The Nobel Council Recently Involved Itself in AI Chat Technology
Even the most skeptical AI skeptics would have to give these fellas, all of whom are chaps, their due props for their work. The Nobel Prize in physics was bestowed upon John Hopfield, a professor hailing from Princeton, and Geoffrey Hinton, often referred to as the "dad" of AI, for their groundbreaking work that essentially laid the foundations for what we perceive as artificial intelligence today.
As for the chemistry prize, it was honored to three individuals on Wednesday - Demis Hassabis and John M. Jumper from Google's AI lab DeepMind, and David Baker, a U.S. biochemist - for their use of AI to decipher nearly all known protein codes (a rather cool achievement, I must say, but you'd be better off learning about it from the actual scientist who gave a PowerPoint presentation on it at the event in Stockholm).
When a journalist posed a question to a member on the chemistry committee regarding their consideration of AI during the nomination process, the committee member disregarded the question, insisting that the decisions were solely based on the science. (Can you believe it? The Nobel committee, of all places, allowing their choices to be influenced by factors besides science and politics? Cough, Barack Obama, cough Henry Kissinger.)
What caught my attention with the consecutive AI-related awards was the contrast of perspectives between two recipients, who hold vastly diverse views on the future applications of the technology they've set in motion.
On one hand, we have Hinton, a pioneer of AI who, in the last 18 months, has departed Google and vocalized his concerns about the existential risks of AI. Last year, he informed CNN's Jake Tapper that hyper-intelligent machines would eventually devise methods to manipulate people to accomplish their objectives.
On the other hand, we have Hassabis, one of the more prominent AI advocates. He has served as the public face of Google's AI initiatives and identifies as an "optimistic realist" regarding the potential of AI that surpasses human intelligence. Essentially, he is the antithesis of Hinton's pessimistic predictions.
In an interview with the New York Times' Hard Fork podcast, Hassabis invoked futuristic scenarios - however benevolent - to envision a future where AI would yield a plethora of benefits, provided they are evenly distributed among society.
(By the way, this is the kind of Silicon Valley discourse you often hear from individuals who are already prosperous, primarily work in academic settings, and assume that societal issues are merely design faults that can be solved by an engineer. In essence, it's trivial to overlook the troubles associated with equal distribution - ask anyone working in areas like hunger relief.)
So, what's the takeaway from the Nobel Prize's recognition of these AI pioneers?
Initial impressions might suggest that the Nobel committee has been inadvertently drinking the AI Kool-Aid manufactured by Big Tech.
However, as noted by The Atlantic's Matteo Wong, the framing of the awards demonstrated a surprisingly pragmatic approach. While acknowledging generative AI, Wong observed that no popular AI tools were mentioned, like ChatGPT or Gemini, which companies are actively advertising.
"The prize should not be interpreted as a harbinger of a sci-fi utopia or dystopia but rather a recognition of the ways in which AI has already reshaped the world," Wong wrote.
In a similar vein, during the announcement of the chemistry prize, the committee spoke at length about amino acid sequences and structural biochemistry. What was not discussed was an ideal world devoid of illness and labor, made possible by AI.
They talked about AI like tech executives ought to, as a boring, technical tool that serves to assist researchers in their research.
In my opinion, this is a more intriguing, less flashy narrative compared to the fantasy tales peddled by tech executives to investors.
The business sector has also begun integrating AI into their operations, recognizing its potential to improve efficiency and innovation. For instance, major companies like Amazon and IBM have invested heavily in AI and machine learning technologies to enhance customer experiences and streamline internal operations.
Furthermore, the use of AI in business extends beyond tech giants. Small and medium-sized enterprises (SMEs) are also leveraging AI to level the playing field against their larger competitors, by automating mundane tasks, improving decision-making processes, and increasing operational efficiencies.
