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New Report Forecasts Machine Learning Impacts to 2030

Australia’s economy benefits, UK economy takes hit; policymakers must focus on investing in skills and training, keep data safe, and investing in R&D and technology.

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A new study released by The Economist Intelligence Unit ran three econometric scenarios to 2030 on five areas: the United States, the United Kingdom, Australia, Japan, and the Asian region as a whole. Two scenarios in the report (Risks and Rewards: Scenarios Around the Economic Impact of Machine Learning), commissioned by Google, assumed greater human productivity thanks to upskilling and greater investment in technology and access to open source data.  A third scenario assumed insufficient policy support for structural changes in the economy.

The results showed that although the fears of those pessimistic about the impact of machine learning (and artificial intelligence in general) may be overblown, the optimists’ claims are not entirely supported, either. The other area of the study, a look at the impact of machine learning on four industries, reaches a similar conclusion. Transportation, healthcare, energy, and manufacturing are already benefiting from the use of machine learning and will continue to do over the forecast period.  However,  many of these benefits will be incremental improvements in safety and efficiency rather than massive step changes.

For firms developing machine learning and for those using it, the reports finds that communication between themselves and with the public and policymakers needs to improve. This includes doing better to manage expectations about the impact of machine learning, acknowledging the potential risks as well as the rewards, improving trust and transparency, and educating the public so that knowledge gaps are not filled with misinformation and distortion.

Policymakers, for their part, face several important choices about machine learning and its impact. Chief among them is investing in skills and education, not just STEM skills. The demand for “soft skills,” such as team building and critical thinking, is set to rise, which means technical education and training alone will not help economies to cope with the churn in labor markets machine learning is likely to cause.

Getting policy right on data and investing in R&D and technology will also be critical. The concerns of citizens about privacy and the security of personal data need to be assuaged so data can continue to flow within and between countries. The public sector also needs to return to investing in R&D so that it isn’t only the private sector that is advancing technology.   

You can download the full report here.

The Economist Intelligence Unit is a global business intelligence provider. It is the business-to-business arm of The Economist Group, which publishes The Economist newspaper. The Economist Intelligence Unit provides timely, reliable. and impartial analysis on worldwide market trends and business strategies. More information can be found at

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