Opinion
Artificial Intelligence is on the March. But is Government Ready?
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AI and other advanced technologies can be thought of as tools that are used across multiple industries in our economy and in multiple facets of our life. As such, it would seem difficult to create an AI-specific agency with a specific domain, separate from other existing agencies.
By Robert Seamans
Technology has advanced rapidly along several related fronts. In just the last few years, there have been dramatic improvements in robotics, sensors, and machine vision, and Artificial Intelligence (AI) can now perform better, per Stanford’s AI Index, than humans on multiple dimensions, including image recognition, speech recognition, translation, and strategy games such as Go, Poker and chess.
In pursuit of profits from AI-enabled business models, firms are now investing lots of money in these technologies. Worldwide industrial robotics shipments have increased from an annual average of about 100,000 units prior to 2010 to almost 300,000 annual shipments by 2016. Investment in AI startups has gone from less than $500 million annually prior to 2010 to over $4 billion in 2016. According to estimates by McKinsey Global Institute, investment in AI-related projects by established companies was between $18 billion and $27 billion in 2017.
Worries about potential downsides from adoption of these technologies have led to calls for new regulations. For example, data portability could address declining competition between dominant tech platforms and a Universal Basic Income could address mass joblessness arising from automation. Due to lack of data, however, little is known about the efficacy and tradeoffs involved with these types of new policies.
Read the full Forbes article.
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Robert Seamans is Associate Professor of Management and Organizations
In pursuit of profits from AI-enabled business models, firms are now investing lots of money in these technologies. Worldwide industrial robotics shipments have increased from an annual average of about 100,000 units prior to 2010 to almost 300,000 annual shipments by 2016. Investment in AI startups has gone from less than $500 million annually prior to 2010 to over $4 billion in 2016. According to estimates by McKinsey Global Institute, investment in AI-related projects by established companies was between $18 billion and $27 billion in 2017.
Worries about potential downsides from adoption of these technologies have led to calls for new regulations. For example, data portability could address declining competition between dominant tech platforms and a Universal Basic Income could address mass joblessness arising from automation. Due to lack of data, however, little is known about the efficacy and tradeoffs involved with these types of new policies.
Read the full Forbes article.
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Robert Seamans is Associate Professor of Management and Organizations