Shakespeare wrote in Hamlet, “There is nothing either good or bad, but thinking makes it so.” There have always been a few people who have used technology for nefarious activities. So, with the invention of AI, it is natural that there will be some people who will use it for causing harm to humanity.
Deepmind co-founder Mutstafa Suleyman suggested that one of the best ways to mitigate the misuse of AI would be containment of the AI industry. A combination of technical, social and legal mechanisms could be used to effectively control, limit and, if need be, close down AI technologies at any stage of their development or deployment.
AI offers us a future of unparallelled possibilities. A few weeks ago, Google DeepMind had announced that it had developed an AI-based weather forecasting system that is more accurate than the European Centre for Medium-Range Weather Forecasts’ (ECMWF) model, which so far has been the global benchmark in weather forecasting.
This AI-based technology will go a long way in helping farmers, fishermen and so on, so that they are better prepared for inclement weather and natural calamities.
How do we fully utilize the capabilities of this new technological development? The traditional approach will be to get as many people as possible to download the app. The more downloads it has, the more successful such a technology is. No doubt, popularizing the app would be a significant first step in the usage of this new technology. But can we go further from here?
Last week, Mint reported that 87% of India’s districts are vulnerable to drought, 30% to floods and 46% of extreme rainfall. Between 2019 and 2023, India suffered economic damages totalling an estimated $56 billion due to these weather-related disasters.
The same report also pointed out that despite all the uncertainties around agriculture, only 26 million farmers in India have any insurance to protect their income from weather shocks.
Various studies have shown that the human brain does not have the ability to visualize future risks. What if the AI weather app’s output helps farmers better visualize future weather risks? Could it serve as a basis to convince farmers about the uncertainties of weather and persuade more of them to take insurance as protection from the vagaries of natural forces?
From this perspective, the success of an AI-based weather app should not be evaluated based on how many farmers downloaded it, but by the extent to which the new AI technology creates a whole new behavioural ecosystem around it.
This stage, at which the new technology becomes an agent of population-scale behavioural change, is when AI transforms itself into human-centred AI, which is what the world needs.
This development of human-centred AI is not going to be easy. First, one needs to tackle an observed assumption among some technocrats and technologists that the very creation of a technology amounts to its adoption. This belief is far from the truth.
Even in life-and-death situations, and even when new products are given away free, adoption does not happen easily. Poor adherence to tuberculosis medication and high levels of hesitancy when it came to covid vaccines some years ago are a few examples that demonstrate how difficult it is to create sustained adoption behaviour among humans.
The responsibility of creating human-centred AI cannot be left to technologists. The talent that is required to create AI technology is not the same as what will work to ensure it is widely adopted by end users. While the former is done best by technology specialists, the latter is best achieved by those with a deep understanding of human behaviour.
This approach of distinct teams for technology creation and adoption, with both working in collaboration, is behind the success of the global automotive industry. In the early days of motorized carriages, carmakers had to face the protests of horse-carriage owners, whose horses were scared by the sounds of motors and who themselves felt threatened by the rise of a replacement.
Today, it is an industry responsible for close to 1.35 million road-accident deaths every year across the world. The carbon footprint it leaves behind is another huge negative fallout of this industry.
The auto industry thrived and continues to withstand negative perceptions of it by playing up the positive side of motoring. The industry had to shed its initial arrogance of having produced a mode of personal transport superior to horse carriages.
An industry whose pioneer once declared “You can have a car of any colour as long as it is black” (for low-cost standardization) had to bow down to consumer needs and demands. Over the years, it became a consumer-centric industry. This consumer centricity helped save the automobile industry from being pulled down by its negative side.
Like the automobile industry, the AI industry too needs to find ways to multiply its positives without being overwhelmed by its harms. The ensuing transformation of AI into human-centred AI might be its best bet for future growth.
#humancentred #charm #people #adoption
