomline is, it is learning, certainly not training.
Artificial Intelligence is a tool that needs to be first understood and then leveraged. There are many benefits to be reaped and it all begins when one stops reacting to the hype.
In a Reuters interview, Tomás Dodds – a researcher opined: “We need to try to understand what hype is and what hype does, which is to simplify very difficult concepts like innovation or how these technologies actually work. When we hype technologies, what we’re doing is kind of creating a myth around them, and not putting the focus on the political, cultural and social consequences that these technologies are going to have. By hyping these technologies, we are reducing the framework of our understanding of what these technologies actually are, and how we should appropriate them.”
Indeed many of the fears and apprehensions are real and very well founded. Emerging tech, including AI, Machine Learning and Large Language Models (LLMs), together these can be like an unbridled horse. The challenges are numerous. Are we looking at the right ones? On the one hand is the question of humans being replaced by technology and on the other how these technologies are being developed, who is training AI, the biases that seeps in and how technology is appropriated, to name but a few.
The challenge is also how and in what capacity AI is assisting or replacing human efforts in creating socio-political as well as economic narratives. The problem begins with who is working on AI. Lack of diversity means the tendency to have bias. Additionally, if one looks at the influx of information and the ongoing media warfare as far as social, new and traditional media is concerned, one can easily discern how this tool has been leveraged to create and propagate mis-info, disinfo and mal-information, thereby polarizing the world.
The risks are manifold as they are grievous. From an individual as well as organizational point of view, AI needs to be seen as a resourceful tool, not a nemesis, which assists us sentient beings. Humanity has always feared the unknown, the unexplored and most importantly change, which is ironic since change is inevitable. This debilitating fear also plays a villainous role in hampering our ability to adapt and adopt.
It has been said before as it is currently reiterated: the critical need for all stakeholders to have a seat at the table. Diversity is not just key to challenge biases, but also for transparency and accountability. Policies, regulations and strategies require a bottom up approach together with the already existing top-down one. Experts in this field urge the importance of information sharing practices to understand the technologies one is working with. This means not to work in siloes. Ending gatekeeping and monopoly of big tech based in capitalistic regions is another issue that needs to be addressed.
So again, are we really asking at the right questions?
Image by GrumpyBeere from Pixabay
