AI technologies bring greater precision, precision and speed to analysis and forecasting. They can perform risky activities and repetitive tasks that are boring for humans. They are also readily available and make it easy to expand technology services and reduce costs. But how are these effects felt around the world, especially in a context of growing inequality?
While we have witnessed a decline in the incidence of extreme poverty over the past decades (progress which is now being reversed by the impacts of the pandemic, the climate crisis and rising debt), Inequalities have continued to increase globally, across income, wealth, assets and human development. Those who already have deep pockets or high levels of development have accumulated more proportionately, which has widened the gaps between and within countries. So what does AI mean for the world’s most vulnerable people?
Research on AI and automation reveals that countries face different potential levels of automation, due to differences in employment, job automation, labor market structures, education , skill levels and government policies. Jobs and industries involving more routine and codifiable tasks face a greater risk of automation, while others that require high human capital or technical skills are more difficult to automate and therefore more resilient. China and India are among the countries whose populations face the greatest risk of automation.
Job opportunity vs vulnerability
Developing AI solutions also includes tasks that depend on human oversight. Most machine learning applications use supervised learning, which requires the correct labeling of the data sets to train the AI models. Sometimes referred to as ‘ghost work’, it is often contracted out to a remote workforce and includes tasks such as tagging and labeling images or other content, moderation, proofreading, editing, editing and sorting. While these new forms of work offer valuable income-generating opportunities, they also remove many traditional safety nets protecting workers and risk perpetuating poor working conditions and increasing the vulnerability of existing jobs.
While AI offers many potential benefits, in the short term it can lead to issues like the displacement of jobs and the polarization of skills, leading to wage inequalities. Different countries and regions may be differently prepared to deal with affected workers. Mitigating mechanisms such as policies protecting vulnerable workers, economic safety nets for the unemployed, retraining initiatives and the ability of other sectors to absorb displaced workers could significantly alter any negative societal impacts.
When these mitigation mechanisms are not in place, the benefits of automation and AI adoption will be concentrated in the hands of those who own the technologies, unless they are reinvested in the process. of production. Additionally, when AI disadvantages those in mid-skilled, automatable jobs and increases the returns of highly skilled workers, wages can be polarized. Highly skilled workers may start earning more while others face lower wages and increased competition for lower skilled jobs that resist automation.
AI adoption and the digital divide
The potential benefits of AI are harder to reap where access to digital infrastructure and data is lacking, and skill levels and cultural beliefs condition people’s interactions with AI. More than 10% of the world’s population is illiterate, around 40% still do not have access to the Internet, and more than half do not own a smartphone. These poorly connected or disconnected populations are unevenly distributed geographically and excluded from the many AI-powered services that facilitate access to vital information for those who are connected. This includes e-commerce, education and training, democratic processes and health services.
Beyond that, there is a digital divide in terms of the ability of people to use devices and the internet, understand digital content, create and participate in it. This divide is linked to other socio-demographic characteristics such as gender, race, income, education, location (whether urban or rural) and age. When economies do not have a sufficient pool of skilled workers or IT resources to collect, store and process data, adoption of AI to meet local needs will be limited.
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Additionally, some communities may not have the resources to develop AI solutions, and those designed externally may not be fit for purpose. They may not reflect a wide range of perspectives in their design or in the data collected. When vulnerable and disconnected populations are insufficiently taken into account in AI design, existing digital divides can widen further.
Fight inequalities and improve efficiency
While the inequitable distribution of AI and automation poses challenges, it can also offer many potential benefits and solutions. Sustainable, responsible and accountable AI practices take into account the impact of a product on the world and on various populations. This thoughtful approach can also avoid worsening inequalities or harming vulnerable people.
The adoption of AI can increase efficiency and profits, and help ease the labor market’s transition from repetitive routine tasks to those requiring cognitive and socio-emotional skills. Countries and regions can begin to direct their efforts towards knowledge-intensive services, thus avoiding spending their money and scarce resources on expensive or inefficient activities that could easily be automated.
While the adoption of AI may worsen the situation in the short term, putting in place the right policies could mitigate these risks. Historically, technological upheavals have often temporarily led to an increase in inequality, with some populations winning and others losing, but in the longer run these differences have tended to diminish and the overall level of wealth has increased.
It is crucial that those responsible for developing and adopting AI solutions are aware of the potential pitfalls and develop frameworks to counter any negative effects. AI enables faster and more accurate processes and its benefits should be harnessed for the benefit of critical and productive sectors around the world.
I discuss this topic in more detail in a recent report from the Alan Turing Institute.
Sanna Ojanperä is a PhD student specializing in platform work and AI in the workplace at the Alan Turing Institute and the University of Oxford.
This article originally appeared in our issue The Future of Work: AI and Automation.