From automated check-outs in grocery stores to autonomous vehicles, automation and artificial intelligence (AI) is here to stay, prompting fears of robots replacing humans.
The latest McKinsey Global Institute briefing note, which was published in June 2018 for the Tech4Good summit organized by the French government, addresses “both the promise and the challenge” of automation and AI in the workplace and provides a list of ten things we need to solve for.
Accelerating progress in AI and automation is creating opportunities for businesses, the economy, and society.
With this rapid technological progress, we have new generations of more capable autonomous systems with the potential to transform business and contribute to economic growth, but challenges remain, including the need to address challenges in the use of AI techniques, avoiding potential bias in the training data and algorithms, as well as data privacy, malicious use, and security.
How AI and automation will affect work
About half of the activities (not jobs) carried out by workers could be automated, including physical activities in predictable and structured environments, data collection, and data processing. While jobs will decline until 2030, new jobs will be created during the same period. It is most likely that we will see more jobs changed than lost or gained as machines complement human labor in the workplace.
Key workforce transitions and challenges include digital platforms, the gig economy, and the rise of tech-enabled independent work.
Workers will need different skills to thrive in the future workplace, with many workers needing to change occupations. Workplaces and workflows will change as more people work alongside machines, and automation will likely put pressure on average wages in advanced economies
Ten things to solve for
In the search for appropriate measures and policies to address these challenges, the McKinsey study suggests that rather than seeking to roll back or slow diffusion of the technologies, companies should harness automation and AI to benefit from this enhanced performance and productivity contributions as well as social benefits. The way to do this is to find more actionable and scalable solutions in these ten key areas:
- Ensuring robust economic and productivity growth
- Fostering business dynamism
- Evolving education systems and learning for a changed workplace
- Investing in human capital
- Improving labor market dynamism
- Redesigning work
- Rethinking incomes
- Rethinking transition support and safety nets for workers affected
- Investing in drivers of demand for work
- Embracing AI and automation safely