Artificial intelligence (AI) has over the recent years managed to progress the digital infrastructure (and digital economy) by advancing the field of superhuman capabilities. The opportunities that AI technology poses are expanding from medicine and health to transport and education, and most importantly, economic growth that transcends the firms and the respective economies. Time and again, the debate around AI technology takes the form of the challenges regarding labour displacement, economic inequality, market instability, reinforced totalitarianism, and a shift in the global economy. In the upcoming field of artificial intelligence technologies, companies (buyers) who are the innovators of this new system of production find themselves in need of a particular service to improve their production function by machine learning and advanced AI applications. This service is called data annotation - it is the process of sorting data and labelling or tagging them, the said data can be images, texts or even audios.
The training, validating, labelling and sorting of high volume data is done to feed the annotated data to the machines. In turn, from the annotated data, the machine learns how to read the patterns from the input and provides respective outputs, in this case, it acquires a method of production and simplifies the process of production based on the industry. The machine learns to adapt and produce products, and as a result, the need for labour reduces. In such a scenario, it is hard to refute a decrease in employment. However, the current day AI systems require human interaction and input to reach the final step of production, and this is precisely where data annotation companies come into play. For a company to annotate their data requires labour (including employee training), time, technology (data annotation software) and capital. Hence, this production process of annotating data is outsourced by the company to freelance microworkers, crowdsourcing platforms, or companies that provide annotation services. The nature of the market for data annotation puts it into the category of the digital service industry, which in turn makes this market a part of the digital economy.
How is AI creating more digital labour?
In recent years, AI has provided a platform for a new market to emerge in the digital economy, creating a new type of production process, new skills for the digital labour and a new area for businesses to grow. As a result, there is a niche market for data annotation. Data annotation is easy to teach to anyone who has a basic understanding of how to use a computer. Keeping this in mind, many entrepreneurs have come up with a solution for global data annotation needs. These entrepreneurs act as middlemen to digital labour and companies in need of annotated data. These entrepreneurs set up data factories where they employ people from underprivileged backgrounds, train them and give them fixed employment with employee benefits. Companies such as iMerit and Samasource have been exceptional in creating jobs in rural parts of India and Africa and train data for AI. The process of sourcing work to the economically weak sections of the labour market is 'Impact Sourcing'. Through the help of companies like Samasource, AI provides digital work across the globe. Digital platforms such as Upwork and Amazon Mturk have the potential to guarantee digital work for employment seekers; even so, there is no long-term job security or employee benefits. This article reviews just one aspect of the AI system and industry.
The creation of digital labour and job opportunities due to AI is proof that AI is learning from humans and needs humans to function. The advancement of AI in recent years has intrigued several scholars in different fields. Institutes such as 'Centre for Governance of AI' at Oxford University and 'AI for Good' project at University College Dublin aim to assist humanity to apprehend the benefits and alleviate the risks of artificial intelligence. Many other research institutes also focus on the political challenges that arise from changing AI systems and work towards a better policy framework that benefits the society as well as business positively.