Artificial intelligence (AI) is everywhere, generating excitement about how it could transform our lives in multiple ways. Yet the technology is very likely to be disruptive. Businesses and policymakers must try to capture the full value of what AI has to offer while avoiding any risks.
The concept of AI has been around for more than half a century, and many of us have lived through prior periods of excitement followed by dull stretches of disappointment — “AI winters” — when the promise of A.I tech failed to live up to expectations.
However, recent progress in AI techniques and algorithms, combined with a huge increase in computing power and an explosion in the amount of data available, has created significant and tangible advances, promising to generate massive value for businesses, individuals, and the whole of society.
Companies are currently applying AI techniques in sales and marketing to personalize product recommendations to the desires of individual customers. Also, in manufacturing, AI is improving predictive maintenance by using “deep learning” and applying calculations to high volumes of data from sensors.
By simply deploying algorithms to detect anomalies, firms can decrease the downtime of machinery and equipment, from assembly lines to jet engines.
Recent research has highlighted hundreds of such business cases, which together have the potential to create between €.3.17tn and €5.25tn in revenue every year.
AI can contribute to economic growth by augmenting and substituting labor and capital inputs, spurring innovation, and boosting wealth creation and reinvestment.
It’s estimated that AI and analytics could add as much as €11.78 trillion to total global output by 2030, increasing the yearly rate of global GDP growth by more than one percentage point.
Research suggests AI will be most beneficial if it focuses on innovation-led growth, and if this growth is accompanied by proactive managerial measures — particularly, retraining workers to give them the skills they will need to excel in the new working era.
As AI starts to contribute to faster GDP growth, social welfare is also likely to increase. It’s estimated that AI and related technologies could improve welfare by 0.5%-1% a year between 2020 and 2030.
That would be very similar to the social impact of previous waves of technology adoption, including the internet and communications technology revolution.
AI is likely to help to improve many aspects of wellbeing, from job security and living standards to educational practices and environmental sustainability.
Its most significant positive contribution to human welfare may come in the areas of healthcare and longevity: AI-driven drug discovery is many times faster than conventional research. And AI-based traffic management could reduce the negative impact of air pollution on health by 3%-15%.
AI will also help to address a wide range of social challenges. If implemented carefully, this technology could help the world meet all 17 of the United Nations Sustainable Development Goals.
AI tech that is currently being field-tested includes disease detection systems, smuggler trackers (to combat human trafficking), and tech that helps to predict and aid in disaster relief efforts.
There are still some challenges that must be addressed. These technologies are still very much in their infancy, with more breakthroughs needed to make them applicable on a global scale.
In the fastest possible automation-adoption scenario, up to 375m workers worldwide will have to switch occupational categories by 2030, while some 75m will be affected in some professional capacity. The nature of almost every job type is likely to change, as people are forced to interact with smart machines in the workplace.
That will garner the need for new skills, presenting companies, and policymakers with the challenge of training and retraining the workforce at a massive scale. And as demand for high tech-skill jobs grows, low-skill workers could be left behind, resulting in severe economic imbalance.
The diffusion of AI could also raise challenging ethical questions. Some of these may relate to the use and potential misuse of the technology in areas ranging from public surveillance and advanced military applications to social media.
Algorithms and the data used to train them may introduce new biases, or perpetuate and institutionalize existing types. Other critical concerns include the use of personal information, privacy, cybersecurity, and “deep fakes” used to manipulate some election results or perpetrate large-scale global fraud.
Despite these challenges, AI is likely to generate a tremendous amount of value for all of us, if policymakers and businesses act smartly and swiftly to capture its full benefits…
The much-anticipated AI Spring could be just around the corner!