A former CEO and executive chairman of Google, recently suggested that the tech giant’s apparent lag in AI development was due to the company prioritising employees’ personal wellbeing over progress. Eric Schmidt : “Google decided that work-life balance and going home early and working from home was more important than winning.”
Author
- Peter Bloom
Professor of Management, University of Essex
Schmidt later his statement, claiming he “misspoke”. Yet his comment reflects a common view in the tech industry – that progress is dependent on intensive work patterns and keeping a close eye on staff.
Companies such as Amazon have implemented worker tracking systems. Others promote a culture of as a necessary part of innovation.
But this mindset overlooks the crucial role that an engaged and happy workforce plays in creating beneficial technology. Studies , for example, that remote working and better work-life balance often lead to increased productivity rather than hindering progress.
History also shows that empowering workers and fostering a democratic approach has accelerated technological breakthroughs. The movement, where information is shared in software development, is a case in point. Wikipedia is another example – a success story built entirely on volunteer contributions and collective effort.
In AI too, there has been rapid progress with projects, which openness and collaboration, such as language models similar to ChatGPT known as and . This demonstrates that democratising access to AI tools and knowledge can accelerate progress.
Meanwhile, many of the ethical challenges in AI development – from algorithmic bias to privacy concerns – stem from rushed development cycles and a lack of diverse perspectives.
For instance, in facial recognition systems reportedly emerged because development teams were working under pressure to deliver results quickly. The , which exposed the misuse of Facebook user data, illustrated the risks of prioritising growth and profit over privacy and social impact.
The drive for relentless productivity and market dominance has also led to the emergence of “digital sweatshops” – associated with AI development.
These include “factories” where workers are exposed to traumatic material for long hours with minimal support (a spokesperson for Facebook’s parent company it takes its responsibility to content reviewers seriously, with “industry-leading pay, benefits and support”.) Or the data processing operations connected to machine learning where workers in perform repetitive tasks for little reward.
Companies such as Facebook, Google and Amazon have been criticised for these crucial (but often overlooked) aspects of AI development to contractors with poor working conditions. And they highlight the human cost of rapid AI advancement, where the real motivation is often about and maximising shareholder value.
This model also leads to innovations that fail to address broader social and ecological challenges. The substantial associated with AI development shows the urgent necessity for more considered, sustainable methods.
But these are more likely to emerge from well-treated teams of people, who are granted the autonomy to the wider implications of their work. They will not come from rigid hierarchies focused solely on immediate financial returns.
Herein lies the false binary between worker power and technological advancement. The evidence that when executives exert too much control, the development of socially beneficial technology is hindered. They simply won’t provide what empowered workers and open collaboration can bring to the table.
Socially beneficial intelligence
Worker-led initiatives have also been at the forefront of ethical technology development. For example, Google employees’ protest against the company’s involvement with , a US military AI scheme, was a success. And Amazon workers have continued to for the company to improve its environmental credentials.
Schmidt spoke of “winning” in the AI race. But what exactly is being won through techniques that prioritise corporate control and worker exploitation? Often the result is unethical technology developed under exploitative conditions – technology which serves narrow corporate interests rather than social needs.
But the future of AI and other emerging technologies should not be driven solely by market forces. Innovation does not require oppressive work conditions or excessive corporate control.
And technological progress and social progress are not mutually exclusive. In fact, they can be mutually strengthening. A truly successful AI industry should be one that produces innovative technologies in a way which empowers workers, deals with ethical considerations, and makes a positive contribution to society.
