This week, Geoffrey Hinton, of all people, lashed out at artificial intelligence (AI), a technology he helped develop. They fear that companies like Microsoft and Google competing aggressively to make products based on generative artificial intelligence, the technology that powers popular chatbots like ChatGPT, are running towards danger. Even before this, inventors had distanced themselves from the very technologies they helped create. Alfred Nobel, the inventor of dynamite, and J.J. Robert Oppenheimer was troubled by the destructive use of the technologies he had helped develop. In each of these cases, his walkout sparked important movements: the Nobel Prize and the Nuclear Non-Proliferation Treaty.
Hinton’s response is a reminder to the AI industry that they need to act urgently to address the growing fears surrounding the industry. AI companies would do well to remember what happened to the nuclear power industry. The truth is that nuclear power generation has one of the lowest levels of lethality per unit of energy generated among its various sources. So far, there have been only three major accidents in the industry, only one of which was catastrophic. But with each accident, the Three Mile Island accident in 1979, the Chernobyl disaster in 1986 and the Fukushima disaster in 2011, exaggerated and irrational fear mounted on the industry and the emotional distance with end-users went beyond repair. Does the AI industry have the wherewithal to face a potential ‘Chernobyl’ disaster caused by its technology?
The AI industry can carve out a bright future for itself by not only mitigating its bad effects, but also by building on its positive qualities. It could learn a lesson or two from the automotive industry. Whatever ills the world produces, from road accidents to carbon emissions, they are effectively countered by playing up its main benefit: the joy of road transport.
There is a lot of excitement about the AI industry these days, especially since the release of ChatGPT. But this enthusiasm for generative AI is unlikely to last long. This glee is only about the ‘manufacture’ and initial use of the product. For this glow to last long, generative AI technology must move into a critical phase: that of adoption, in the continued use of its products. Excessive enthusiasm in the ‘creation’ phase does not always translate into continued use of a new product.
The ChatGPT is not a machine whose use is determined by its calibration. It’s more like a tool that can produce usable output in the hands of a skilled user. The continued adoption of this new technology will largely depend on what it produces in response to our needs. It is therefore imperative that users of ChatGPT are equipped to use it as effectively as possible.
Anyone working in a creative industry like advertising knows that the quality of the creative output is only as good as the quality of the strategic brief provided to the creative team. Soon companies like Google and Chinese tech giant Baidu are going to launch their own generative AI tools. What will serve as a clear differentiator in the generative AI space is the quality of the signals provided to generative AI tools. Those equipped to provide intelligent, creative prompts will get the best out of these tools.
Advertising agencies typically employ another strategy to further improve the quality of their creative output: competition. Often, multiple internal creative teams are asked to work on the same strategic brief. This internal competition brings out the best in most people. Taking a cue from this idea, could the output of ChGPT-dependent neural networks be used to fire real neurons in the human brain? For example, can the output of generative AI be considered as a benchmark to beat humans?
Human beings have always responded positively to the challenges that new technologies have thrown upon them. For example, the most prominent artistic movement in Europe in the early part of the 19th century, when industry was on the rise, was Realism.
Its focus was representation with the least distortion of reality. Around this time, the technology of photography was also invented, which forever changed the nature of visual representation. Photos could create images that were far more realistic than the best any human artist could paint. So how have human artists and picture makers dealt with this competition from the new technology of photography?
Painters started exploring new directions of artistic expression using different dimensions of painting. The artistic movement Impressionism was the first to deviate from realistic norms. Impressionist painters such as Monet focused on conveying the essence of a scene through colour, light, movement and emotion. Expressionism, as an art movement, emerged to express the meaning of emotional experiences rather than physical reality. In Cubism, subjects were analyzed, broken down, and reassembled into an abstract form with multiple perspectives, rather than depicting objects from a single perspective. There was also Surrealist art, which allowed the unconscious mind to express itself on a canvas.
The emergence of photography as a technology gave rise to so many great artists, such as Vincent Van Gogh, Pablo Picasso, Salvador Dali and many others, who changed the way we think about art. If so, just imagine the human potential that could be unlocked by harnessing the power of technology like generative AI. Geoffrey Hinton would then be proud of this development.
Biju Dominic is the Chief Evangelist for Fractal Analytics and the President of FinalMile Consulting.
catch all business News, market news, today’s fresh news events and Breaking News Update on Live Mint. download mint news app To get daily market updates.