Rrecently Jon Stewart made a segment mocking the AI promises highlighted by tech CEOs. I don’t think automating toasters is the best way to showcase the potential of AI, as Jon did, but I agree with the central premise of his argument that the disruption caused by AI will be leveraged to prioritize profits over people. It will likely cause one of the largest and fastest labor displacements in human history.
I run a Silicon Valley-based AI company focused on solving climate change, and I am a former policymaker for the government of India. At the Davos 2024 World Economic Forum, my discussions with the media, heads of state and CEOs of Fortune 500 companies highlighted global perspectives on AI, where AI was widely discussed to unlock the next productivity revolution, promote creating wealth and lifting people out of poverty. poverty, democratizing and reducing the cost of access to information/education. Most conversations about risks to AI have centered on the risk of AI extinction and the regulatory barriers we needed to protect ourselves from that future. My conversations about the political and social risk from increased labor displacement from AI have been met with skepticism even from my community of fellow AI founders.
The reality is that what we are witnessing through AI is a force multiplying the pace of structural labor displacement. For example, the Internet era and globalization have allowed U.S. companies to outsource customer support to developing countries such as India, Vietnam, and Thailand, to the detriment of the middle class in some regions of the U.S.; Now, a chatbot built on an LLM enterprise stack is proving to be more/equally effective than humans in customer support, making them redundant. This impact will be even more severe in high-income countries. A recent IMF report mentioned that around 60% of jobs will be affected by AI, likely leading to increased inequality. Half of them will benefit, but the other half will be made redundant/less effective, leading to lower wages, reduced purchasing power and a lower standard of living in an inflationary era.
These labor displacements accumulate over time, mainly affecting the lower and middle classes and, in turn, becoming political movements. In the US, the wave of globalization and automation of the last 30 years has created the most disruptive political movement, resulting in the election of Donald Trump. However, this time, disruption is also coming to some white collar workerswhich makes its effects unknown and potentially more dangerous.
Typically, the debate over the impact of AI on work hinges on two arguments. One is more binary argument of some economists that there will be job creation and destruction and that the net impact will be positive. Furthermore, workers who will lose jobs can be reskilled/reskilled into new job categories that will be created and made possible by the redistribution of wealth.
The second argument is that the global promise of AI in areas such as education and research more than ethically offsets the negative impact on society through job losses. This argument is made by the founder/investor community, who are quick to point out the technological wonders of the Internet boom, such as smartphones, and its impact on connecting billions of people in emerging economies like India.
The first argument assumes that the pace of displacement – job losses in a region/sector – will be slower than the pace at which reskilling can happen and that the redistribution of wealth is fair and smooth. America made the same assumption about the transition to renewable energy for coal mining workers and thus became one of the few major economies where climate change has become a polarizing issue. Namely, in the redistribution of wealth, the share of the richest 20% in the US Rose of 61% in the 1990s to 71% in 2022.
The second argument assumes that education equates to job preparation, as I saw in my home country of India, where 80% of the 1.5 million engineers who graduate every year are considered unemployed for any job in the knowledge economy. Further down the hierarchy of needs, having a smartphone rarely takes precedence over having a decent job and an affordable meal for the family. In second place,
This brings me to the uncomfortable truth of accepting our responsibility, as founders of AI, to decide the course of this transformation together with governments. Our obsession with profitability has often led us to focus more on applications like creating smarter chatbots to replace customer support or sales representatives, rather than on the more challenging but significant problems for humanity, like improve the productivity of smallholder farmers in the developing world or solve Cancer.
Secondly, we need to work with governments and regulators to ensure that some of the wealth created in this process is redistributed fairly and equitably. For example, we can co-finance the creation of NGOs like Coalfield Development. This community nonprofit engages coal miners who have been unable to transition to renewable energy jobs by helping them gain skills in construction, agriculture and solar installation.
Third, governments can learn lessons from Norway’s efforts to ensure the fair redistribution of wealth created by the oil boom in the 1970s. Norway created the Global Government Pension Fund (Norwegian Oil Fund) in 1990 to manage the oil revenues for future generations, aiming for economic stability through diversified global investments. It currently has the second lowest inequality in the world.
Lack of action now is a path to a future that magnifies the political, social and environmental crises we have seen over the past three decades. However, the world will still see more billionaires than ever before and possibly the world’s first AI trillionaire in the next decade.
This story originally appeared on Time.com read the full story
